Food plant economics

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FOOD PLANT ECONOMICS

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FOOD SCIENCE AND TECHNOLOGY Editorial Advisory Board Gustavo V. Barbosa-Cánovas Washington State University–Pullman P. Michael Davidson University of Tennessee–Knoxville Mark Dreher McNeil Nutritionals, New Brunswick, NJ Richard W. Hartel University of Wisconsin–Madison Lekh R. Juneja Taiyo Kagaku Company, Japan Marcus Karel Massachusetts Institute of Technology Ronald G. Labbe University of Massachusetts–Amherst Daryl B. Lund University of Wisconsin–Madison David B. Min The Ohio State University Leo M. L. Nollet Hogeschool Gent, Belgium Seppo Salminen University of Turku, Finland John H. Thorngate III Allied Domecq Technical Services, Napa, CA Pieter Walstra Wageningen University, The Netherlands John R. Whitaker University of California–Davis Rickey Y. Yada University of Guelph, Canada

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FOOD PLANT ECONOMICS ZACHARIAS B. MAROULIS GEORGE D. SARAVACOS

Boca Raton London New York

CRC Press is an imprint of the Taylor & Francis Group, an informa business

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CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487‑2742 © 2008 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid‑free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number‑13: 978‑0‑8493‑4021‑5 (Hardcover) This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the conse‑ quences of their use. No part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www. copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC) 222 Rosewood Drive, Danvers, MA 01923, 978‑750‑8400. CCC is a not‑for‑profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging‑in‑Publication Data Maroulis, Zacharias B., 1957‑ Food plant economics / Zacharias B. Maroulis and George D. Saravacos. p. cm. ‑‑ (Food science and technology ; 171) Includes bibliographical references and index. ISBN‑13: 978‑0‑8493‑4021‑5 (alk. paper) ISBN‑10: 0‑8493‑4021‑7 (alk. paper) 1. Food industry and trade. 2. Chemical engineering. 3. Chemical plants. I. Saravacos, George D., 1928‑ II. Title. III. Series. TP370.5.M36 2007 664’.024‑‑dc22 Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com

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to Anda and Vassilis Maroulis and Katie Saravacos

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CONTENTS I. Preface I. List of Application Examples

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1. Introduction I. INTRODUCTION II. FOOD SYSTEM III. FOOD PROCESS TECHNOLOGY IV. FOOD PLANT ECONOMICS V. ECONOMIC ANALYSIS OF FOOD PROCESSING PLANTS 1. Food Preservation Plants 2. Food Manufacturing Plants 3. Food Ingredients Plants VI. FOOD RESEARCH AND DEVELOPMENT 1. Food Science 2. Food Engineering

1 2 3 4 5 6 6 7 8 9 9

2. Structure of the Food Industry I. INTRODUCTION II. FOOD SYSTEMS 1. The US Food System 2. The US Food Processing Industry a. Industry Classification b. Food Consumption c. Value Added in Food Processing d. Raw Materials e. Labor and Energy 3. Food Trade Industries 4. The European Food Processing Industry a. Dairy Industry b. Sugar c. Edible Oils d. Fruits and Vegetables e. Grain Milling f. Baking Industry g. Confectionery h. Meat Industry i. Fish Industry k. Coffee Industry 5. Multinational Food Companies 6. Food Distribution Systems © 2008 by Taylor & Francis Group, LLC

13 14 14 15 16 17 19 19 19 20 20 22 22 22 22 23 23 23 23 23 23 24 25

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3. Overview of Food Process and Plant Design I. INTRODUCTION II. FOOD PROCESS DESIGN 1. Process Flowsheets 2. Material and Energy Balances 3. Sizing and Costing of Equipment III. FOOD PLANT DESIGN 1. Plant Buildings a. Plant Location b. Building Construction 2. Food Plant Safety 3. Hygienic Design 4. Cleaning of Equipment 5. Plant Maintenance IV. FOOD PLANT UTILITIES 1. Process Water 2. Steam 3. Electricity 4. Plant Effluents V. FOOD PLANT ECONOMICS 1. Capital Investment Cost 2. Operating Expenses 3. Food Plant Logistics

27 28 29 29 33 34 35 35 35 36 37 39 39 40 40 40 41 41 42 43 43 44

4. Process Engineering Economics I. MONEY FLOW IN A BUSINESS ENTERPRISE II. CAPITAL COST 1. Fixed Capital Cost 2. Working Capital Cost III. MANUFACTURING COST IV. CASH FLOW ANALYSIS 1. Construction Period 2. Operating Period 3. Discounted Cash Flow V. PLANT PROFITABILITY VI. SENSITIVITY ANALYSIS

47 49 50 56 60 65 65 67 74 76 78

5. Capital Cost of Food Plants I. INTRODUCTION 1. Unit Operations in Food Processing 2. Mechanical Processes a. Mechanical Transport Operations b. Mechanical Processing Operations c. Mechanical Separation Operations 3. Food Packaging Processes II. QUOTATIONS FROM FABRICATORS © 2008 by Taylor & Francis Group, LLC

83 83 85 85 86 86 86 90

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III. EQUIPMENT COST ESTIMATION 1. Effect of Material of Construction 2. Effect of Pressure on Equipment Cost 3. Effect of Inflation on Equipment Cost IV. DATA FOR PRELIMINARY EQUIPMENT COST ESTIMATION V. SHORT-CUT EQUIPMENT SIZING 1. Pumps and Blowers 2. Compressors 3. Conveyor Belts 4. Screw Conveyors 5. Size Reduction 6. Vessels 7. Heat Exchangers 8. Evaporators 9. Dryers 10. Filters 11. Continuous Flow Sterilizers

92 93 94 95 98 120 120 121 122 123 124 124 126 127 128 130 130

6. Operating Cost of Food Plants I. INTRODUCTION II. RAW MATERIALS III. FOOD PRODUCT COST DATA 1. Retail Prices 2. Farm Prices 3. Retail-to-Farm Price Ratios IV. PACKAGING MATERIALS V. UTILITITIES 151 VI. UTILITY COST ESTIMATING MODEL 1. Fuel oil Cost 2. Natural gas Cost 3. Electricity Cost 4. Steam Cost 5. Cooling Water Cost 6. Refrigeration Cost 7. Energy-Related Utilities Cost 8. Non Energy-Related Utilities Cost 9. Waste Treatment Cost VII. LABOR VIII. LABOR COST ESTIMATING MODEL 1. Factorial Method 2. Annual Operating Time 3. Manpower 4. Labor Rates

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135 135 137 137 141 146 151 154 154 156 158 160 160 161 161 164 164 165 166 166 167 168 168

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7. Food Preservation Plants . INTRODUCTION 1. Food Preservation Plants 2. Application Examples I. TOMATO PASTE PLANT 1. Process Technology a. Raw Materials b. Concentrated Tomato Products c. Inspecting/Washing d. Crushing/Finishing e. Concentration f. Sterilization/Packing g. Plant Effluents 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis a. Break-Even Analysis b. Effect of Resource Prices and Tax and Debt Characteristics II. ORANGE JUICE CONCENTRATE PLANT 1. Process Technology a. Raw Materials b. Washing/Grading c. Juice Extraction /Finishing d. Centrifuging/Debittering e. Juice Pasteurization f. Juice Concentration g. Aseptic Packing and Storage h. Peel/Pulp Drying i. Peel Oil Extraction j. Plant Effluents 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis III. UHT STERILIZED MILK PLANT 1. Process Technology a. Raw Material b. Separation/Homogenization c. UHT Sterilization d. Aseptic Packaging 2. Process Flowsheet 3. Material and Energy Requirements © 2008 by Taylor & Francis Group, LLC

175 176 177 178 178 178 178 179 179 179 179 179 180 183 184 185 188 190 190 191 194 194 194 194 194 195 195 195 195 196 196 196 196 199 200 201 203 205 208 208 208 208 208 208 208 210

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4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis IV. FRUIT CANNING PLANT 1. Process Technology a. Raw Materials b. Washing/Pitting/Peeling/Grading b. Filling/Syruping c. Sealing/Sterilization of Cans d. Labeling/Packing/Storage 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis V. VEGETABLE FREEZING PLANT 1. Process Technology a. Raw Materials b. Cleaning/Grading/Cutting c. Blanching d. Freezing/Packing e. Storage 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis VI. VEGETABLE DEHYDRATION PLANT 1. Process Technology a. Raw Materials b. Washing/Peeling c. Dicing/Blanching/Sulfiting d. Drying e. Packing 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis VII. TECHNO-ECONOMIC COMPARISON VIII. SUPPLIERS OF MAJOR FOOD PROCESSING EQUIPMENT

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211 212 215 217 220 220 220 220 221 221 221 221 224 226 227 228 229 232 232 232 232 232 233 233 233 233 238 238 239 242 244 244 244 244 244 244 245 245 245 249 250 252 253 256 266

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8. Food Manufacturing Plants . INTRODUCTION I. BREAD MANUFACTURING PLANT 1. Process Technology a. Bread Ingredients b. Dough Preparation c. Fermentation d. Dough Mixing e. Dough Dividing/Rounding f. Pre-proofing g. Bread Molding/Panning h. Proofing i. Baking Oven j. Depanning/Cooling of Bread k. Slicing/Packaging l. Storage m. Frozen Dough 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis a. Break-Even Analysis b. Effect of Resource Prices and Tax and Debt Characteristics II. YOGURT MANUFACTURING PLANT 1. Process Technology a. Raw Materials b. Standardization/Mixing c. Homogenization d. Heat Treatment e. Fermentation f. Mixing of Yogurt g. Packaging h. Cooling/Storage 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis III. WINE PROCESSING PLANT 1. Outline of Process Technology a. Raw Materials b. Grape Crushing c. Juice Expression d. Fermentation e. Ageing of Wine © 2008 by Taylor & Francis Group, LLC

269 274 274 274 275 275 275 275 276 276 276 276 276 277 277 277 277 280 280 281 284 287 287 287 290 290 290 290 290 290 291 291 291 291 292 292 295 295 299 301 304 304 304 304 304 305 305

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f. Wine Filtration g. Bottling of Wine h. Bottle Storage i. Plant Wastes 2. Process Flowsheet 3. Material and Energy Requirements 4. Capital Investment 5. Operating Expenses 6. Plant Profitability 7. Sensitivity Analysis IV. ECONOMIC COMPARISON

305 306 306 306 306 306 309 309 313 315 318

9. Food Ingredients Plants . INTRODUCTION I. BEET SUGAR PLANT 1. Outline of Process Technology a. Raw Materials b. Sugar Extraction c. Juice Concentration d. Sugar Crystallization e. Centrifugation f. Drying of Sugar g. Drying of Beet Pulp h. Sugar Molasses i. Plant Effluents j. Sugar Storage 2. Preliminary Sugar Plant Design 3. Outline of Sugar Economics II. OVERVIEW OF PROCESS PLANT OPTIMIZATION 1. Parametric Optimization 2. Structural Optimization 3. Cogeneration in Food Processing

323 326 326 326 326 328 328 329 329 329 329 329 330 330 335 336 336 338 339

Appendices I. GLOSSARY OF ECONOMIC TERMS II. NOTATION AND CONVERSION TO SI UNITS III. USEFUL THERMOPHYSICAL PROPERTIES OF WATER IV. THERMOPHYSICAL PROPERTIES OF SOME FOOD MATERIALS V. RHEOLOGICAL PROPERTIES VI. OVERALL HEAT TRANSFER COEFFICIENTS VII. ACCOMPANYING CD .

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PREFACE Food Plant Economics can be considered as part of process economics, which was developed in chemical engineering and has been applied successfully in the chemical process industries. Food economics involves the entire food system, comprising of production of agricultural raw materials, food processing, and food distribution. In addition to economic considerations, food production should meet special requirements of customer acceptance, human nutrition, and food safety. The purpose of this book is to analyze the economics of food processing plants. Food Plant Economics is related to the design and operation of food processes, processing equipment, and processing plants. It utilizes recent advances in process economics and computer technology, particularly computer aided design (CAD). Simplified spreadsheet (Excel) applications are convenient in preliminary plant design and plant economics. Economic analysis of food plants requires quantitative data from the design and operation of food processes and processing plants. For preliminary economic analysis, material and energy balances, equipment sizing, and plant operating costs are necessary. The first 3 chapters of the book are devoted to the background of Food Plant Economics. Chapter 1 outlines the subjects discussed in the book and summarizes the recent advances in food process technology and in food research and technology. Chapter 2 discusses the structure of the Food System with emphasis on the United States and European food industries. Chapter 3 reviews the principles of modern design of food processes, processing equipment, and processing plants. Chapter 4 reviews critically process economics in relation to food plant economics. The concepts of capital cost, manufacturing (operating) cost, and cash flow are discussed and applied to the estimation of plant profitability. Sensitivity analysis is discussed briefly in relation to food processing plants. Chapter 5 discusses the estimation of capital investment of food plants, applying modern process economics techniques. The conventional engineering cost indices for processing equipment and plants are explained in relation to food plant design. Engineering data, derived from the literature, are presented for the preliminary cost estimation of process plants. Cost data of selected food processing equipment can be provided by equipment suppliers. A shortcut design procedure, used in this book, is outlined, including some useful rules of thumb. Chapter 6 covers the estimation of operating (or manufacturing) cost of food plants, which consists of the cost of raw materials, labor, utilities, maintenance, depreciation, and local taxes. Statistical data on the prices of US food products are presented, showing the differences among the farm, retail, and processed products. The cost of food packaging materials is an important cost component of the manufactured foods. The cost of plant utilities includes steam, fuel, electricity, refrigeration, cooling water, and waste treatment and disposal. Empirical models are presented for cost estimation of plant utilities as a function of crude oil cost.

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Chapters 7–9 discuss the economics of various food processing plants, based on the procedures of Chapters 5 and 6. A number of hypothetical food plants are considered, using established process technology and technical data from the literature, the food industry, and the suppliers of equipment. Chapter 7 deals with the economics of 6 typical food preservation plants, i.e., tomato paste, orange juice concentrate, UHT sterilized milk, fruit canning, vegetable freezing, and vegetable dehydration. The procedures and data of Chapters 4, 5, and 6, and the appendices are used for the estimation of profitability of the example food plants. Chapter 8 discusses the economics of three typical food manufacturing plants, i.e., bread, yogurt, and wine. The application examples of food plants are designed and analyzed utilizing the data of Chapters 4, 5, and 6, and the appendices. Chapter 9 reviews the design and economics of food ingredients plants, such as sugars, oils, proteins, and food chemicals. Such plants are designed and optimized using conventional chemical engineering procedures. The appendices contain tables and information useful in calculations of the various application examples of the book, such as nomenclature, conversion of units, food properties, and heat transfer coefficients. A glossary of the economic terms used in this book is included. The accompanying CD contains Excel files of equipment cost, utilities cost model, and plant economics results of application examples. The applications can be updated and modified according to the user specifications. We wish to acknowledge the contributions and help of our colleagues, associates, and graduate students at the National Technical University of Athens, especially Magda Krokida for preparing the tables and diagrams, and checking the calculations in this book. We appreciate the information provided by manufacturers and suppliers of equipment and materials, used in the design and evaluation of food plants of the application examples of this book. We hope that this book will contribute to the recognition of process economics as an important part of the developing field of food engineering. We realize that some areas of Food Plant Economics need further development, and that some other aspects should be added. The cost components of the food plants should be updated with the latest information from various suppliers and manufacturers of materials, equipment, and labor. We will appreciate the comments and criticism from readers experienced in this field. Zacharias B. Maroulis George D. Saravacos

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LIST OF APPLICATION EXAMPLES

Food Preservation Plants (Chapter 7) 1. Tomato paste 2. Orange juice concentrate 3. UHT sterilized milk 4. Fruit canning (apricots, peaches) 5. Vegetable freezing (beans, peas) 6. Vegetable dehydration (potatoes, carrots) Food Manufacturing Plants (Chapter 8) 7. Bread 8. Yogurt 9. Wine Food Ingredients Plants (Chapter 9) 10. Beet sugar

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1 Introduction

I. INTRODUCTION Commercial Food Processing converts raw agricultural or animal materials into edible intermediate or consumer food products through application of technology and labor. Farm and marine raw materials are converted to more refined, concentrated, convenient, nutritious, and more palatable food products. Large amounts of food products are processed world-wide to feed the expanding population and satisfy the consumer nutrition requirement and organoleptic preferences. Economics plays an important role in supplying sufficient quantities of food products at affordable prices, while providing considerable profit to the food producers, processors, and distributors. Food Plant Economics is a special subject of the field of Process Economics, which deals with the economic analysis of various Process Industries (Holland and Wilkinson, 1997). Economics plays an important role in the design and operation of industrial processes and processing plants (Peters et al., 2003; Couper, 2003). The design and optimization of food processes is based on the application of Food Science principles to the established techniques of Chemical Process Design. Simplified computer-aided techniques, such as the Excel spreadsheets, have been applied to the design of several food processes (Maroulis and Saravacos, 2003). Food processes, based on heat and mass transfer, such as heating, refrigeration/freezing, evaporation, dehydration, thermal processing, and mass transfer separations, can be analyzed, designed, and optimized quantitatively, using published engineering data, particularly transport properties of food materials. The design of mechanical processes and separations of solid and semisolid food materials, such as mechanical transport and storage, size reduction 1

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and enlargement, mixing and forming, mechanical separation of food parts, mechanical expression, and mechanical cleaning, are designed empirically, based mostly on technical data and specialized processing equipment, provided by equipment manufacturers and suppliers (Saravacos and Kostaropoulos, 2002). Food Plant Design is an optimum integration of Food Process Design, Equipment Design, and Process Engineering Economics. In addition, the requirements of appropriate plant buildings and hygienic (sanitary) operation should be considered (Lopez-Gomez and Barbosa-Canovas, 2005). Food Processing is characterized by some important peculiarities, such as variability and sensitivity of the raw materials, and strict safety requirements of the food products. Hygienic design and operation and food safety precede any other engineering and economic consideration of food processing plants. II. FOOD SYSTEM Food processing is one of the largest industries in most countries in terms of annual sales, raw material and product capacity, and labor force (Connor and Schiek, 1997). Food Processing is considered part of the Food System, which includes agricultural production, processing, distribution, and consumption of food products. The Food System or Food Chain is the major part of the AgroIndustrial Complex, which includes food and nonfood agricultural products. Raw materials for the food processing industries include agricultural, animal, and marine products, packaging materials, food ingredients, and food chemicals. They represent the major operating cost of the food plants. Some large food processing industries use raw food materials produced in other countries, such as the milling industry which may use large quantities of imported wheat. Food Processing contributes substantially to the national economy of a country by the significant value added to the products, which is the difference between the sales and the processing expenses. Value added includes labor, capital utilization (depreciation of equipment), taxes, and profit. Large food companies produce large quantities of semi-processed and consumer food products in continuous-flow operations. These industries require high capital investment to specialized processing and control equipment, which must be utilized continuously. Computer applications can improve the processing operations and the economics of food plant operation. Manufacture of specialized food products in relatively smaller amounts is based mostly on batch-operated processing equipment with only the necessary process control, imposed by food safety regulations. Multiple use (flexible)

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equipment is often used for several products, produced in relatively small batches. Food Distribution includes transportation, storage, and sale of food products. Food is distributed in food stores (e.g., supermarkets), food service, and food exports. The food processing and food distribution costs are increasing faster than the cost of raw materials. III. FOOD PROCESS TECHNOLOGY Traditional food process technology was based on experience and it developed from small scale to industrial production. The food preservation industry was developed mainly to preserve seasonal fruits and vegetables into food products, making them available to the consumers throughout the year. Science (Chemistry and Microbiology) and Engineering (Mechanical and Chemical) have been applied successfully at various stages in the development of Food Process Technology (Lopez-Gomez and Barbosa-Conovas, 2005). Quantitative application of unit operations requires quantitative data on the physical and engineering properties of foods (Rao et al., 2005; Saravacos and Maroulis, 2001). Food processing equipment has been adapted from equipment used in the Chemical Process Industries with some important modifications to handle sensitive food materials, without damaging the nutritive and organoleptic quality of the finished food products. Recent books on Food Processing attempt to combine the underlying principle of process engineering with the advances in Food Science and Nutrition (Ramaswamy and Marcotte, 2005). In addition to the (physical) unit operations, Food Processing involves several microbiological, biochemical, and chemical processes, which are based on Reaction Kinetics (Earle and Earle, 2003). Recent changes in food availability, production, and use are affecting world economics and management of Agriculture. Issues of food legislation, environment, food safety and quality, nutrition and health have a significant impact on traditional and new process technologies. Recent emphasis of consumers on food safety and quality, and the protection of the natural environment are observed world-wide, especially in EU and the USA. These important developments have significant economic implications and they should concern Food Plant Economics. World Food Economics is affected by agricultural food production, food processing, food trade, and food use. Food legislation, environmental issues, food safety and quality, nutrition and health affect food process technology.

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IV. FOOD PLANT ECONOMICS Food Plant Economics can be considered a specialized area of Process Engineering Economics, which has been developed mainly in Chemical Processing. (Couper, 2003; Brennan, 1998). The economic analysis of food processing plants is based on the estimation of capital cost (or fixed capital investment) and the operating cost (operating expenses). In addition, the profitability of the food plant is determined, using modern economic concepts, such as time value of money, cash flow, and depreciation. The basis of plant economic analysis is the capital cost estimate. A guide for simplified capital cost estimation was presented by Gerrard (2000). Sophisticated computer programs are used by large corporations, but useful engineering estimates can be obtained using PC spreadsheet programs. Capital cost estimates appear in balance sheets and in income statements, since most operating expenses are capital dependent. Process flowsheets (block diagrams) are used to estimate the material and energy balances of the food plant. Contrary to chemical processing, where a large number of alternative flowsheets is possible for a given process, only a limited number of food process flowsheets is possible, due to the strict process conditions, such as temperature sensitivity of foods, food safety, and hygienic requirements of food plants. Food plant capacity and material and energy balances are used in process equipment sizing and costing, and in cost estimation of utilities (steam, water, electricity). Empirical factors, such as the Lang factor, are used to estimate the costs of installation, construction, engineering, and various overhead charges. Capital cost estimates are used in deciding the development of a new plant project or in expanding and revamping existing plants. Cost estimates are approximations and the probable range of accuracy should be given, whenever possible. They are valid for a given time and location, and adjustments should be made when transferring such figures. Operating costs (expenses), contrary to capital costs, are not found easily in the literature, because such information is of proprietary nature. They can be divided into process operating costs and nonprocessing costs. Process operating (manufacturing) costs include costs of raw materials (agricultural, marine, intermediate food materials, packaging materials, and chemicals), utilities (steam, fuel, water, and electricity), personnel, and capitalrelated costs (Brennan, 1998). Nonprocessing (nonmanufacturing) costs include costs of distribution, selling, research and development, and the cost of running the company, which can be allocated to the product in question. The raw material requirements are estimated from detailed material and energy balances in the food process flowsheet. The unit costs of food raw materials depend on the availability of agricultural materials and the location of the

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food plant. The supply and prices of raw materials are negotiated by contracts, or purchases are made in the “spot” market. There is a wide variation of prices from country to country and from season (year) to season. Large quantities of some raw materials are available in international trade at relatively stable prices, e.g., wheat, corn, and soybeans. Food Packaging constitutes a major part of food processing. The cost of food packaging materials is very important in overall food plant economics, especially in manufacturing food products in individual consumer packages. Food preservation and manufacturing plants use either aseptic packaging systems or metallic and plastic individual packages. Food ingredients plans, e.g., sugar, starch, and vegetable oils are packed in bulk containers and they are transported to the food plant for further processing. Utility requirements can be estimated from material and energy balances on the process flowsheet. In estimating energy requirements, thermal losses to the environment should be taken into account (25% of the theoretical energy requirements). Utility charges are usually expressed as $/GJ, $/MWh, or $/t of product. Utility costs vary with plant location and availability of fuel, water, and electricity. International energy crises, such an oil crisis, will affect strongly the utilities costs. Personnel requirements include process labor (often working in shifts), maintenance labor, and plant staff and management (engineering support, laboratory, accounting, and secretarial personnel). Food plant profitability requires the estimation of several economic quantities, such as depreciation, cash flow, taxes, net income, and payout time (Couper, 2003). Profitability analysis of a new venture will show whether an investment should be made. Sensitivity and/or uncertainty analyses examine various scenarios to determine the effect on profitability of changes in sales price, sales volume, capital requirements, and operating expenses. Feasibility analysis includes items from estimating the capital requirements through sensitivity and uncertainty analyses. V. ECONOMIC ANALYSIS OF FOOD PROCESSING PLANTS For the purposes of this book, food processing plants can be divided into three major groups, i.e., Food Preservation Plants, Food Manufacturing Plants, and Food Ingredients Plants. This loose division is intended to emphasize underlying processing, engineering, and economic principles in a much diversified food industry. Costs of a number of food processing plants, designed and operated in various countries, were published by Bartholomai (1987).

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1. Food Preservation Plants Food Preservation includes thermal, refrigeration and freezing processes, concentration and dehydration, and nonthermal preservation. Food preservation plants utilize agricultural raw materials, which are usually seasonal and sensitive to mechanical damage and to microbial spoilage. The food plants are normally located near the agricultural production area to minimize spoilage during transportation of raw materials. The quality of raw materials and preserved foods is highly depended on the agricultural growing conditions and the variety of the product. The cost of raw materials is often the major operating cost of preserved food products. Freezing is the most expensive preservation process, followed by thermal processing and dehydration. Nonthermal preservation methods, such as radiation processing and high pressure technology, are still in the developing stage and they are considered as not economical at the present time. The design and economics of 6 food preservation plants are analyzed, using process engineering and economics principles, and process technology data from the literature. The plants discussed involve traditional preservation methods of fruits/vegetables and milk, such as concentration/dehydration, thermal processing, and freezing. The application examples represent hypothetical food processing plants of medium commercial size. Several simplifying assumptions were made concerning the engineering design, the processed product, and the economics of plant design and operation. Simplified computer-aided design, using Excel spreadsheets, is used in the engineering and economic analysis of the food processing plants. 2. Food Manufacturing Plants Food manufacturing plants include several small and medium sized processing plants, often batch-operated, which produce a multitude of food products from agricultural, animal, and marine raw materials. They apply the classical food preservation processes of heating, refrigeration/freezing, concentration and dehydration, fermentation, and use of antimicrobial agents. Packaging plays a very important role in the economics of such plants, since the food products are usually delivered to the consumers in rather expensive individual packages. These plants use several mechanical processing operations, such as mixing, mechanical separation, mechanical expression, forming, extruding, homogenization, and agglomeration. Combined mechanical and heating operations are applied in baking and roasting processes. The new field of Food Prod-

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uct Engineering is applied to formulate and produce foods of desired mechanical structure and texture, food quality, and food safety. Food manufacturing plants are located preferably near urban centers for easy access to the consumers. The raw materials of small/medium food plants are often transported from distant production areas or imported from other countries. Refrigeration or freezing may be needed for the storage and distribution of heat-sensitive food products, increasing substantially the cost. Hygienic plant operation and food safety are of paramount importance, since microbial spoilage and chemical changes of most manufactured products are possible during processing. Three different food manufacturing plants are used as application examples in this book, i.e., bread baking, yogurt manufacture, and wine processing. They represent hypothetical food plants of medium to large commercial size, using established technology. Several simplifying assumptions were made in the engineering design, the plant economics, and the food product specifications. The engineering assumptions and technical data are in accordance with the established engineering technology, reported in the literature, and applied in practice. 3. Food Ingredients Plants Food ingredient plants produce various ingredients used in food processing, such as sugars, starches, vegetable oils, proteins, food extracts, pectins, natural flavors and gums, and food chemicals. Several food ingredients are supplied by the Fine Chemicals Industry, such as artificial sweeteners, antioxidants, preservatives, amino acids, and vitamins. The raw materials of the natural food ingredients are bulk (commodity) agricultural products, available in large quantities and at relatively low cost, e.g., sugar beets or sugar cane, soybeans, and corn. Some food ingredients are produced from by-products of food processing plants, e.g., citrus or apple peels, cheese whey, and fish waste. The design of food ingredient plants is based on the classical unit operations of Chemical Engineering with optimum use of raw materials and utilities (energy). Instrumentation and process control are essential, and the plant effluents are treated to meet the environmental requirements. Hygienic and food safety requirements of such plants are less strict than food preservation and food manufacturing plants, since microbial spoilage and chemical deterioration of food ingredients are very limited. Less expensive process equipment can be used, similar to the chemical process industries.

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The design and economics of a hypothetical food ingredient plant, i.e., beet sugar processing, is outlined as an example, using process engineering and economic principles, and technology data from the literature.

VI. FOOD RESEARCH AND DEVELOPMENT Food R&D provides the knowledge to produce and deliver the safe and nutritious foods needed to improve the life of the consumers. A fundamental understanding of the Chemistry, Microbiology, and Physical Properties of foods is needed in any industrial application of Food Preservation or Food Manufacturing. In the US, basic or generic food research is conducted primarily in State Universities. Applied research and development is conducted mainly in Government Laboratories, in Private Laboratories, and in the Industry. In several countries applied research and development may be carried out in State Universities. The State Universities and the State Agricultural Experiment Stations have contributed decisively in the development and growth of the US Food Industry. They succeeded in combining the agricultural output of farm raw materials with the development of food products needed for national consumption and export. The Agricultural Experiment Stations were particularly useful for the small and the intermediate-size food industries, which could not afford a R&D Laboratory. Recent advances in Science and Technology have led to the development of Centers of Advanced Technology in the US, which utilize the expertise and equipment of various University Departments to address difficult food research problems. The growth of large food industrial corporations has created the need for fundamental research, which can be provided only by high-quality Research Universities. The research needs in Food Science and Technology were discussed by Heldman (2004). Large food companies have R&D departments and laboratories, which develop new food products and processes, and oversee the production of safe and quality food products. Large international food companies operate central R&D departments, which can address food research, development, and quality problems from food plants, operated in different parts of the world. The food processing industries employ a smaller share of scientists and engineers and spend considerably less in R&D than the other US manufacturing industries. Food industries employ biological and agricultural scientists, chemists, engineers, and other scientists. R&D expenditures (1991) of the food processing industries was 1.4 G$, corresponding to 0.4% of the net sales. All US industries spent 104 G$ for

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R&D in 1991, corresponding to 4.7% of the net sales (Connor and Schick, 1997). Food industries spend most of the research funds in applied research and development and only about 5–10% in basic research. Applied food research is concerned with product development, process engineering, and quality control. A significant part of the applied R&D research is outsourced (contracted) to independent laboratories. Food processors import innovations from various other manufacturers, such as instrument and control, packaging, industrial equipment, and food ingredients. Food processors need the R&D performed in Universities, Government agencies, consultants, and suppliers to improve their R&D efforts and increase their innovative activities. Food R&D related to the Food Industry can be divided into two broad categories, i.e., Food Science and Food Engineering. A brief review of current Food R&D in these areas is outlined below. 1. Food Science Research in Food Science is concerned mainly with the development of new or the improvement of existing food products acceptable to the consumers. To a lesser degree it is directed to the development of new or improved food processes, resulting in more efficient operations. Food Science is based on the principles and techniques of Food Chemistry, Food Microbiology, and Food Engineering Science. Food Research projects in Universities include food composition and structure/texture, microbial kinetics, transport properties of foods, shelf-life prediction, and new preservation technologies. Emphasis is on food quality, food pathogens, and predictive modeling. The application of recent advances in Molecular Biology and Biotechnology to food systems is also investigated. Food quality and safety in Food Processing is of paramount importance and basic and applied research is carried out for better understanding and control. Recent quality management systems include Hazard Control Critical Points (HACCP), international quality standards (ISO 9000), and Total Quality Control (TQC). 2. Food Engineering Fundamental Food Engineering research is focused on the physical and engineering properties of foods, which are required in the quantitative design of food processes, food processing equipment, and food processing plants (Rao et al., 2005). Of particular importance are the transport properties of foods, which are affected strongly by the physical structure of the product (Saravacos and Maroulis, 2001).

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The design of food processes and food processing equipment has advanced remarkably during the recent years by the application of the Chemical Engineering principles and the use of simplified computer design techniques (Maroulis and Saravacos, 2003; Saravacos and Kostaropoulos, 2002). Modern economic analysis is essential in evaluations of the efficiency and profitability of food processing plants. Control and automation of food processes and processing plants requires research on on-line sensors of process parameters, such as temperature, moisture content, and composition. Computerized systems can be applied to many food plants. Modern food plants are using increasingly continuous flow processes, which can be controlled more readily than the batch processes. Research on efficient and economic methods of treatment and disposal of food wastes, especially wastewater and solids, is necessary to comply with the strict environmental laws and regulations. In addition to conventional Process Engineering, recent research is focused on Food Product Engineering, i.e., the design and manufacture of food products based on scientific principles of Physical Chemistry, Materials Science, and Chemical Engineering (Cussler and Moggridge, 2001). Food Product Engineering is related to the molecular structure, nanostructure, microstructure, and macrostructure of food products, which affect strongly their texture, and the rheological, heat, and mass transfer properties (Aguilera and Stanley, 1999; Saravacos and Maroulis, 2001). The food industry is concerned mainly with food products which are sold to the retail consumers in relatively small packages. Processing of foods and filling in individual packages requires packages and high speed packaging equipment, which can handle thousands of units per hour (Saravacos and Kostaropoulos, 2002; Valentas et al., 1997). Specialized packaging materials are provided by experienced companies. The manufacture of consumer food products is increasingly using purchased semi-processed food materials (food ingredients), such as concentrated juices and pulps, dehydrated foods, and isolated food components. Food chemicals, approved for food safety, are provided by specialized chemical companies. Food Engineering is concerned with the control and automation of the food plants, which can reduce labor, improve the yield, and increase the product throughput. Process modeling, control and sensors require an understanding of the complex food structure, especially the solid and semi-solid materials.

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REFERENCES Aguilera JM, Stanley DW, 1999. Microstructural Principles in Food Processing and Engineering. Aspen Publications. Bartholomai A, 1987. Food Factories: Processes, Equipment, Costs. VCH Publishers. Brennan D, 1998. Process Industry Economics. IChemE. Connor JM, Schiek WA, 1997. Food Processing. An Industrial Power-house in Transition, 2nd Edition. Wiley. Couper JR, 2003. Process Engineering Economics. Marcel Dekker. Cussler EL, Moggridge GD, 2001. Chemical Product Design. Cambridge University Press. Earle R, Earle M, 2003. Fundamentals of Food Reaction Technology. Leatherhead Food Research Association. Gerrard AM, 2000. Guide to Capital Cost Estimation. 4th Edition. IChemE. Heldman DR, 2004. Identifying Food Science and Technology Research Needs. Food Technology 58(12)32–34. Holland FA, Wilkinson JK, 1997. Process Economics. In RH Perry and DW Green, eds. “Perry’s Chemical Engineers’ Handbook” 7th Edition. McGraw-Hill. Lopez-Gomez A, Barbosa-Canovas GV, 2005. Food Plant Design. CRC Press. Maroulis ZB, Saravacos GD, 2003. Food Process Design. Marcel Dekker, New York. Peters SM, Timmerhaus KD, West RE, 2003. Plant Design and Economics for Chemical Engineers, 5th Edition. McGraw-Hill. Ramaswamy HS, Marcotte M, 2005. Food Processing: Fundamentals and Applications. CRC Press. Rao MA, Rizvi SSH, Datta AK, 2005. Engineering Properties of Foods, 3rd Edition. CRC Press. Saravacos GD, Kostaropoulos AE, 2002. Handbook of Food Processing Equipment. Kluwer Academic / Plenum. Saravacos GD, Maroulis ZB, 2001. Transport Properties of Foods. Marcel Dekker. Valentas KJ, Rotstein E, Singh RP, 1997. Handbook of Food Engineering Practice. CRC Press.

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2 Structure of the Food Industry

I. INTRODUCTION Food Processing is the largest industry in the United States of America (US) and in most of the developed world. It is very important in developing countries, and it has a large potential in underdeveloped areas of the world. Food Processing is a very stable industry with steady growth potential, since it addresses the basic and continuing need of humans for food and nutrition. Detailed statistical data are available on food industry in US Government publications. Some information is available on the food industries of European Union (EU), but similar data and information on other countries are very limited. The development of Food Processing in the various countries follows more or less the pattern of the US food industry, and it is believed that an economic analysis of food processing plants, based mainly on available US and EU data and experience, will be very useful world-wide. Globalization and world trade of the economy have changed markedly the food industry during the recent years. The rise of the per capita income and the fast population growth of the urban areas of the underdeveloped countries have created the need for large amounts of nutritious processed foods at affordable cost. At the same time, health and food safety concerns of the consumers require that the food industry conforms with the increasingly strict national and international food standards and regulations.

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II. FOOD SYSTEMS 1. The US Food System The food delivery system consists of production of raw food materials (agricultural and marine), food processing, food trade, food distribution, and food service. Statistical data and evaluation of the US food system are given by Connor and Schiek (1997), Putman and Ambrose (1998), and the Council of Economic Advisers (2004). The value added in the US food system was 495 G$ (billion US dollars) per year (1992). The value added is defined as the total output (sales) minus the external purchases of goods and services. This value amounted to 8.2% of the US Gross Domestic Product (GDP) in 1992. Economic trends in the US show that the food system was surpassed recently by the health-related (medical, pharmaceutical) expenses, which grow at a faster rate. A broader estimation of the US Food System, including industries providing to agriculture, food processing, distribution and food service (machinery, chemicals, energy, business services, motor vehicles, refrigeration equipment, construction services) sums up to 668 G$, which corresponds to 12% of the US GDP (1992). Food processing represents about 25% of the total food system value, while agriculture is gradually decreasing to about 15%. Food distribution and food service are increasing their share to about 30% and 20%, respectively. US farms sold about 30% of their production to other countries in 1992, most of which was processed in the importing countries. The US imported 30 G$ of raw and semi-processed foods and 6 G$ of seafood in the same year. Employment in the US Food System (1995) was 18.5 M (million), out of which 17% was for agriculture and 10% for food processing. Recent trends show that employment is nearly stable in food processing, it is decreasing gradually in agriculture and it is increasing in the food distribution and food service systems. Americans spend less percentage of their personal expenditures for food than any other country, 10.7% (1994), down from 13.8% (1970). Expenditures in some other countries (1994) were, Canada 10.5%, U.K. 11.2%, various undeveloped countries 50%. The inexpensive food in America is the result of a large and efficient agricultural production, and efficient food processing and food distribution systems, supported by technical information from Universities, and state and federal agencies. Approximate economic values of the US food system for the current year can be obtained from the 1992 data by assuming an average increase of consumer price index of 4% per year. Thus, the total food sales for 2005 would be about 495x (1+ 0.04x15) = 792 G$.

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2. The US Food Processing Industry The Food Processing Industry, the largest US manufacturing industry, had shipments (sales) of processed foods of 495 G$ in 1992, about 10% of the total shipments of all the US industry. The majority of the 20,000 US food processing plants are rather small with less than 20 employees. The value of food shipments (sales) was 495 G$ out of total manufacturing sales of 3000 G$ (1992). Food processing heads the list of manufacturing, followed by chemicals/pharmaceuticals, industrial machinery, electrical/electronic equipment, etc. Manufacturing amounted to 18% of the US GDP (1992). Meat products accounted for the 22% of total food shipments in the US (1992), followed by beverages (15%), dairy products (12%), fruits and vegetables (12%), grain mill products (11%), bakery products (9%), sugar and confections (4%), and miscellaneous foods (10%). Some important economic data on the U.S. economy for 2003 are: GDP 10 400 G$, value added in manufacturing 1450 G$, agriculture 142 G$. Nondurable goods exports 218 G$, imports 480 G$. Profits of nondurable goods 78 G$ (foods 32 G$, chemicals 24 G$, petroleum products 20 G$). Food processing is a labor-extensive industry with an average annual cost of 250 k$/employee, i.e. high output per employee. It is a capital-intensive industry with high physical assets per employee. It is also a materials-intensive industry, handling large quantities of raw materials and processed products. Smaller food plants are located primarily in rural areas, near agricultural production, while the headquarters and the management of the large plants concentrate in urban areas. The food processing industry purchases the services of other companies, such as engineering design, plant equipment, and food plant cleaning. Although employment is not increasing, the growth in food processing industry is achieved by increases in labor productivity. The productivity of the US food processing industry has increased by the replacement of batch production by continuous-flow equipment, particularly in brewing, baking, confectionary, and large food ingredient/intermediate industries. The number of food processing plants in the US is about 20,000, out of which about 120 are large plants with more than 1000 employees. About 50% of the plants are quite small with less than 20 employees. Large companies have central administrative headquarters and they own several operating plants in various locations. There are about 16,000 food companies with an average 1.4 plants per company. Capital expenditures in Food Processing are about 2–4% of the sales/year. It is very low in meat packing (0.8%) and high in pasta manufacturing (6.9%). High rates of capital cost characterize food industries of rapid tech-

© 2008 by Taylor & Francis Group, LLC

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nological change, introducing new products, and requiring new equipment, e.g., flour mixes, cookies, canned and dried fruits. The output of the US food processing industry is the largest in the world, followed by Japan (55% of US) and Germany (33% of US). The total food production in the European Union (EU) is slightly higher than the US (Connor and Schiek, 1997). The average prices for processed foods in the US are about 30% lower than in Western Europe and Japan. Shipments (% of world sales) of processed foods in some developed countries (1995): EU 44%, USA 35%, Japan 9.8%, Germany 9.1%, France 8.4%, UK 8.1%, Spain 5%, and Italy 4.8%. Sales of processed foods in developing large countries are increasing gradually, following the growth of their national economy, e.g., China, Brazil, and India. There is more foreign (mostly European) investment in US food industries than investment of US food industries abroad. a. Industry Classification The food processing industries in the U.S. were classified in 1987 according to the Standard Industrial Classification (SIC) system. The food and kindred products were classified in the SIC 20 series using 4-digit codes (US Census Bureau, 1992; Connor and Schiek, 1997). The Food and Kindred Products group includes establishments of processing or manufacturing foods and beverages for human consumption, and certain related products, such as manufacture of ice, vegetable and animal fats and oils, and prepared animal feeds. The SIC system lists 49 Food Processing Industries coded from 2011 (Meat Packing Plants) to 2099 (Misc. Food Preparations). Recently (1997), the North American Industrial Classification System (NAICS) was adopted in the U.S., Canada, and Mexico. The food processing industries are classified in the NAICS 311 series using 6-digit codes (US Census Bureau, 2002). Table 2.1 lists 9 main groups of Food Processing Industries (Manufactures), according to the SIC and the NAICS systems. Table 2.3 lists in detail both the SIC and NAICS codes of specific processed foods.

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Table 2.1. Main Groups of Food Industries, SIC and NAICS Codes Food Product Animal (meat, poultry, egg) products Dairy (milk, cheese) products Canned and preserved fruits and vegetables Grain mill (flour) products Bakery (bread, biscuits) products Sugar and confectionery (candy, chocolate) products Animal and vegetable fats and oils Beverages (beer, wine, soft drinks) Miscellaneous foods (seafood, pasta, coffee)

SIC code 201 202 203 204 205 206 207 208 209

NAICS code 3116 3115 3114 3112 3118 3113 3112 3112 3119

b. Food Consumption Details on food consumption in the US were presented by Putman and Allahouse (1998.). The US spent 710 G$ for food in 1997, corresponding to 10.7% of the GDP. The annual consumption per capita of some important foods in the US (1997–1998) is as follows: • Animal Products: beef 39 kg, chicken 20 kg, pork 20 kg. eggs 250 pieces (20% processed), dairy total 250 kg, fluid milk 100 L (50% whole and 50% low- and nonfat), cheese 12.5 kg, ice cream 8 kg, yogurt 3 kg. • Fruits and vegetables 325 kg, sugar (sucrose) 32 kg, corn sweeteners 36 kg, fats and oils 28 kg, candy 10 kg, flour 100 kg (65% wheat flour). • Carbonated beverages 200 L, coffee 90 L, beer 80 L, fruit juices/drinks 65 L, wine 8 L, distilled spirits 5 L. During the last 20 years the consumption of the following foods increased substantially: fruits and vegetables, grain products, poultry and fish, cheese, fats and oils, beer, and carbonated beverages. There was a decrease in the consumption of eggs, fluid (whole) milk, and coffee.

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Table 2.2. Classification of Food Processing Industries, SIC and NAICS Systems Food Product Meat products Sausages, prepared meats Meat byproducts, lard Poultry and egg products Creamery butter Cheese products Dry, evaporated, condensed dairy products Ice cream and frozen desserts Fluid milk, cream, yogurt UHT fluid milk Canned specialties Canned fruits and vegetables Dried fruits and vegetables Pickled fruits and vegetables, sauces Frozen fruits, fruit juices, and vegetables Frozen specialties Flour, other grain milling products Cereal breakfast foods Rice milling Flour mixes and doughs Wet corn milling Refined oils Dog and cat food Prepared animal feeds Bakery products Cookies and crackers Frozen bakery products Cane sugar Beet sugar Confectionery products Confectionery from cocoa beans Confectionery from chocolate Chewing gum Nonchocolate confectionery Roasted nuts and seeds Cottonseed oil Soybean oil Vegetable oils Animal and marine oils Shortening and margarine Malt beverages Wine and brandy Soft drinks Coffee and tea flavorings Flavoring extracts and syrups Seafood canning Fresh and frozen seafoods Coffee and tea products Potato chips and similar snacks Manufactured ice Dry pasta products Miscellaneous food products

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SIC Code 2011 2013 2015 2021 2022 2023 2024 2026 2032 2033 2034 2035 2037 2038 2041 2043 2044 2045 2046 2046 2047 2048 3051 3052 2053 2062 2063 2064 2066

NAICS Code 311611 311613 311615 311512 311513 311514 31152 311511 311514 311422 311421 311423 311941 311411 311412 311211 31123 311212 311822 311221 311225 311111 311812 311821 311813 311312 311313 311313 31133

2067 2068 2074 2075 2076 2077 2079 2082 2084 2086 2087 2087 2091 2092 2095 2096 2097 2098 2099

31134 311911 311223 311222 311223 311613 311225 311213 311213 31192 31193 311711 311712 31192 311919 311113 311823 311999

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c. Value Added in Food Processing The value added depends on the food product, technology used, and the cost of raw materials. High priced farm raw materials yield low value-added products, e.g., meat, dairy products, and seed oils. Also, semi-processed food ingredients yield low value-added products, e.g., tomato paste, juice concentrate, condensed and dried milk. Industries based on fresh fruits and vegetables, grains, and convenience foods yield higher value-added products. Value added of typical food products, in diminishing order are, food flavorings, cereals, cookies, bread, pasta, beer, confectionary, canned specialties, dried fruits and vegetables, frozen specialties, coffee, meat packing, soybean oil. Most of the beverage industries and food industries that use flow-type processes rank high in value-added products, e.g., oils, sugars, sauces, flour, and rice milling. Labor-intensive food processing industries rank low in valueadded production, e.g., cookies, bread, dried fruits and vegetables, frozen foods. d. Raw Materials Raw and other materials of the food processing industries, purchased from other sectors, such as agricultural products, livestock, crops, semi-finished foodstuffs, containers, and chemicals, represent about 60% of the total cost, with a wide variation in the various industries. The requirements of raw materials used in food processing are unique, due to the biological nature of agricultural and marine products. There is a seasonal variation of supply of some food raw materials, due to farm production, e.g., fruits and vegetables, corn, beets, and oil seeds. Some farm raw materials are spoilage-sensitive, e.g., fruits, vegetables. Storage-stable raw materials include grains (wheat) and oil seeds. Some farm products are subsidized by the Government in order to increase the farm income: Typical examples of subsidies are corn, cattle and pork in the US, and milk, fruits (oranges), and vegetables in the European Union. Demand-oriented industries (fluid milk, beer) tend to locate near cities, while supply-oriented industries (canned fruits and vegetables) locate near agricultural production. Coastal areas near cities are convenient for food processing industries, using imported raw materials, such as tropical fruits and vegetables, grains and seafood. e. Labor and Energy Food Processing is a labor intensive industry, representing about 15% of the food sales. The food industry assets are in the range of 100–1500 k$/employee

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(k$ = thousand US dollars). A large substitution of capital for labor is observed in technologically advanced industries, e.g., grain products, sugar, vegetable oils, coffee and beverages. Energy requirements in the food processing industries are relatively low, on the average 1.3% of sales. However, higher energy requirements are observed in some food industries, e.g., 6% in corn milling, cane sugar, beet sugar, 4.5% in cottonseed oil, and 2.6% in freezing and drying of fruits and vegetables. 3. Food Trade Industries Establishments engaged in packing and selling, but not manufacturing, food products are classified as Trade or Wholesale Trade Industries. The following examples are considered food trade (not processing) industries in the US: a. Bottled natural spring water – not carbonated water b. Cutting and resale of purchased fresh carcasses c. Bakeries selling directly products on the premises to household consumers d. Grading and marketing of farm dried fruit, such as prunes and raisins e. Bottling purchased malt beverages. Bottling, but not manufacturing, purchased wines, brandy, and various liquor. 4. The European Food Processing Industry The food processing industry is one of the largest industrial sectors of all European states. The principal food industries in Europe are the dairy, meat processing, edible oil, fruit and vegetable, grain milling, bakery, sugar, confectionery, fish, and coffee. Most European states support the large dairy and meat industries, which bring considerable income and economic development to the rural areas. An economic analysis of the European food processing industry in the period 1975–1980 was reported by Kostaropoulos (1983). The initial EEC was changed to the EU10 (European Union of 10 countries), which later expanded to 15 countries (EU15). The total sales of the European food industry in 2003 (EU15) was 950 G$. Table 2.3 shows the food industry sales in some European countries. Table 2.3 Food Industry Sales in EU15 Countries (2003) Country Food sales, (G$) France Germany UK Italy Spain Sweden Greece

165 155 134 125 75 18 12

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The European Union has recently expanded to Eastern Europe and the Balkans to include 27 countries (EU27). Recent data on the European food industry can be found in Publications of the Statistical Society (Eurostat: http://ec.europa.eu/eurostat). The location of the food industries depends strongly on the availability of raw materials. Thus, fruit and vegetable processing plants are located preferably in southern regions of Europe, due to favorable weather conditions for growing raw materials. Beet sugar plants requiring large quantities of raw materials, can operate in northern regions. Edible oil plants, requiring large amounts of imported oil seeds, are located near harbor facilities. Dairy plants, requiring large amounts of fresh milk, operate near dairy farms, and preferably close to large urban areas, where consumers live. Fish processing plants are located near sea ports, where fishing vessels bring in the fish catch. In addition to agricultural and marine raw materials, the food processing industry is depended to some other industries and services, such as food processing equipment, food packaging, and storage and transportation facilities. Food preservation plants are usually small to medium size and they use established processing technology and equipment. The required labor includes unskilled workers from the farm areas near the plant. The investment of fruit and vegetable canning or freezing plants is about 10 M$ per plant. Sugar and edible oil plants are more capital intensive. They have larger capacities than the preservation plants and they use advanced technology and automation, requiring investments near 50 M$ (M$ = million US dollars). The European food industries are classified according to the NACE system (Table 2.4). Table 2.4 Classification of the European Food Processing Industries (NACE) NACE 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427

Food Processing Industry Processing of vegetable and animal oil and fat Slaughtering, preparing, and preserving of meat Manufacture of dairy products Processing and preservation of fruits and vegetables Processing and preserving of fish Grain milling Manufacture of pasta, spaghetti, etc. Manufacture of starch and starch products Manufacture of bread and flour pastry Sugar manufacturing and refining Manufacture of cocoa and confectionery Manufacture of animal and poultry foods Manufacture of other food products Manufacture of ethanol from fermented liquors Manufacture of wine from grapes and related beverages Brewing and malting Manufacture of soft drinks, including bottled water

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A brief overview of the European food processing industries is presented here: a. Dairy Industry The dairy industry is the top food industry in Germany, France, United Kingdom, the Netherlands, and Italy. Good prospects for growth have the fluid milk, yogurt, and cheese, while condensed milk and milk powder are rather declining. Most of the fluid milk is pasteurized, while a growing percentage is sterilized by the high temperature-short time (UHT) process. The production of yogurt (fermented milk product) is growing. A large portion of the milk powder produced in Europe is used for animal feed. Cheese is produced mainly in France, the Netherlands, and Italy, usually in multi-purpose dairy plants. b. Sugar Europe is one of the largest beet sugar producers in the world with an annual output of about 15 Mt/y (1980). Beet sugar is produced mainly in Germany and France in large plants of about 65 kt/y annual capacity. Due to seasonal availability of the beets, the sugar plants operate at maximum capacity for about 2–3 months a year. The sugar by-products are used as an animal feed. (Mt = million tons; kt = thousand tons) c. Edible Oils The raw materials for the edible plant oil industry in Europe, i.e. soybeans and rapeseeds, are imported from the US or South America. The vegetable oils are extracted from the crushed beans by a solvent. The bean residue after the solvent extraction is sold as an animal feed, representing a significant income. d. Fruits and Vegetables The processing plant should be located near the agricultural production of the sensitive raw materials, which should be harvested, transported, and processed fast. The seasonal availability of the raw materials requires high capacity processing plants. Fruit and vegetable canning plants are located in France, Germany, United Kingdom, Italy, and Greece. Freezing plants operate in the Netherlands, while dehydration is practiced in France, Ireland, and Germany. Potato processing is concentrated in the Netherlands, Germany, and the United Kingdom.

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e. Grain Milling Grain milling, mainly production of wheat flour, is a large food processing industry in France, Germany, United Kingdom, and Italy. It is characterized by a small number of large units, located near grain-producing areas or in harbors. Grain milling is a capital intensive industry, using modern technology. It supplies with various flour products the baking, biscuit, and pasta industries. f. Baking Industry The baking industry consists of several small bakeries, producing various bread types, and a few large baking plants, producing standardized bread loaves and pastry. Biscuits are produced by large bakeries, mainly in the United Kingdom, France, Italy, and Germany. Pasta (spaghetti, macaroni, etc.) production is a capital intensive industry, developed mainly in Italy. g. Confectionery The confectionery industry is particularly important in the United Kingdom, Germany, France, and the Netherlands. It is based mainly on imported cocoa beans, and it uses large amounts of sugars. The principal confectionery products are cocoa, chocolate, and candy products. Ice cream is considered as a confectionery product in some countries, while in other countries it is classified as a dairy product. h. Meat Industry The meat industry is a large food industry in Germany, France, and Italy. Most of the beef and poultry are consumed as fresh (refrigerated), and only a small portion is processed. On the contrary, pork (pig meat) is processed to various products, mostly sausages and ham. i. Fish Industry Denmark is the largest producer of processed fish in Europe. Fish processing is also important in the United Kingdom, Germany, France, and Italy. Canned tuna fish and frozen fish are the most important processed fish products. k. Coffee Industry The coffee industry is an important processing industry in Germany and the Netherlands, followed by France, United Kingdom and Italy. It produces ground roasted coffee and soluble coffee from coffee beans imported from

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South America and Africa. There are only a few large coffee processing companies, located near seaports (import of raw material) and large urban areas. 5. Multinational Food Companies A number of multinational food companies, with headquarters mainly in Europe and the US, operate several food processing plants in different parts of the world. Foreign industrial investment improves the economy of less developed countries and increases international trade. Some food products can be processed and manufactured more economically in countries with abundant raw materials and less expensive labor. Several small food companies are acquired by international food companies, resulting in more efficient plants, better marketing, and improved food quality. The major multinational companies are listed in Table 2.5. The headquarters of the multinational companies are located mainly in the USA, United Kingdom (UK), Switzerland (CH), the Netherlands (NL), and France (F). Several US food companies operate food processing plants in foreign countries. The following companies have more than 30% of their plants abroad: CPC International, Heinz, Ralston Purina, Quaker Oats, Kraft, Philip Morris, Kellogg’s, McCormick, Campbell Soup, Procter and Gamble, and Sara Lee. Table 2.5 Multinational Food Companies Multinational company Major food products Nestle (CH) Coffee, dairy foods Unilever (NL, UK) Edible oils, frozen foods Danone (F) Dairy foods Philip Morris/Kraft (USA) Coffee, cheese Coca Cola (USA) Soft drinks Pepsico (USA) Soft drinks, snack foods Best Foods (USA) Soups Mars (USA) Confectionery Cadbury Schweppes (UK) Confectionery Heinz (USA, UK) Canned Foods RHM (UK) Baked foods Cargill (USA) Edible oils Campbell (USA) Soups

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6. Food Distribution Systems The Food Distribution Systems specialize in the transportation, storage, display and sale of food products (Connor and Schiek, 1997). The Logistics system of food distribution is discussed in Chapter 3 of this book. Processed foods in the US are distributed to food stores (52%), food service and institutional sales (20%), semi-processed foodstuffs and byproducts (22%), and exports (6%). Food imports are also about 6% of the total processed foods. Food stores include food supermarkets, large consumer centers, and super centers. Food service includes catering, hotels, restaurants, fast food outlets, and Government and international aid. Supermarkets selling brand names dominate the sales of processed foods in the US, while private labels represent about 15% of the food sales. By contrast, private label sales of processed foods are much higher in the EU, e.g., 40– 50% in the UK, with higher profits than the US food outlets. Efficient distribution of processed foods in supermarkets or large consumer outlets (e.g., Wal-Mart) lowers food prices. The demand of a particular food product is expressed by the Stock Keeping Units (SKU), which may account up to 20,000 in a typical supermarket. To meet the SKU demands of various customers, many food plants employ Flexible Manufacturing Systems (FMS), which can switch from one product to another, using the same processing or packaging equipment. International companies and supermarkets may dump various foods, i.e. sell products at very low prices, with local companies unable to compete in the market. Anti-dumping measures are taken by various countries to protect their industries at the national and international levels. REFERENCES Connor JM, Schiek WA, 1997. Food Processing. An Industrial Powerhouse in Transition, 2nd Edition. John Wiley & Sons. Council of Economic Advisers, 2004. Economic Report of the President. Government Printing Office, Washington, D.C. Kostaropoulos AE, 1983. Concentration, Competition and Competitiveness in the Food Industry of the EEC. Commission of the European Communities IV/584/83-EN, Brussels, Belgium. Putman JJ, Allhouse JA, 1998. Food Consumption, Prices, and Expenditures, 1970– 1997. Food and Rural Economics Division, Economic Research Service, US Dept. of Agriculture, Statistical Bulletin No. 965. US Census Bureau, 1992. Census of the Manufactures: Industry Report Series. US Census Bureau, 2002. North American Industry Classification System (NAICS). Washington, DC. http//www.census.gov/epcd/www/naics.htlm

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3 Overview of Food Process and Plant Design

I. INTRODUCTION The design of food processes, processing equipment, and processing plants has evolved from an empirical art and industrial practice into an applied engineering and economics area, based on the principles and practices of modern Chemical Engineering. Chemical process and plant design have contributed greatly to the development of efficient chemical and petrochemical plants, producing large quantities of industrial (commodity) and consumer products at relatively low cost. The conventional design of chemical processes, equipment, and plants is described in standard books, such as Seider et al. (1999), Turton et al. (1998), Biegler et al. (1997), Perry and Green (1997), Sinnott (1996), Smith (1995), Peters et al. (2003), Douglas (1988), and Walas (1987). The design and operation of the chemical process industries has been improved by the application of modern molecular thermodynamics, mathematical modeling and simulation, and computer technology. These industries process mainly gases and liquids, for which sufficient data and predictive models of their physical and engineering properties are available in the literature (Biegler et al., 1997). Most large chemical process industries are operated continuously, which makes them easier to model, simulate, and control. Limited literature and fewer data are available for food process and plant design. Food products are more sensitive to processing and storage than chemicals, and there are strict requirements on food safety and quality, which should be considered in addition to conventional engineering and economics. The application of Chemical Engineering analysis to Food Process Design has been successful in the classical unit operations of heat and mass trans27

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fer (heating/cooling, evaporation, drying, extraction), and in the kinetics of biochemical and microbiological reactions (Fryer et al., 1997; Maroulis and Saravacos, 2003). However, widely used mechanical processing operations of Food Manufacturing, such as size reduction, mechanical separations, mixing and forming, and packaging are still designed empirically, based on industrial experience and technical information from suppliers of equipment (Saravacos and Kostaropoulos, 2002; Walas, 1988; Perry and Green, 1997). Recent research and publications on engineering properties of foods (Rahman, 1995; Rao et al., 2005) and food transport properties (Saravacos and Maroulis, 2001) have improved significantly the quantitative design of food processes and processing equipment. Food Plant Design involves the estimation of capital (investment) and operating costs. The capital cost is based on the estimation of the equipment cost, while the operating cost includes the costs of raw materials, labor, utilities operation, and various overhead expenses. Design and overall cost data of several food processing plants were published by Bartholomai (1987). In addition to conventional Process Engineering, the food plants must comply with the special requirements of hygienic (sanitary) design of equipment and plant facilities, and the safety and quality of the processed food products (Clark, 1997; Clark, 2000; Lelieveld et al., 2003). More attention is paid recently to Food Product Engineering, i.e. the design and engineering of food structure and quality of processed foods. A similar trend is observed in chemical product design (Cussler, 2001). The microstructure of complex fluid and solid food products, such as colloids, emulsions, porous and extruded products, plays an important role in determining their quality and acceptability (Aguilera and Stanley, 1999). The transport properties of foods, especially the mass diffusivity and the thermal conductivity, are affected strongly by the micro-structure (1 – 10 μm) and the macro-structure (0.1 – 10 mm) of the foods (Saravacos and Maroulis, 2001). Food Process Economics is applied to estimate the profitability of food processing operations. The methods used in Process Engineering Economics (Couper, 2003) can be applied to the economic analysis of food processes and processing plants. II. FOOD PROCESS DESIGN Process Design, based on unit operations, transport properties, and chemical kinetics has been developed and applied to the Chemical Process Industries. In addition to the techniques of Chemical Engineering, Food Process Design is based on the principles and practices of Food Science and Technology. Food Process Design includes the selection of the process flowsheet, the material and energy balances, and the sizing and costing of the process equipment (Maroulis and Saravacos, 2003). The design of food processes is based on © 2008 by Taylor & Francis Group, LLC

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the same principles of Chemical Process Design, considering also the requirements for food quality, hygienic operation, and food safety. The unit operations of Food Processing include the basic heat and mass transfer operations, several mechanical processing operations, and specialized food processing operations, such as thermal processing, refrigeration, freezing, and packaging (Saravacos and Kostaropoulos, 2002; Gould, 1996). Computer spreadsheets are useful in Food Process Design (Zaror and Pyle, 1997). 1. Process Flowsheets The simplest flowsheet in Food Processing is the process block diagram (PBD), which shows the flow of materials in distinct blocks. The PBD is conventionally used in preparing the material and energy balances of the process. Figure 3.1 shows a simplified PBD of an orange juice concentrate process. The process flow diagram (PFD) or the flowsheet (Figure 3.2) presents the flow of the raw materials and products in more detail, using accepted symbols for the various types of equipment. The layout or floor plan of the process equipment (Figure 3.3) is used in estimating the floor requirements of the food processing plant. Three-dimensional (3D) flowsheets are useful for a better visualization of the food plant (Saravacos and Kostaropoulos, 2002). Piping and instrumentation diagrams (PID) are used in complex plants to represent piping, process instrumentation, and process control. 2. Material and Energy Balances Material and energy balances provide necessary quantitative data for the design of food processes and processing plants. They are based on the material flow rates and the composition of the raw materials, the intermediate, and the final food products. The percent total solids (%TS), or moisture content, wet basis (%Water = 100 - %TS) are the most commonly used composition data. In some applications, other special components may be used in material balances, such as % sugar, % fat, % protein, or % salt. In sugar solutions or fruit juices, the sugar content is expressed as oBrix, which is defined as the % content of TS, wet basis, expressed as sucrose. In clear sugar solutions and in clarified fruit juices, the nonsugar content is negligible and the oBrix is approximately identical with the % TS (Saravacos and Kostaropoulos, 2002). Material balances should be based on mass flow rates, e.g., kg/h or ton/h. Volumetric flow rates, (L/h or m3/h) are converted to mass flow rates, using the appropriate mass density of the material (kg/L or ton/m3). It should be noted that International Units (SI) are used throughout this book and the ton is 1000 kg. In the U.S. the “short” ton is sometimes used, which is equal to 2000 lb or 908 kg.

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Chapter 3 Oranges

Washing

Oranges 13.6% TS Inspecting/sorting

Rejects

Oranges 13.6% TS

Peel oil

100 kg

Juice extraction

Peels 14.5% TS

0.30

Oil extraction

48.0 Pulpy juice 13% TS

Peels 14% TS

52.0

Finishing

Pulp 36.0% TS

47.7

Mixing

2.00 Orange juice 12% TS

50.0

Pasteurizing

Pulp 14.9% TS

49.7

Drying

Orange juice 12% TS

50.0

Annimal feed 90% TS

8.20

Evaporation

Concentrated juice 65 % TS

9.23

Cooling

Concentrated juice 65 % TS

9.23

Asepting packing

Storage

Figure 3.1 Process block diagram and material balance of orange juice concentrate plant. Basis, 100 kg of oranges.

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Oranges Sorting Inspecting

Rejects

Extraction Peel oil

Drying Peels

Finishing

Pressing Pulp

Animal feed

A F

Orange juice

S

W

Evaporation

Pasteurizing

S

s

s

Concentrated

C K

orange juice

Cooling Aseptic packaging

c

Figure 3.2 Process flow diagram of orange juice concentrate plant. A, air; C, cooling water; F, fuel; K, packaging material; S, steam; W, condenser water.

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Storage of oranges

Juice Washing

Sorting

Extraction

Oil Drying

Extraction

Finishing

Evaporation

Pasteurizing

Cooling

Aseptic packaging

Storage

Figure 3.3 Equipment layout of orange juice concentrate plant. Most food processes involve continuous flow operations, and the inlet must be equal to the outlet mass, i.e. the mass accumulation is zero. In batch processing operations, the accumulation (inlet minus outlet) in the process or the equipment is an important term of the material balance equations. Energy balances in Food Processing refer mainly to heat (enthalpy) balances around processing equipment and entire processes. Mechanical energy flow, expressed in kW, refers to motors used in various processing equipment and plant utilities. Of particular importance are heat balances in processes, which use large amounts of energy, such as evaporation and drying (removal of water form foods). Material and heat flows in the whole processing plant are sometimes presented graphically in a Sankey diagram.

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Heat balances require thermal property data for foods, water, and air (Rahman, 1995; Rao et al., 2005; Saravacos and Kostaropoulos, 2002). Very useful thermal data for water are specific heat Cp = 4.18 kJ/kg K, heat of vaporization (pressure 1 bar) ΔΗv = 2.26 MJ/kg, and heat of freezing ΔΗf = 333 kJ/kg. The energy requirements are often expressed as MJ/kg or kWh/kg product (1kWh=3.6MJ). In energy balances calculations, the SI units are convenient, and the other technical units (e.g., Btu/lb or kcal//kg) should be converted to MJ/kg or kWh/kg, when starting the calculations. 3. Sizing and Costing of Equipment The size of the food processing equipment can be estimated, using the flow diagram and the material and energy balances of the process. The techniques of the Chemical Engineering Unit Operations can be used effectively, especially in the design of conventional heat and mass transfer operations, such as heat exchangers, evaporators, dryers, distillation columns, and solvent extractors. Some novel food process operations, such as membrane separations (ultrafiltration and reverse osmosis), can be designed applying the same techniques (Maroulis and Saravacos, 2003). Mechanical processing equipment, such as grinders, agglomerators, extruders, mixing and forming equipment, and food packaging equipment are designed and selected empirically, based on the experience of equipment suppliers and food manufacturers (Saravacos and Kostaropoulos, 2002). Mechanical equipment is selected on the basis of product capacity, usually kg/h, and the power requirement, mainly for the electrical motor (kW). The requirements for other utilities should also be specified, e.g., steam and water (kg/h), and compressed air (m3/h). The materials of construction and the hygienic design of the food processing equipment are very important and should be specified (see section on Plant Design in this chapter). The design of special food processing equipment, such as thermal sterilizers, refrigeration and freezing equipment, and packaging equipment is based on engineering principles and the experience of equipment manufacturers and food processing operators. Similar procedures (engineering and practical experience) are used in the design and operation of treatment and disposal of food wastes (water, gaseous, and solid wastes). The cost of food processing equipment can be determined directly by price quotations from equipment suppliers. For preliminary design, cost data for Chemical Engineering equipment can be used in food process design, especially for conventional fluid flow, and heat and mass transfer equipment (Peters et al., 2005; Couper, 2003). The Marshall and Swift (M&S) index is used to convert the cost from previous years.

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Limited cost data have been published on food processes and processing equipment. Some data on selected food processing equipment were presented by Saravacos and Kostaropoulos (2002). Costs of entire food plants were presented by Bartholomai (1987). III. FOOD PLANT DESIGN The design of food processing plants is based mainly on the design of food processes and processing equipment. In addition, several components of the food plant should be analyzed quantitatively, such as plant buildings, raw materials, food products and by-products, plant utilities, packaging materials and equipment, labor, quality control, storage (warehousing), and waste treatment (Lopez-Gomez and Barboza-Canovas, 2005). Food Plant Economics is very important and it is outlined in the next section of this chapter. Food plants, in addition to economic efficiency (profitability), should conform to strict requirements of food product safety, legal, and environmental regulations. Laws and regulations (State and Federal) should be considered at the design stage, such USDA (inspection of meat and poultry), FDA (Code of Federal Regulations), and EPA (environmental) in the United States. Stricter standards than the official regulations may be applied by some food companies to ensure their product safety to the consumers. Increased international trade of food products makes it necessary to consider the food laws of other countries or federations, e.g., of the European Union (Saravacos and Kostaropoulos, 2002). In Food Plant Design, the following special requirements should be considered: (a) The raw materials are usually seasonal and sensitive agricultural products which require special harvesting, transportation and storage before processing; (b) materials handling equipment and processing should not damage mechanically or cause microbial, enzymatic, or chemical spoilage of the product; (c) special packaging materials and equipment may be required for each food product; (d) hygienic (sanitary) design and cleaning of the process equipment and the processing plant are necessary (Clark, 1997). Most food plant design and construction is concerned with improvements of existing installations rather than building new (grassroots) plants. Such modifications or revamps and expansions are necessary for meeting the new requirements of ecology, waste reduction, energy availability, specialized labor, nutrition and food safety, international trade, increasing population, and economic profitability.

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1. Plant Buildings The design of food plants is an architectural and civil engineering task which, in addition to structural engineering, should consider strict food safety and quality requirements and regulations of foods being handled and processed. The food plant should provide adequate space for equipment installation and storage of materials, prevent cross-contamination of the products, provide adequate lighting and ventilation, and protect the products from outside contamination and pests (Clark, 2000; Lopez-Gomez and Barbosa-Canovas, 2005). a. Plant Location The location of the food plant is decided by considering the availability of raw materials and labor, the access to plant utilities (water, power) and waste treatment/disposal, the transportation systems, the regulation requirements, and the food consumption outlets. In evaluating a food plant location, the following aspects should be considered (Downing, 1996): 1. Quantity, quality, and cost of raw materials. 2. Sales and delivery cost to markets. 3. Transportation and distribution by highways, railroad, waterways, or airways. Storage and terminal facilities. 4. Adequate labor, labor skills, supervisory personnel. 5. Availability, quality, and cost of water. Waste and sewage disposal. 6. Availability and cost of power. 7. Laws related to workers, waste disposal. 8. Taxes and banking system. 9. Climate (rainfall, snowfall, storms). 10. Living conditions, housing, schools, hospitals. 11. Site characteristics (soil, elevation, drainage, flooding). A medium size food processing plant would require a lot area of about 10,000 m2. Fruit and vegetable processing plants should be located near the agricultural farms, so that truck transportation will be fast enough to prevent any spoilage of the sensitive raw materials. Medium size processing plants of about 100 tons/day raw materials are usually built and operated for such materials. Much larger plants of the order of 1000 tons/day are operated for some high-volume food ingredients, such as beet sugar and soybean oil. b. Building Construction The construction of plant buildings should take into consideration the special hygienic and legal requirements of food processing plants. Based on the block flow and the equipment layout diagrams of the food process, a block building diagram can be prepared, which will define the floor (space) requirements of the food plant. Building space is important in designing the efficient flow of raw materials, products, and personnel in the plant. One-story buildings (large floor space) are preferred in general for better equipment layout, product flow, process inspection and control, cleaning, and maintenance. The plant buildings, especially the internal walls and floors, should conform to the hygienic require-

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ments and regulations. The building construction should prevent and eliminate the entrance of animal pests, such as insects, rodents, and birds, and prevent any accidental or intended contamination of the processed and stored foods. Plant floors should preferably be at ground level to permit direct unloading and loading of the raw materials and the finished products. The earth resistance of the floors should be adequate (reinforced, if necessary) to withstand high loads and lift trucks. The plant site should have a soil-bearing capacity of at least 14 tons/m2. Modular construction is preferred in the construction of new food processing plants, so that future expansion of the plant can be realized easily. Concrete floors should be about 12–15 cm thick, coated with silicate fillers, to resist the acidity of food wastes. Floor drains, 12–15 cm deep and 15– 39 cm wide with grated covers, are normally used. Free drainage of plant floors requires a slope of about 1–2%. Floor finishing materials, such as ceramic tiles and epoxy resins, should withstand CIP cleaning solutions, including acids, and be no-slippery. Building walls of the plant processing section should be lined with tiles or epoxy resins, which are resistant to food spillage and cleaning solutions. In addition to the main processing and warehousing buildings, special spaces are needed for the cold storage, the steam boiler, the machine shop, the other plant utilities, the waste treatment/disposal facilities, the offices, the quality control and research laboratories, and the employee facilities. Industrial lighting, properly designed, is required for the efficient operation of the food processing plants. Recommended light intensities (candela/ft2 or lumen/m2) for various food plant operations (e.g., product inspection) are provided by the Illuminating Engineering Society (Downing, 1996). Fluorescent lamps are preferred over incandescent lamps, because they are 2.5 times more efficient and they provide a softer light. 2. Food Plant Safety Food plant safety refers to the safe design and operation of food equipment and food plants, i.e. prevention of physical hazards and accidents that may cause physical damage to the food plant and/or health problems and injuries to the workers and employees. Plant safety programs should include management and employee involvement, work place analysis, hazard prevention and control, and safety and health training (Imholte, 1984). Equipment and plant regulations, issued by Government agencies, and practical rules and good manufacturing practices should be followed (Saravacos and Kostaropoulos, 2003). Two important hazardous operations (HAZOP) in food processing plants are fire and explosions, which require strict measures and practices for efficient prevention. Fire danger exists in ovens and furnaces, edible oil plants, grinding

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mills, and in storage of dry products. Fire detection and fire fighting equipment must be installed in all food plants. Explosions are a serious hazard in equipment and storage installations handling combustible food powders and dusts, e.g., pneumatic conveying and storage silos of flour, starch, or sugar. Prevention of explosions is based on controlling the solids concentration of air/particle mixtures and the elimination of local overheating and electrical sparks in product transport and storage installations. A potential explosion hazard is the plant steam boiler, parts of which may be overheated by the combustion gases, when no water is present. To avoid potential damage to the employees and the rest of the plant, steam boilers should be installed in separate rooms. Dust explosion is a serious hazard in equipment handling powdered food solids, e.g., dryers, grinders, silos, dust collectors, mixers, and pneumatic conveyors. Dust explosions occur when the solids concentration in air suspension is above the minimum and below the maximum critical concentrations for the particular material. Ignition sources are mechanical seals, friction heating, and electrostatic discharges (Zalosh et al., 2005). Dust explosions can be prevented by proper design of the process equipment (vents), dust concentration control, safe operating temperatures, and low oxygen (inert) atmosphere (Center for Chemical Process Safety, 2005; National Fire Protection Association, 2000). Food plants handling fire and explosion hazardous materials must conform to special regulations of Government agencies, such as the OSHA (Occupational Safety and Health Organization) of the US Department of Labor, and the National Fire Protection Association (NFPA) of the US. The fire protection system should provide for the safety of the employees, and protect the plant (building, equipment, raw-material, and products). Fire extinguishers, fire detectors, fire alarms and water sprinklers should be installed in appropriate locations. In the US, the testing of the fire protection equipment is conducted by the Underwriters Laboratories (Storm, 1997). Noise levels in industrial working places should not be excessive and damage the health of the personnel, e.g., operators of bottling lines. The noise level in European Union workplaces should not exceed 87dB in a period of 8h work. HAZOP (Hazardous Operations) studies should be made at the design stage, before the plant is constructed (Kletz, 1999). 3. Hygienic Design Hygienic (sanitary) design refers mainly to the prevention of microbiological hazards of food products during processing and storage. Proper equipment and plant design can eliminate the hazard (danger) of growth of spoilage and pathogenic microorganisms (mainly bacteria), which may have serious health effects on the consumers. Physical and chemical contamination of food products should also be avoided, because of the adverse effect on food quality and consumer acceptance.

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Hygienic and safety requirements for food products and environmental considerations are of primary importance during the design, construction, and operation of food plants (Gramer, 2006). Hygienic design refers to both food processing equipment and food plant. (Jowitt, 1980; Saravacos and Kostaropoulos, 2002). Regulations of hygienic design and operation of processing plants are issued and enforced by appropriate health authorities in various countries. A significant number of hygienic practices, known as Good Manufacturing Practices (GMP) are applied to food equipment and food plants (Gould, 1994). In the U.S., the hygienic (sanitary) aspects of food processing are the concern of the United States Department of Agriculture (USDA), the Food and Drug Administration (FDA), the Environmental Protection Agency (EPA), and some other authorities and organizations. Food plant hygiene (sanitation) in plant design, operation, and inspection is practiced by food sanitarians (Troller, 1993; Marriott, 1997) and hygienic engineers (Lelieveld et al., 2006). Cross contamination, i.e. contamination of processed (sterilized or pasteurized) products with incoming unprocessed food, should be prevented by proper layout of equipment. Hygienic design of food processing equipment involves the construction materials and the fabrication of equipment, which should be suitable for the processing operation and be easily cleaned. (Jowitt, 1980; Saravacos and Kostaropoulos, 2002). Government and professional regulations and standards of hygienic design and operation of food processing equipment include the USDA (meat and poultry), the US Department of Interior (fish), the FDA, and the International Association of Milk, Food, and Environmental Engineers (IAMFES). The 3-A sanitation standards, originally developed for milk processing equipment, are recently applied to other foods. The US Codes of Federal Regulations (CFR) contain information on sanitary (hygienic) design and operation of food plants. The European Hygienic Equipment Design Group (EHEDG) has developed guidelines and test methods for equipment used in food processing (EHEDG, 1997; Lelieveld et al., 2006). In the European Union, the 3-A sanitation standards and the EHEDG guidelines are recommended for various pieces of food processing equipment. Provisional safety and hygienic requirements have been published for various processing equipment, e.g., dough mixers, bakery ovens, mincing machinery, vegetable cutting machines, etc. The building services of food plants, such as air conditioning, refrigeration, and air filtration, should comply with the hygienic standards. The process and storage buildings should be designed and constructed to control (eliminate) pest infestation, i.e. rodents, insects, and birds. Food plant safety programs use the Hazard Analysis Critical Control Points (HACCP) system, which identifies, evaluates, and controls the microbiological, physical, and chemical hazards. The HACCP system was first devel-

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oped for meat, poultry, and dairy products, which are very sensitive to microbiological spoilage and health hazards (Gould, 1994). Recently, it has been expanded to several industries world-wide. Detailed HACCP programs are an integral part of Food Quality Control in most food industries. Food plant design should consider the application of HACCP programs during plant operation. Microbiological contamination and hazards should be minimized or eliminated by e.g., by product flow without cross contamination, and by positive air pressure in the processing areas (Saravacos and Kostaropoulos, 2002). 4. Cleaning of Equipment Food processing equipment needs periodic cleaning to remove undesirable deposits (fouling). The various deposits reduce the efficiency of the process equipment, and they may damage the quality of the processed food. Fouling is particularly serious in heat exchangers (plate or tube) handling heat-sensitive fluid foods, e.g., milk and fruit juice. The food processing equipment should be designed and fabricated so that it can be cleaned thoroughly. Small equipment can be cleaned by dismantling to individual parts. Large scale equipment is usually cleaned by Cleaning In Place (CIP) systems: The processing system (tanks, pumps, piping, process vessels, etc.) is rinsed with water, cleaned with alkali, rinsed again with water, neutralized with acid, and sanitized with chlorine solution (Seiberling, 1997). Two CIP systems are used, i.e. the once through and the recirculation systems. The cleaning processes of food plants should be monitored and tested according to cleaning standards and food safety regulations. 5. Plant Maintenance Large food processing plants, e.g., sugar refineries, may require a separate maintenance department with mechanical and electrical specialists. In smaller food preservation and food manufacturing plants, maintenance may be the responsibility of operating personnel, when the plant is not in operation. In some plants, outside maintenance contractors may be utilized. Preventive maintenance is applied to high-speed operating equipment, where some moving parts must be replaced before they are worn out. Predictive maintenance uses testing techniques to detect possible problems, e.g., vibration analysis, current analysis, thermography, and ultrasonic analysis (Chou, 2000). A parts inventory should be maintained in the plant, with as few as needed parts at hand. Modern plants use special computerized management systems.

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IV. FOOD PLANT UTILITIES The principal plant utilities in a food plant are process water, process steam, electric power for motors and lighting, and fuel (Robberts, 2002). 1. Process Water Process water is required for washing the raw materials and for various cooling operations. In fruit and vegetable processing plants, water may be used for transportation (fluming) of the raw materials from receiving to processing areas. Water used in steam boilers may require ion exchange treatment to reduce its hardness. Total water requirement in fruit and vegetable processing may range from 5 to 15 m3/ton of raw material (Greensmith, 1998). 2. Steam Steam boilers are needed in most food processing plants to provide process steam, used mainly in various operations, such as heating of process vessels, evaporators and dryers, sterilization, blanching, and peeling. A medium size food plant (80 tons/day raw material) may require a boiler producing about 10 tons/h of steam at 18 bar pressure. Two principal types of steam boilers are used in the food processing industry (Robberts, 2002), i.e. the fire-tube and the water-tube boilers. The firetube boilers operate at relatively lower pressure (1–24 bar) and produce cleaner steam. The water-tube units operate at higher pressures (100–140 bar) and they are suited for co-generation, i.e. electrical power and exhaust steam of lower pressure for process heating. Co-generation is economical in large food plants, requiring large amounts of low-pressure steam, e.g., beet sugar plants. Safety regulations for pressure vessels, such as the ASME codes are required for all steam boiler installations. A standby steam boiler of proper capacity may be necessary to provide process steam during any boiler failure or breakdown. Steam boilers are rated in Btu/h, kW or boiler HP (1 Btu/h = 0.293 W, 1 boiler HP = 9.8 kW). The heat flux in the boiler heating surface is about 0.75kW/m2. The boiler efficiency is about 85% with most of the thermal losses in the dry gases and the moisture. Steam generation is about 1.4 t/h per MW. In order to maintain the concentration of accumulated dissolved solids in steam boilers below 3500 ppm, periodic discharge of hot water (blowdown) is practiced. Fuel is used in food plants mostly for generating process steam and process drying. Natural gas and liquefied propane (LPG) are preferred fuels in food processing, because their combustion gases are not objectionable in direct contact with food products. Fuel oil and coal can be used for indirect heating, i.e. through heat exchangers. The heating values of the common industrial fuels

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are: natural gas 37.2 MJ/m3, LPG 50.4 MJ/kg, fuel oil 41.7 MJ/kg, anthracite coal 30.2 MJ/kg, and lignite coal 23.2 MJ/kg (Robberts, 2002; Saravacos and Kostaropoulos, 2002). Culinary steam of special quality is used when steam is injected in food products. The steam must be free of objectionable chemicals used in boilers, which may be carried into the food being heated. Culinary steam is usually produced from potable water in a secondary system of a heat exchanger heated with high pressure industrial steam. 3. Electricity Electrical power in food processing plants is needed for running the motors of the processing, control, and service equipment, for industrial heating, and for illumination. For a medium size food plant processing about 100 tons/day raw materials, the power requirement may of the order of 500 kW. A standby power generator of about 200 kVA is recommended for emergency operation of the main plant, in case of power failure or breakdown. Single-phase or three-phase alternating current (AC) of 110 V (60 cycles) or 220 V (50 cycles) is used in food processing plants. The electrical motors are either single-phase or three-phase squirrel cage. National codes, such as the US National Electrical Code (NEC) are applied in the electrical installations (Storm, 1997). Energy-efficient electrical motors should be used in various food processing operations. A measure of the efficiency of electrical power is the power factor (pf), defined as pf = kW/kVA, which should be equal or higher than 0.85. Illuminating (lighting) of industrial food plants should utilize fluorescent lamps, which can save significant amounts of energy. 4. Plant Effluents Plant effluents consisting mainly of wastewater, but including solids and gas wastes require special handling and treatments to comply with the local laws and regulations (Wang et al., 2006). Food plants should be designed and operated so that a minimum pollution is caused to the environment (Clark, 1997). The Environmental Protection Agency (EPA) in the US has issued codes and regulations that ensure the quality of natural water bodies is not damaged by effluent discharges from industrial plants. Similar regulations apply to atmospheric emissions of objectionable gases and dust. Environmental information needed to comply with EPA regulations for wastewater includes testing for pH, temperature, biochemical oxygen demand (BOD), fats oil and grease (FOG), and total suspended solids (TSS).

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Large amounts of waste are produced in the processing of fruits and vegetables, as in canning, freezing, and dehydration operations. Smaller waste volumes are produced in dairy plants (with the exception of cheese and milk powder), and in dry-processing (milling) of grain (e.g., wheat flour). A medium size fruit or vegetable processing plant handling about 100 ton/day of raw materials may discharge about 1000 m3/day of wastewater. Treatment of food wastewater may involve one or more of the following operations: 1. Simple screening out of the suspended solids, 2. gravel filtration, 3. solids settling in sedimentation tanks, 4. biological oxidation (aeration), 5. spray irrigation, 6. discharge into the local public sewer, and 7. discharge into a waterway. Liquid wastes (wastewater) can be disposed to the local waste (sewage) treatment plants, after removing some objectionable components, such as fat, oil, and grease to an acceptable level, e.g., lower than 1000 mg/L. Pollution loads higher than 200 mg/L are common in food plant liquid wastes. It is more economical to pay pollution surcharges to the local sewage plant, whenever possible, than to build an expensive wastewater treatment facility. Food preservation plants, located away from municipal sewage systems, dispose the process water to large storage ponds (lagoons), where a slow natural bio-oxidation of the organic waste takes place. The treated lagoon wastewater can be discharged to the land adjoining the plants (Storm, 1997). Some solid food wastes can be sold at relatively low prices for animal feeds, either unprocessed or dried, e.g., solid citrus or sugar beet wastes. Some solid food wastes can be diverted to the land (grape pomace to vineyard), while some other can be mixed with the soil (composting). The sanitary sewage of food plants, depending on the number of employees, should be treated in a different system than the process wastewater. It can be discharged to the local sewage system, if available. Otherwise, it is treated in septic tanks constructed near the food plant. Relatively small amounts of gas wastes (odorous VOC) are generated by some food industries, such as bakeries (ethanol), fishmeal dryers, and edible oil refining plants. Also, odors from coffee and cocoa roasting may require some form of treatment. Treatment of objectionable gas wastes involves gas absorption equipment, such as wet scrubbers (Saravacos and Kostaropoullos, 2002). The design of treatment facilities for industrial wastewater, and solids/gas wastes requires the expertise of environmental engineers who are familiar with the local laws and regulations concerning environmental pollution (Tsobanoglous and Franklin, 1991).

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V. FOOD PLANT ECONOMICS A detailed discussion of the economic aspects of food plants is presented in the following chapters of this book. Process Engineering Economics is essential in preparing the capital and operating cost estimates, and the profitability analysis of food processing plants (Peters et al., 2003; Couper, 2003). A preliminary economic analysis of capital costs, operating expenses, and profitability is needed to determine if a food plant project can be realized successfully. If the project appears feasible, detailed process engineering data, capital, and operating costs are obtained for the detailed engineering of the food plant. Economic analysis is also applied in process improvement projects (reduction of utilities and energy consumption), and in product improvement projects (food product quality, safety, stability). Modern economic analysis should be based on the new concepts of profitability, cash flow, and net present value. Process Engineering Economics is based on the estimation of capital costs and operating expenses, out of which plant profitability can be evaluated (Couper, 2003). A limited literature has been published on Food Process Economics: Bartholomai (1987), Clark (1997), Saravacos and Kostaropoulos (2002), Maroulis and Saravacos (2003), Lopez-Gomez and Barbosa-Canovas (2005). The design and scale-up of some food processing operations was discussed by Valentas et al. (1991). In addition to the classical quantitative economic criteria, some important intangible factors may control the viability of a food processing operation. They include employee safety, food safety and hygienic operation, and environmental and legal constraints (state, federal, and international). The capital requirements, operating expenses, and changes in cash flow should be estimated in order to meet the safety and environmental codes and regulations. 1. Capital Investment Cost The estimation of the capital investment or fixed capital cost is based on the process equipment cost, which is estimated in Food Process Design. The process flowsheet is used to calculate the material and energy balances and the utility requirements of the food processing plant. Detailed Chemical Engineering calculations and empirical shortcut methods are utilized to estimate the size and cost of the main processing equipment (Walas, 1988; Perry and Green, 1997; Saravacos and Kostaropoulos, 2002; Couper, 2003). Empirical factors or percentages of the equipment cost are used to estimate the various components of the Fixed Capital Investment, such as installation of equipment, site preparation, plant buildings, environmental control equipment, and engineering fees (see Chapter 5).

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Chapter 3

2. Operating Expenses Operating expenses of food plants include direct costs, such as raw materials and labor, and indirect costs, such as warehousing, maintenance, quality assurance, and office personnel (see Chapter 6). Raw materials and utilities expenses can be estimated with reasonable accuracy from material and energy balances for a process and from price information. Less literature is available on operating expenses than on capital investment. Operating expenses include cost of manufacturing and packaging the food product plus costs of selling and distribution plus maintenance and general overhead. Labor expenses are difficult to estimate, and practical experience is necessary. All the other cost items of the operating cost are estimated as percentage of labor expenses. The cost of packaging of many consumer products, such as beer, soft drinks, and breakfast cereals, can be higher than the cost of the ingredients. Modern food processing is applying new management techniques, such as JIT, FMS, and TQC. JIT (Just-In-Time Manufacturing) is used to reduce inventories, particularly when the finished food product is perishable in the warehouse, or when demand is temporarily very high. FMS (Flexible Manufacturing Systems) and CIM (Computer Integrated Manufacturing) utilize computer technology for more efficient and profitable operation. 3. Food Plant Logistics Logistics is defined as the design, organization, and management of the most effective flow of materials and information in an enterprise. It includes customer service, supply of materials, storage, management of inventories (stocks), distribution of products, materials handling, forecasting, materials traceability, information systems, documentation, and handling of orders. Logistics is important in the modern food supply chain, which involves raw materials, food processing plants, food storage, and distribution to customers. Recent developments in the standard of living of increasing world population have created the need for mass food production and efficient distribution. Globalization and competition among national and multinational companies require improved economics of raw materials, food plants, and distribution systems. Food plant logistics is concerned with the storage of processed foods in large quantities, near consumption centers, such as large cities and metropolitan areas. The stored products (including several nonfoods) are distributed to local supermarkets, food stores, and food service outlets. Logistics systems may be established and operated by own large food companies, but mostly by specialized companies (third party logistics, 3PL), which store, distribute, and offer services of added value. Logistics centers re-

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45

quire special equipment and personnel. Logistics installations may be rented to food processing and marketing companies. The building areas of logistics centers include dry and refrigerated storage rooms, product movement equipment (lift forks, conveyors), and associated services, i.e. refrigeration/air conditioning, administration. Large areas are constructed, e.g., 20 to 200 km2. Logistics center services include receiving of the product, quality control, product classification, storage/preservation, picking, packing, inventory control, and product renewal. Supply chain management (SCM) or stock and supply management includes warehousing and distribution systems. Automated distribution centers have been developed recently in the US. The right amount of stock must be available in storage (logistics) centers to cut costs. Large inventories of stored supplies are uneconomical, because considerable capital is immobilized. The FIFO (first in first out) system is applied to all products stored in the logistics centers. Particular attention is paid to sensitive food products of short expiration dates, e.g., pasteurized milk. The logistics and distribution costs of some food products may be high, e.g., 30% of the net sales of refrigerated pasteurized milk. Costs of logistics for other refrigerated products vary in the range of 5–7%, and for nonrefrigerated shelf-stored food products 2–3%. In general, the logistics cost is higher when the food industry operates its own facilities (3–10% of sales) than when outsourcing, i.e. using 3PL (2–5% of sales). REFERENCES Aguilera JM, Stanley DW, 1999. Microstructural Principles in Food Processing and Engineering. Aspen Publications. Bartholomai A, 1987. Food Factories - Processes, Equipment, Costs. VCH Publishers. Biegler LT, Grossman IE, Westerberg AW, 1997. Systematic Methods of Chemical Process Design. Prentice Hall. Center for Chemical Process Safety, 2005. Guidelines for safe handling of powders and bulk solids. AIChE. Chou CC, ed, 2000. Handbook of Sugar Refining. J Wiley. Clark JP, 1997. Cost and profitability estimation. In: KL Valentas, E Rotstein, RP Sing, eds, Handbook of Food Engineering Practice. CRC Press. Clark JP, 2000. Plant design and construction. In: Francis FJ, ed, Wiley Encyclopedia of Food Science and Technology. J Wiley. Couper JR, 2003. Process Engineering Economics. Marcel Dekker. Cramer MM, 2006. Food Plant Sanitation, Maintenance, and Good Manufacturing Practices. CRC Press. Cussler EL, Moggridge GD, 2001. Chemical Product Design. Cambridge Univ Press. Douglas JM, 1988. Conceptual Design of Chemical Processes. McGraw-Hill. Downing DL ed, 1996. A Complete Course in Canning, Vol 1, 13th Edition. CTI Publ. EHEDG, 1997. Guidelines and test methods. Trends in Food Science and Technology.

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Fryer PJ, Pyle DI, Rielly CD, 1997. Chemical Engineering for the Food Industry. Blackie Academic and Professional. Gould WA, 1994. Current GMP’s in Food Plant Sanitation. CTI Publications. Gould WA, 1996. Unit Operations for the Food Industries. CTI Publications. Greensmith M, 1998. Practical Dehydration, 2nd Edition. Woodland Publications. Imholte TJ, 1984. Engineering for Foods Safety and Sanitation. Technical Institute of Food Safety. Crystal. Jowitt R, 1980. Hygienic Design and Operation of Food Plant. Ellis Horwood. Kletz T, 1999. HAZOP and HAZAN, 4th Edition. IChemE. Lelieveld H, Mostert M, Holah J, 2006. Handbook of Hygiene Control in the Food Industry. CRC Press. Lopez-Gomez A, Barbozs-Canovas G, 2005. Food Plant Design. Taylor and Francis. Maroulis ZB, Saravacos GD, 2003. Food Process Design. Marcel Dekker. Marriott NG, 1997. Essentials of Food Sanitation. Chapman Hall. National Fire Protection Association, 2000. Standard for the prevention of fire and dust explosions from the manufacturing, processing, and handling of combustible particulate solids. NFPA 634. National Fire Protection. Perry RH, Green DW, Maloney JO, 1997. Perry’s Chemical Engineers’ Handbook, 7th Edition. McGraw-Hill. Peters SM and Timmerhaus KD, West RE, 2003. Plant Design and Economics for Chemical Engineers, 5th Edition. McGraw-Hill. Rahman S, 1995. Food Properties Handbook, CRC Press. Rao MA, Rizvi SSH, Datta AK, 2005. Engineering Properties of Foods, 3rd Edition, Taylor and Francis. Robberts TC, 2002. Food Plant Engineering Systems. CRC Press. Saravacos GD, Kostaropoulos AE, 2002. Handbook of Food Processing Equipment. Kluwer Academic/Plenum. Saravacos GD, Maroulis ZB, 2001. Transport Properties of Foods. Marcel Dekker. Seiberling DA, 1997. CIP sanitary process design. In: Valentas KJ, Rotstein E, Singh RP, eds, “Handbook of Food Engineering Practice”. CRC Press. Seider WD, Seader JD, Lwein DR,1999. Process Design Principles. J Wiley. Sinnot RK, 1996. Chemical process design. In: Coulson JM, Richardson JF, eds, Chemical Engineering, Vol 6, Butterworth-Heinemann. Smith R, 1995. Chemical Process Design. McGraw-Hill. Storm D, 1997. Winery Utilities. Chapman and Hall. Troller JA, 1993. Sanitation in Food Processing, 2nd ed. Academic Press. Tsobanoglous G, Franklin RL, 1991. Wastewater Engineering, Treatment, Disposal, Reuse, 3rd Edition. McGraw-Hill. Turton R, Bailie RC, Whiting WB, Shaeiwitz JA, 1998. Analysis, Synthesis and Design of Chemical Processes. Prentice Hall. Valentas KJ, Levine L, Clark JP, 1991. Food Processing Operations and Scale-Up. Marcel Dekker. Wang LK, Hung Y-T, Lo HH, Yapijakis C, 2006. Waste Treatment in the Food Processing Industry. CRC Press. Walas SM, 1988. Chemical Process Equipment. Butterworth-Heinemann. Zaror CA, Pyle DL, 1997. Process design: an exercise and simulation results. In: PJ Fryer, DL Pyle, CD Reilley, eds. “Chemical Engineering for the Food Industry”. Blackie A & P.

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4 Process Engineering Economics Process engineering economics is concerned with the design, operation, and economic analysis of processing plants. It has been applied successfully to the chemical process industries, resulting in economic production of large quantities of chemicals, petrochemicals, and other products. The chemical engineering aspects of process economics have been presented by Peters and Timmerhaus (2003), Holland and Wilkinson (1997), and Couper (2003), Brown (2007). Application of process engineering economics to the food industry has been limited, due to the diversity of food processes and the lack of engineering and economic data related to the complex food products (Clark, 1997). However, recent advances in food engineering, especially in the engineering properties of foods and in the computer application in food process design, can be utilized in developing food process economics, resulting in more efficient and profitable food processing plants. I. MONEY FLOW IN A BUSINESS ENTERPRISE Modern companies and corporations are complex in their financial structure, but basically, the following model describes them adequately (Clark, 1997): A successful business enterprise must survive financially, which means that it must generate enough money to pay its obligations by selling goods or 47

© 2008 by Taylor & Francis Group, LLC

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Chapter 4

services at prices that exceed their cost. A typical money flow diagram to and from an enterprise is summarized in Figure 4.1. The various businesses utilize some form of assets to generate the goods or services sold. The assets of food industries include mainly the manufacturing plant and the distribution system. The initial capital is provided by the investors and the banks. The inventors who provide a portion of the capital expect to earn a profitable return. This return comes from dividends and/or from an increase in the value of their shares in a stock market. The banks which provide the remainder portion of the initial capital expect to recover their capital plus the appropriate interests. As the business operates, a sales income is obtained from the consumers. This income is used to pay the various resources spent in the manufacturing process, that is raw materials, utilities, labor, maintenance, etc. The difference between money flowing in from sales and money flowing out for expenses (manufacturing cost) is the gross profit. From the gross profit obtained, the tax and the loan payments are subtracted to obtain the net profit. The net profit is divided to the dividends payment and the retained earnings, which are used for reinvestments. Loan

Consumers FIRM Sales Income

Banks

Loan Payment

Manufacturing Cost

Resources Own Capital

Taxes

Investors

Dividend Tax Authorities

Figure 4.1 A simplified money flow diagram to and from a business enterprise.

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Once survival is obtained, the second important purpose of a business is to enhance its value. Value may reflect in the market price of publicly traded stock or in calculated book value. In theory, stock prices reflect the present value of future cash flows to the stockholders, often estimated as earnings per share. In practice, the actual price of a stock is affected by supply and demand, by opinions about the economy, and by opinions about potential changes in future earnings of the firm. Rapid growth companies often are valued more highly than those seen as more stable. They often achieve their results: (a) by retaining a higher portion of earnings, sometimes paying no dividends at all; and (b) by assuming relatively high debt loads, thus acquiring assets more quickly than profits alone would permit. Most major food companies are stable and have stocks which usually pay dividends, with a balance between debt and equity in their financial structure. They obtain predictable earnings, which lead to stock values, which can grow steadily and reliably over time. The ultimate purpose of capital and operating cost estimates is to help allocate the funds available for investment so as to increase the value of the firm, with less concern of how it is realized. Cash is of primary importance in business, and it is critical to survival and value enhancement. Thus, most evaluation techniques depend on estimating the cash impact of investment. II. CAPITAL COST The total capital CT invested in a processing plant, as shown in Figure 4.2, consists of the following: • •

The fixed capital CF or fixed investment, needed to supply the necessary plant facilities, and The working capital CW, necessary for the operation of the plant that is:

CT = C F + CW

(4.1)

The fixed capital CF includes the cost of the purchased equipment, installation, piping, instrumentation and control, electricals, buildings, site improvement, land, off-site facilities, engineering, start-up, contractors fee, and contingency, as shown in Figure 4.2.

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Chapter 4

CAPITAL COST

Fixed

0 Purchased Equipment 1 Installation 2 Piping 3 Instrumentation and control 4 Electrical 5 Buildings 6 Site improvement 7 Land 8 Off-site facilities 9 Engineering 10 Start-up 11 Contractors fee 12 Contigency

Working

Figure 4.2 Total capital cost breakdown. The working capital CW in an industrial plant consists of the total amount of money invested in raw materials and supplies carried in stock, finished and semi-finished products, accounts receivable and payable, and cash kept on hand. 1. Fixed Capital Cost The fixed capital investment in a processing plant can be estimated from empirical rules or approximations. For example, the Lang method can be used to estimate the fixed capital CF from the process equipment cost Ceq, using the empirical equation (Chilton, 1960; Peters and Timmerhaus, 2003):

C F = f L C eq

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(4.2)

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51

where fL is the Lang factor and Ceq the purchased equipment cost. The purchased equipment cost Ceq is calculated using the following equation, after a process sizing procedure: Ceq =

∑ j

⎛ Aj C0 j ⎜ ⎜ A0 j ⎝

⎞ ⎟ ⎟ ⎠

nj

(4.3)

where, Aj is the size of the jth equipment, C0j is the cost of the jth equipment at a standard size A0j and nj the scaling factor of the jth equipment. The most important equipment is included in Equation 4.3. Updated values of the equipment cost characteristics (C0j, A0j, and nj) are discussed in Chapter 5. Traditionally, for plants in Chemical Process Industry (CPI), the Lang factor varies in the following ranges (see, for example, Sinnott (1996), Holland and Wilkinson (1997), or Seider et al. (1999)): 3.10 − 3.80 for solids processing f L = 3.60 − 4.10 for mixed fluids/solids processing 4.70 − 4.80 for fluids processing

(4.4)

The higher fL factor for gases and liquids processing is due to the higher requirements for piping and valves. The above values refer to plant expansion cost. For grass roots (entirely new) plant cost, these values should be increased by 1. It is generally recognized that the Lang method has the tendency to overestimate the fixed capital cost. In food processing plants, the fL factor is generally smaller, because of the higher cost of equipment (stainless steel) and less piping. Cost data of various food processing plants presented by Bartholomai (1987) and compiled by Marouli and Maroulis (2005) are summarized in Table 4.1 and Figure 4.3. Both Table 4.1 and Figure 4.3 present a revealing picture of the Lang factor for various food plants. Thus, the Lang factor fL for food industries should be considered in the range:

1.35 minimum f L = 1.80 most probable 2.75 maximum

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(4.5)

52

Chapter 4

Table 4.1 Lang Factor fL for Various Food Processing Plants Plant Fruits and Vegetables Apple Processing Plant Fruit Puree Plant Orange Juice Concentrate Plant Tomato Paste Plant Frozen Vegetable Plant Dairy and Egg Products Mozzarella Cheese Plant Blue Cheese Plant Dairy Plant Modular Dairy Plant Milk Powder Plant Dried Whole Egg Plant Yogurt Plant Ice Cream Plant Cereals and Grains Parboiled Rice Plant Corn Starch Plant Pasta and Tofu Pasta Plant Precooked Lasagna Plant Fermantation Baker's Yeast Plant Vinegar Plant Extruded Products and Snacks Quenelles Plant Tortilla Chip Plant Corn Snacks Plant Seafoods and Meats Catfish Processing Plant Shrimp Processing Plant Surimi Plant Coextruded Sausage Plant Protein Recovery Plant Fats and Oils Vegetable Oil Refinery Baked Products Pan Bread Bakery Arabic Bread Bakery Half-baked Frozen Baguette Bakery Beverages Sea Water Desilination Plant Fruit Juice Plant

C eq

CF

fL

3.93 1.53 2.03 2.08 1.61

5.85 2.20 4.12 3.67 2.70

1.49 1.43 2.02 1.76 1.68

0.68 5.72 13.2 1.52 5.40 2.61 6.47 2.66

1.68 8.19 27.1 2.42 8.00 4.57 9.66 5.03

2.47 1.43 2.05 1.59 1.48 1.76 1.49 1.89

1.78 27.4

2.76 60.6

1.55 2.21

3.43 4.42

4.71 6.52

1.37 1.47

19.6 1.00

53.1 1.50

2.72 1.50

0.95 2.50 0.24

1.97 3.38 0.62

2.07 1.35 2.53

2.02 0.38 11.8 2.00 3.80

4.80 0.86 20.0 4.00 5.34

2.37 2.25 1.70 2.00 1.41

2.64

4.72

1.79

3.44 1.32 2.38

5.61 2.54 3.91

1.63 1.93 1.64

16.1 0.99

36.9 1.62

2.29 1.63

Ceq equipment cost in M$, CF fixed capital cost in M$. © 2008 by Taylor & Francis Group, LLC

Process Engineering Economics

53

100

corn starch dry yeast

water milk products seafood

10

yogurt skim milk powder

blue cheese

Fixed capital cost CF (M$)

lasagna white bread apple products ice cream protein frozen fish pasta concentrated juice egg powder sausages frozen bread tomato paste tortilla chips

parboiled rice arabic bread quenelles (dumplings) mozzarella cheese

frozen vegetables milk products fruit puree

vinegar fruit juice

1 frozen shrimp

C F = f L C eq

corn snacks

fL = 1.35 minimum 1.80 fitted 2.75 maximum

0.1 0.1

1

10

Equipment cost C eq (M$)

Figure 4.3 Fixed capital cost versus equipment cost for various food processing plants. Data from Bartholomai (1987).

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1 00

54

Chapter 4

Nevertheless, in modern food processing plants, using modern instrumentation and process control, environmental protection (effluent treatment), and computers, the Lang factor may be greater. A value of 3 should be considered as safe enough for preliminary estimations. This value corresponds to main processing plants or plant expansion, while for grass roots plants it should be increased to 4, as analyzed in Table 4.2 and summarized in Figure 4.4. Table 4.2 is a breakdown of the Lang factor to its components. Typical average values for food industries are presented. These values will be used in all applications in this book in order to obtain comparable results between the various industries examined in the second part of the book. Table 4.2 Lang Factor Breakdown for Food Plants Plant expansion 0 Purchased Equipment

1.00

Grass roots (new) 1.00

1.00 1 2 3 4

Installation Piping Instrumentation and control Electrical

0.50 0.25 0.15 0.10

1.00 0.50 0.25 0.15 0.10

1.00 5 Buildings 6 Yard improvement 7 Land

0.35 0.05 0.10

1.00 0.35 0.05 0.10

0.50 8 Off-site facilities

0.00

0.50 1.00

0.00 9 10 11 12

Engineering Start-up Contractors fee Contingency Lang Factor

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0.25 0.10 0.05 0.10

1.00 0.25 0.10 0.05 0.10

0.50

0.50

3.00

4.00

Process Engineering Economics

55

Fluids

Fluids/solids

Solids

Traditional values chemical process plants

Food processing plants (Data from Bartholomai, 1987)

Foods

Suggested values for modern food processing plants Plant expansion

Grass roots

Foods

0

1

2

3

4

5

Lang factor

Figure 4.4 Lang factor ranges for chemical and food processing plants.

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6

56

Chapter 4

2. Working Capital Cost

It is logical to estimate the working capital cost as a fraction of the annual sales income S:

CW = f WS S

(4.6)

The working capital factor fWS essentially expresses the so called collection period tcol: f WS = t col =

CW S

(4.7)

which is the fraction of the year needed to collect the working capital from the sales income. Nevertheless, in plant design it is more convenient and more usual to estimate the working capital as a fraction of the fixed capital:

CW = f WF C F

(4.8)

The following equation correlates the above two factors:

fWF = TCR fWS

(4.9)

where TCR is the turnover to capital ratio defined as: TCR =

S CF

(4.10)

Turnover to capital ratio TCR is a characteristic of the type of the food plant. It varies from 0.2 to 5. Values less than 1 are for large volume, capitalintensive plants, while values greater than 1 are for plants with small equipment or expensive raw materials. Exemplary values are presented by Holland and Wilkinson (1997) in Table 4.3. It must be noted that these data are very old (before 1960). More recent results for food plants, presented in Table 4.4 and Figure 4.5, were derived from the data presented by Bartholonai (1986).

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Table 4.3 Working Capital Factors Estimation Working Capital Factors

f WS = t col f WF = TCR f WS

where Collection Period

t col = 0.10

(0.10 y = 36 days)

Turnover to Capital Ratio

TCR = 0.50 1.00 1.50

for chemicals for pharmaceuticals for foods

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Chapter 4

Table 4.4 Turnover to Capital Ratio TCR for Food Processing Plants Plant CF S Fruits and Vegetables Apple Processing Plant 5.85 17.0 Fruit Puree Plant 2.20 2.82 Orange Juice Concentrate Plant 4.12 12.6 Tomato Paste Plant 3.67 19.2 Frozen Vegetable Plant 2.70 5.62 Dairy and Egg Products Mozzarella Cheese Plant 1.68 4.07 Blue Cheese Plant 8.19 5.78 Dairy Plant 27.1 24.0 Modular Dairy Plant 2.42 2.39 Milk Powder Plant 8.00 30.7 Dried Whole Egg Plant 4.57 9.80 Yogurt Plant 9.66 27.2 Ice Cream Plant 5.03 4.07 Cereals and Grains Parboiled Rice Plant 2.76 1.14 Corn Starch Plant 60.6 36.5 Pasta and Tofu Pasta Plant 4.71 4.37 Precooked Lasagna Plant 6.52 5.33 Fermantation Vinegar Plant 1.50 1.06 Extruded Products and Snacks Quenelles Plant 1.97 2.17 Tortilla Chip Plant 3.38 3.56 Corn Snacks Plant 0.62 0.56 Seafoods and Meats Catfish Processing Plant 4.80 25.1 Shrimp Processing Plant 0.86 1.83 Surimi Plant 20.0 28.4 Cattle Slaughterhouse 7.32 61.9 Coextruded Sausage Plant 4.00 1.50 Protein Recovery Plant 5.34 4.99 Fats and Oils Soybean Oil Extraction Plant 49.8 166 Vegetable Oil Refinery 4.72 16.9 Baked Products Pan Bread Bakery 5.61 8.97 Arabic Bread Bakery 2.54 6.54 Half-baked Frozen Baguette Bakery 3.91 3.16 Beverages Sea Water Desilination Plant 36.9 24.6 Fruit Juice Plant 1.62 3.68 S annual sales in M$/y, CF fixed capital cost in M$. Data from Bartholomai (1987).

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TCR 2.90 1.28 3.06 5.23 2.08 2.42 0.71 0.89 0.99 3.84 2.14 2.81 0.81 0.41 0.60 0.93 0.82 0.70 1.10 1.05 0.91 5.22 2.13 1.42 8.45 0.38 0.93 3.33 3.57 1.60 2.57 0.81 0.67 2.27

Process Engineering Economics

59

1 000

soybean oil 1 00 slaughter products corn starch

yogurt

Annual sales S (M$/yr)

frozen fish tomato paste apple products

seafood skim milk powder cooking oil

water

milk products

concentrated juice egg powder

10

arabic bread

white bread

lasagna protein frozen vegetables blue cheese mozzarella cheese ice cream pasta frozen bread fruit juice fruit puree tortilla chips quenelles (dumplings) milk products frozen shrimp sausages

TCR = 1

parboiled rice

8.45 maximum

vinegar

1.54 best fit 0.38 minimum

corn snacks

S = TCR C F

0.1 0.1

1

10

1 00

Fixed capital C F (M$)

Figure 4.5 Annual sales versus fixed capital cost for various food processing plants. Data from Bartholomai (1987).

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Chapter 4

III. MANUFACTURING COST

The annual manufacturing cost CM required to operate a processing plant consists of (See Figure 4.6): • •

The direct manufacturing cost, also called operating cost, which includes a part analogous to fixed capital cost CMF, called “fixed”, and a part analogous to production capacity CMV, called “variable” The indirect manufacturing cost COver, also called overheads, which includes all the enterprise allocated costs that is:

C M = C MF + C MV + C Over

(4.11)

Overhead cost is also variable cost but it is kept separately, since it depends on the allocation of the enterprise’s general costs, which do not concern directly the examined plant. Based on the above definition, the following equations could be stated:

CMF = f MF CF

(4.12)

CMV = f MV S

(4.13)

COver = f Over S

(4.14)

where the coefficients of the above analogies are called cost factors. They are characteristic of the plant, as shown exemplarily in Table 4.5. The fixed manufacturing cost factor fMF can be approximated through experience, based on its component values. The overheads manufacturing cost factor fOver is extremely variable depending on the enterprise characteristics, which does not necessary reflect the plant characteristics. It is an allocated cost. The variable manufacturing cost factor fMV is a crucial magnitude. The direct variable manufacturing cost CMV is the sum of the raw materials cost CMat, the packaging materials cost CPack, the utilities cost CUtil, and the labor cost CLab:

CMV = CMat + C Pack + CUtil + C Lab

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(4.15)

Process Engineering Economics

61

MANUFACTURING COST

Direct (Operating)

Fixed 1 Maintenance 2 Insurance 3 Taxes 4 Royalties

Variable 1 Raw Materials 2 Packaging Materials 3 Utilities 4 Labor

Indirect (Overheads) 1 Sales Expenses 2 General Expenses

Figure 4.6 Manufacturing cost breakdown.

The above components of the direct manufacturing cost can be estimated from the material and energy balances, the process manning, and the production schedule of the examined plant. The following set of equations is a systematic attempt to estimate these magnitudes.

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Chapter 4

Table 4.5 Exemplary Values of Manufacturing Cost Factors Manufacturing Cost 1 2 3 4

Fixed Maintenance Insurance Taxes Royalties

5 6 7 8

Variable Raw Materials Packaging Utilities Labor

9 10

Overheads Sales Expences General Expenses

Fixed Capital

f MF =

Sales Income

0.12 0.01 0.01 0.01 0.15

f MV =

0.20 0.05 0.05 0.20 0.50

f Over =

0.05 0.05 0.10

The sales S is calculated by the following equation: S =t

∑F

Pj c Pj

(4.16)

j

where FPj (t/h) is the flow rate of the jth product material, cPj ($/t) is the unit cost of the jth product material, and t (h/y) is the annual operating time. The cost of the raw materials CMat required by the process is calculated from the material balances: C Mat = t

∑F

Rj c Rj

(4.17)

j

where FRj (t/h) is the flow rate of the jth raw material, and cRj ($/t) is the unit cost of the jth raw material.

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Similarly, the cost of the packaging materials CPack required by the process is calculated from the material balances: C Pack = t

∑F

Gj cGj

(4.18)

j

where FGj (t/h) is the flow rate of the jth raw material, cGj ($/t) is the unit cost of the jth packaging material. The cost of utilities CUtil required by the process is calculated from the energy balance: CUtil = t

∑F

Uj cUj

(4.19)

j

where FUj (t/h) is the flow rate of the jth utility, and cUj ($/t) is the unit cost of the jth utility. The annual cost of labor CLab is calculated by the following equation: C Lab = t

∑M c

j Lj

(4.20)

j

where Mj is the required manpower at the jth specialization level, cLj ($/h) is the corresponding labor rate. The total manufacturing cost CMT, also called total annualized cost TAC, includes the annualized capital charge, that is:

CMT = C M + e CT

(4.21)

where CT is the total capital invested, CM the manufacturing cost, and e is the capital recovery factor, which is calculated from the equation:

e = CRF (i, N ) =

i 1 − (1 + i) − N

(4.22)

where i is the discount rate, expressing the time value of money, and N is the life time of the investment. The information flow diagram for estimation of the total manufacturing cost is summarized in Figure 4.7.

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Chapter 4

Process

Equipment Cost

Sizing

Ceq =

∑ j

Working Capital Cost

⎛ Aj Coj ⎜ ⎜ Aoj ⎝

⎞ ⎟ ⎟ ⎠

nj

CW = fW CS Fixed Capital Cost

Sales Income Material

CS = t y

Balances

C F = f L Ceq

∑P c

j Pj

j

Raw Materials Cost

CMat = f Mat t y

Fixed Manufacturing Cost

∑R c

j Mj

C MF = f MF C F

j

Energy Balance

Packing Materials Cost

C Pack = f Pack t y

Overheads

∑G c

j Gj

j

Utilities Cost Process

(Sales, General Expenses)

C Over = f Over C S Variable Manufacturing Cost

CUtil = fUtil t y

∑Q c

j Uj

j

Manning

C MV = C Mat + C Pack + CUtil + C Lab

Labor Cost

C Lab = f Lab t y

∑M c

j Lj

j

Manufacturing Cost Production Planning

C M = C MV + C MF + C Over Total Manufacturing Cost

C MT = C M + eCT

Total Capital Cost

C T = C F + CW

Figure 4.7 Information flow diagram for manufacturing cost estimation.

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65

IV. CASH FLOW ANALYSIS

Modern plant profitability techniques are based on cash flow analysis which is described in the present section. It is presented for both the construction and operating periods as shown in Figures 4.8 and 4.9, respectively. Both figures come from the generalized flow diagram of Figure 4.1. 1. Construction Period

It is assumed that the total capital invested CT is covered partially by the investors CO and the remainder CL is borrowed from a bank loaner, that is:

CT = CO + CL

(4.23)

The fraction of the total capital obtained by loaning is called the leverage ratio λ. Consequently, the loan CL and the own capital CO are as follows:

tal:

C L = λ CT

(4.24)

CO = (1 − λ )CT

(4.25)

The total capital invested is used for both fixed CF and working CW capi-

CT = CF + CW

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(4.26)

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Fixed Capital

Chapter 4

INDUSTRIAL OPERATIONS

CF

Total Capital

Working Capital

CT

CW

PRODUCTION RESOURCES

Sales Income

S

Manufacturing Cost

CM

TAX AUTHORITIES

Gross Profit

PG

Taxes

TX

BANKS FIRM'S BANK

Loan

Loan Payment

CL

PL

INVESTORS

Profit

P

Own Capital

Devidend

CO

PD Retained Earnings

PR

Figure 4.8 A money flow diagram for financial analysis model. Construction period.

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67

2. Operating Period

The annual gross profit PGn is the sales income Sn minus the manufacturing cost CMn:

PGn = S n − C Mn

(4.27)

The subscript n denotes the nth year of operation. The taxable income PTn is the annual gross profit PGn minus the depreciation allowed by the tax authorities, minus the interest part of the loan payment:

PTn = PGn − d n C F − bn' C L

(4.28)

where dn is annual depreciation allowed by the tax authorities for computing taxable income, b’n is the annual interest payment as a fraction of the total loan. Thus, the annual taxes TXn are calculated by the following equation, considering an income tax rate t:

TXn = t PTn

(4.29)

The annual loan payment LX is calculated by the equation:

LX = b CL

(4.30)

Consequently the annual profit after taxes and loan payment Pn is calculated by the equation:

Pn = PGn − TXn − LX

(4.31)

The depreciation rate dn is decided by the tax authorities:

d n = d (n, N D )

(4.32)

where d( ) is a function describing the method adopted and ND is the period of recovery.

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Table 4.6 summarizes some often used depreciation methods. The amount depreciated in any given year dn and the unrecovery value BV (book value) are presented. The results are compared in Figures 4.10 and 4.11. The MACRS method presented in tabulated format is the current method used in USA. The annual loan payment as a fraction of the loan b depends on the loan interest rate iL and the loan payoff period NL, both being subject of negotiation with the bank loaner:

b=

iL

(4.33)

1 − (1 + iL ) − N L

It must be noted that both ND and NL are generally different from the economic life of the project N. Loan payment is the sum of two terms: • •

The interest payment, and The capital payment.

This distinction is crucial in financial analysis since only the interest payment is tax deductible, as noted in Equation (4.20). The interest payment as a fraction of the loan bn’ is calculated by Equation 4.34 and depicted in Figure 4.12.

(

)

bn' = 1 − (1 + i) n− N −1 b

(4.34)

The following equation calculates the unpaid fraction of the loan Ln at the end of the nth year:

Ln =

1 − (1 + iL ) n− N L 1 − (1 + iL ) − N L

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(4.35)

Process Engineering Economics

Fixed Capital

69

INDUSTRIAL OPERATIONS

CF

Total Capital

Working Capital

CT

CW

PRODUCTION RESOURCES

Sales Income

S

Manufacturing Cost

CM

TAX AUTHORITIES

Gross Profit

PG

Taxes

TX

BANKS FIRM'S BANK

Loan

Loan Payment

CL

PL

INVESTORS

Profit

P

Own Capital

Devidend

CO

PD Retained Earnings

PR

Figure 4.9 A money flow diagram for financial analysis model. Operating period.

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Chapter 4

Table 4.6 Summary of Usually Used Depreciation Methods Depreciation method

Straight Line (SL)

Depreciation rate d n

dn =

Double Declining Balance (DDB)

dn =

Unrecovery value C n

1 N

Cn = 1−

2⎛ 2⎞ ⎜1 − ⎟ N⎝ N⎠

n −1

1 n N

2⎞ ⎛ Cn = ⎜1 − ⎟ ⎝ N⎠

n

Modified Accelerated Cost Recovery System (MACRS)

dn =

n

see values bellow

Cn = 1−

∑d

y

y =1

Year n (y) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Recovery period N (y) 3 5 33.33 20.00 44.45 32.00 14.81 19.20 7.41 11.52 11.52 5.76

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7 14.29 24.49 17.49 12.49 8.93 8.92 8.93 4.46

10 10.00 18.00 14.40 11.52 9.22 7.37 6.55 6.55 6.56 6.55 3.28

15 5.00 9.50 8.55 7.70 6.93 6.23 5.90 5.90 5.91 5.90 5.91 5.90 5.91 5.90 5.91 2.95

20 3.750 7.219 6.677 6.177 5.713 5.285 4.888 4.522 4.462 4.461 4.462 4.461 4.462 4.461 4.462 4.461 4.462 4.461 4.462 4.461 2.231

Annual depreciation rate dn (-)

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71

0.3

0.2

Straight Line

0.1

0.0 1

2

3

0.3

4

5

6

7

8

Recovery period (y)

0.2 Double Declining Balance 0.1

0.0 1

2

3

4

5

6

7

8

Recovery period (y)

0.3

Modified Accelerated Cost Recovery System 0.2

0.1

0.0 1

2

3

4

5

Time n (y)

Figure 4.10 Comparison of various depreciation methods.

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6

7

8

72

Chapter 4

Unrecovery fraction (-)

1.0 Modified Accelerated Cost Recovery System

0.8

0.6

Straight Line

0.4 Double Declining Balance

0.2

0.0 0

1

2

3

4

5

6

7

8

Time n (y)

Unrecovery fraction (-)

1.0

0.8

0.6

Recovery period N (y) 20

0.4 15 0.2

5

3

7

10

0.0 0

2

4

6

8

10

12

14

Time n (y)

Figure 4.11 Comparison of various depreciation methods.

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16

18

20

22

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73

Annual payment (-)

0.30

0.20

0.10

0.00 1

2

3

4

5

6

7

8

9

10

Time n (y)

1.00

Unpaid loan (-)

0.80

0.60

0.40

0.20

0.00 0

1

2

3

4

5

6

7

8

9

10

Time n (y)

Figure 4.12 Capital and interest loan payment versus time. Unpaid loan versus time.

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Chapter 4

3. Discounted Cash Flow

The annual cash flow defined in Equation (4.31) is summed over N years to get the Cumulated Cash Flow CCF, which characterizes the total project: N

CCF = −CO +

∑P

(4.36)

n

n=1

The Cumulated Cash Flow CCF does not take into account the time value of money. Instead, the Net Present Value NPV, defined by Equation (4.37), does: N

NPV = −CO +

Pn

∑ (1 + i) n=1

n

(4.37)

where i is the interest rate, expressing the time value of money. It must be noted that: NPV = CCF , when i = 0

(4.38)

In conclusion, the most important magnitudes in financial analysis are: the Cumulated Cash Flow CCF, and the Net Present Value NPV If P is constant over the years, then it can be proved that:

CCF = −CO + N P NPV = −CO +

P i , where e = e 1 − (1 + i ) − N

(4.39) (4.40)

Figure 4.13a depicts the cash flow of an exemplary project, while Figure 4.13b represents both the Cumulated Cash Flow CCF and the Net Present Value NPV of the project versus time N. The following characteristic time periods are shown: NC Construction period ND Depreciation period NL Loan period

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Process Engineering Economics

Economic lifetime

NE 350

NL

300 250 Cash flow (k$/y)

75

ND

200

CF

150 100

NC

50 0 -50

NE

-100 -150 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Time n (y)

600 NE

Net present value (k$)

500

NL

400

CCF

ND

300

NC

200 100

NPV

0 -100 0

5

10

15

20

Time n (y)

Figure 4.13 A money flow diagram for financial analysis model.

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25

30

76

Chapter 4

V. PLANT PROFITABILITY

There are essentially three bases used for the evaluation of profitability: cash, time, and interest rate. For each of these bases the time value of money can be taken into account (discounted techniques) or not (nondiscounted), as shown in Table 4.7. Cumulated Cash Flow CCF has been defined by Equation (4.36) in the previous section. It is a function of time N. Simple Payback Period SPB is defined as the time N when CCF equals to zero:

N = SPB ⇒ CCF = 0

(4.41)

The inverse of the simple payback period SPB is called the Return on Investment ROI:

ROI =

1 SPB

(4.42)

Net Present Value NPV has been defined by Equation (4.37) in the previous section. It is a function of both time N and interest rate i. Discounted Payback Period DPB is defined as the time N at which NPV equals zero:

N = DPB ⇒ NPV = 0

(4.43)

Discounted Payback Period DPB is a function of interest rate i. The internal rate of return IRR is defined by the following relation:

i = IRR ⇒ NPV = 0 Internal rate of return IRR is a function of time N.

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(4.44)

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Table 4.7 Measures of Plant Profitability

Cash Time Rate

Nondiscounted

Discounted

Cumulated Cash Flow, CCF Simple Payback Period, SPB Return on Investment, ROI

Net Present Value, NPV Discounted Payback Period, DPB Internal Rate of Return, IRR

If P is constant then it can be proved that: SPB =

CT P

(4.45)

ROI =

P CT

(4.46)

DPB =

ln (1 − i SPB)−1 ln(1 + i )

ROI =

(

)

IRR

1 − (1 + IRR)− N

(4.47)

(4.48)

The following inequalities should be kept in mind:

DPB ≥ SPB, DPB = SPB ⇔ i = 0

(4.49)

IRR ≤ ROI, IRR → ROI ⇔ N → ∞

(4.50)

Recently, the Economic Value Added (EVA) concept is used in financial analysis. It is defined as the after-tax net operating profit minus the cost of capital (Couper, 2003). A positive EVA value means that a business earns more than the cost of capital. EVA analysis can improve the efficiency of operation of food processing plants.

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Chapter 4

Table 4.8 presents the measures of the plant profitability which will be used in the examples of this book. Capital Return Ratio CRR is defined as the ratio of the Net Present Value to the Own Capital invested (Couper, 2003; Holland and Wilkinson, 1997; Brennan, 1998): CRR = NPV / CO

(4.51)

Table 4.8 Measures of Plant Profitability IRR Internal Rate of Return DPB Discounted Pay Back Period NPV Net Present Value CRR Capital Return Ratio

VI. SENSITIVITY ANALYSIS

Plant profitability depends on a lot of technical and economic factors. Thus, it is crucial to obtain the effect of the most significant factors on the profitability. The resulting procedure is called sensitivity analysis and the most common technique applied is to vary one factor at a time and calculate the effect on the profitability measures. The following steps are normally used: 1. 2. 3. 4. 5.

Determine which factors of interest should be examined Select the range and the increment of variation for each factor Select the measure or measures of profitability to be calculated Compute the results changing one factor at a time Display the results in tables or figures

A typical figure to show the sensitivity analysis results is the so called “spider plot”. It represents the relative variation of the profitability measure versus the relative variation of each factor (see Figure 4.14). Sensitivity analysis is easy to prepare and yields useful information (Moresi, 1984).

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0.30 Factor 5

0.20

Factor 1

Relative change of profitability

Factor 4 0.10

Factor 2

Factor 3

0.00

Factor 3 Factor 2 Factor 4

-0.10

Factor 1 -0.20

Factor 5

-0.30 -0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

Relative change in each factor

Figure 4.14 Results of a sensitivity analysis using the spider plot.

A special case of sensitivity analysis is the “break-even analysis”. Break-even refers to the point at which income just equals expenses. Both income and expenses are plotted versus the production capacity. The resulting profit is usually plotted in the same graph. Figure 4.15 represents an exemplary break-even plot. Each curve could be plotted for various values of a factor of interest (e.g., time) to show its effect on the break-even points. All these concepts are explained in detail in the applications section (Chapters 7–9).

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Chapter 4

30

Annual income/expenses (M$/y)

25

Sales

Lower

20

break-even point

Manufacturing

15

cost

10

Upper break-even point Maximum

5

profit Profit

0 0

500

1000

1500

2000

2500

Annual operating time (h/y)

Figure 4.15 Break-even analysis.

The factors which are included in a sensitivity analysis are divided into two categories: • Design variables, (also called and decision variables or independent variables); and • Technical and economic data Practically, the design variables can be assigned to any value into a feasible range, while data get values from uncontrolled external factors. Thus, two critical points arise:

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Process Engineering Economics

• •

81

To calculate the optimal values of the design variables to optimize profitability; and To take into account the uncertainty of the data on the profitability

The first point refers to “plant optimization” (also called “economic balance”), while the second point refers to “risk analysis”. NOMENCLATURE

APR Ceq CF CL CLab CM CMat CMF CMV Co COver CPack CS CT CTR CUtil CW d DPB e fL fLab fMat fMF fOver fPack fUtil fWF fWS i IRR

t/y M$ M$ $/h M$/y M$ M$/y M$/y M$/y M$ M$/y M$/y M$/y M$ M$/y M$ y -

Annual Product Rate Purchased Equipment Cost Fixed Capital Cost Labor Rate Cost Labor Cost Manufacturing Cost Raw Materials Cost Fixed Manufacturing Cost Variable Manufacturing Cost Own Capital Overhead Cost Packaging Cost Sales Income Total Capital Cost Capital to Turnover Ratio Utilities Cost Working Capital Cost Depreciation Rate Discounted Payback Period Capital Recovery Factor Lang Factor Labor Cost Correction Factor Material Cost Correction Factor Fixed Manufacturing Cost Factor Overhead Cost Factor Packaging Cost Correction Factor Utilities Cost Correction actor Working Capital Factor Working Capital Factor Discount Rate Internal Rate of Return

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82

L Ln Lx M N NPV P PG PN PR ROI S SPB t TAC TCR Tx t tc

Chapter 4

M$ M$/y persons y M$ M$/y M$/y M$/y t/h M$/y y M$/y M$/y h/y y

Leverage Loan Loan Payment Manpower Lifetime Net Present Value Profit Gross Profit Net Profit Product Rate Return On Investment Annual sales Simple Payback Period Tax Rate Total Annualized Cost Turnover to Capital Ratio Taxes Annual Operating Time Collection period

REFERENCES Bartholomai A, 1987. Food Factories–Processes, Equipment, Costs. VCH Publications. Brennan D, 1998. Process Engineering Economics. IChemE. Brown T, 2007. Engineering Economics and Economic Design for Process Engineers. CRC Press. Chilton CH, 1960. Cost Engineering in the Process Industries. McGraw-Hill. Clark JP, 1997. Cost and profitability estimation. In: Handbook of Food Engineering Practice, CRC Press. Couper JR, 2003. Process Engineering Economics. Marcel Dekker. Holland FA, Wilkinson JK, 1997. Process Economics. In: Perry RH, Green DW, Maloney JO, Perry’s Chemical Engineers’ Handbook, 7th Edition, McGraw-Hill. Marouli AZ, Maroulis ZB, 2005. Cost data analysis for the food industry. Journal of Food Engineering, 67(1)289–299. Maroulis ZB, Saravacos GD, 2003. Food Process Design. Marcel Dekker. Moresi M, 1984. Economic study of concentrated citrus juice production. In McKenna B ed, Engineering and Food. Elsevier. Peters MS, Timmerhaus KD, West RE, 2003. Plant Design and Economics for Chemical Engineers, 5th edition. McGraw-Hill. Seider WD, Seader JD, Lewin DR, 1999. Process Design Principles. John Wiley. Sinnot RK, 1996. Chemical process design. In: Coulson JM and Richardson, JF, eds, Chemical Engineering, Butterworth-Heinemann.

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5 Capital Cost of Food Plants

I. INTRODUCTION As described in Chapter 4, most of the methods of estimating the fixed capital cost are based on the cost of process equipment. In this chapter the methods of estimating the process equipment cost are presented: • Quotations from fabricators • Methods based on cost versus capacity equations • Past purchase records updated with appropriate cost indices 1. Unit Operations in Food Processing The basic Unit Operations of Chemical Engineering, i.e., Fluid Flow, Heat Transfer, and Mass Transfer, have been applied to the food processing industry for many years. The theory on these operations was developed originally for gases and liquids (Newtonian fluids), but in food processing (or food manufacturing) non-Newtonian fluids, semi-solid and solid food materials are handled, and adaptation or extension of the theory is necessary (Maroulis and Saravacos, 2003). Some food processing operations, dealing with such complex materials are still treated empirically, using rules, practices, and equipment developed through experience (Brennan et al., 1991). Generalized models of unit operations are useful in preliminary design. Many specialized unit operations have been developed in the food processing industry, and more than 150 such food processing operations were listed by Farkas (1977, 1980). The unit operations of food processing can be classified on the basis of the processing equipment, and typical examples are shown in Table 5.1 (Saravacos and Kostaropoulos, 2002). 83

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Mechanical processing and mechanical separation operations are very important in most food process industries, dealing with fluid, semi-fluid, and solid food materials. Some of them have been developed empirically for the processing of specific foods and they require specialized equipment. Some mechanical equipment has been adapted from the chemical process industry, using suitable construction materials, such as stainless steel, and hygienic (sanitary) design to protect the quality and safety of the food products. Mechanical transport operations include pumping of liquids, pneumatic and hydraulic transport, and mechanical conveying. Pumping can be modeled and simulated, based on the principles of Fluid Flow and the Rheology of fluid food materials. However, the other mechanical transport operations are based on empirical rules and specialized equipment, developed through experience of manufacturers of equipment and industrial food processors. Modeling and simulation of mechanical processing operations is difficult, and empirical rules and equations are generally used. Size reduction, agglomeration, mixing, and extrusion, developed in the chemical process industries, are adapted and applied to various food processes. Sorting, grading, peeling, slicing, expression, and forming require specialized equipment, which has been developed for the various food products and processes (Saravacos and Kostaropoulos, 2002). Chemical Engineering mechanical separations, such as screening, filtration, and centrifugation, have been adapted from the chemical process industries in various food industries. Cleaning and washing are empirical operations, using specialized equipment, developed for specific food raw materials. Most of the heat and mass transfer processes used in food processing can be modeled and simulated, using established techniques of Chemical Engineering (Maroulis and Saravacos, 2003). Novel nonthermal preservation methods, e.g., irradiation and high pressure processing, are still in the development stage, and economic processing equipment is not available. Food packaging operations and equipment are highly specialized, and they are difficult to model and simulate. Packaging equipment is expensive and its selection is based on the specific food product and food package. A practical description of the unit operations, used in the processing of fruits and vegetables, was presented by Gould (1996). Fruit and vegetable processing is a large industry, consisting of a large number of small to mediumsized processing plants, producing several diverse food products. These plants utilize several mechanical unit operations, since the materials being processed are solid or semi-solids, sensitive to mechanical and thermal processing. Some large food processing industries such as the dairy, edible oil, milling, and beer industries process large amounts of fewer products, utilizing a smaller number of conventional unit operations. The scale-up methods, used extensively in Chemical Engineering, are difficult to apply to food processing operations, due to insufficient physical

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property data, and the complex physical, chemical and biological changes in the food systems. Pilot plant data, collected under similar processing conditions, are necessary for scale-up of industrial operations of complex food processes, such as extrusion cooking of starch-based foods (Valentas et al., 1991), or processing of new foods. The pilot plant is useful in evaluating new food processes, and in testing new processing equipment under industrial operating conditions. It is often used for the production of large samples of new food products, used in storage and marketing tests. 2. Mechanical Processes Mechanical processing operations include mechanical transport of food materials, mechanical processing, and mechanical separations. Mechanical transport includes pumping and mechanical conveyors; mechanical processing is concerned with size reduction, agglomeration, mixing, and forming; and mechanical separations involve filtration, centrifugation, expression, removal of food parts, and cleaning (Table 5.2). Mechanical operations are based on equipment, specific for various processes, developed mostly from experience of equipment manufacturers and users in the chemical and food processing industries. Some empirical equations are applied to specific processes and equipment, but rigorous mathematical modeling and simulation of the mechanical processes is not feasible, except for pumping of fluids, which is based on Fluid Flow and Rheology. Description of mechanical processing equipment, in general, is found in Perry and Green (1997), Walas (1988), and Bhatia (1979-1983), while equipment used in food processing is described by Saravacos and Kostaropoulos (2002). Details of mechanical equipment can be found in bulletins and catalogs of manufacturers and suppliers of processing equipment. Lists of directories of equipment suppliers are given by Saravacos and Kostaropoulos (2002). The equipment used in mechanical processing of foods must comply with the principles of hygienic (sanitary) design and operation. The equipment surfaces coming into contact with food materials should be made of corrosionresistant stainless steel, and should be cleanable with the cleaning in place (CIP) system (Jowitt, 1980; Troller, 1993). a. Mechanical Transport Operations Liquid and semi-fluid foods are transported in food processing plants using various types of pumps, while food particles (powders) and grains are transported by pneumatic conveyors. Hydraulic conveying is used for large food pieces, while various types of mechanical conveyors are used for solid foods, food packages and containers.

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i. Transport of Fluid Foods Rheological data are required for the design of pumping of fluid foods in piping systems. Most fluid foods are non-Newtonian fluids (Saravacos and Maroulis, 2001), and the power-law model yields useful parameters for the estimation of the Reynolds number, the pressure drop, and the energy requirements (Bernoulli equation). Friction losses in pipes and fittings are estimated using empirical equations of fluid flow (Holland and Bragg, 1995; Saravacos and Kostaropoulos, 2002). The design of most food processes is concerned mainly with heat and mass transfer operations, and the equipment required to carry out these important operations, e.g., sterilizers, evaporators, and dryers. Transport of food materials is considered an auxiliary operation, which is carried out with empirically designed specialized equipment (pumps, piping, and valves). Table 5.2 shows some important fluid transport equipment used in food processing (Maroulis and Saravacos, 2003). ii. Mechanical Conveyors Several types of mechanical conveyors are used in transporting solid foods, food packages, and containers. Typical units are listed in Table 5.2. b. Mechanical Processing Operations Mechanical processing equipment, used in chemical and mineral processing, such as grinders, mills, agglomerators, and mixers, has been adapted to food processing. Specialized equipment, such as homogenizers, paste and dough mixers, and forming/extrusion, have been developed by equipment manufacturers for specific food processes and products. Some typical mechanical processes, used in food processing, are shown in Table 5.2. c. Mechanical Separation Operations A wide range of mechanical separation equipment is used in food processing. Some basic equipment, such as screens, filters, centrifuges, and cyclones, are adapted from the chemical process industry. Specialized equipment, such as sorters, peelers, and juice extractors, have been developed for specific food processes and food products. A list of mechanical separation equipment is shown in Table 5.2. 3. Food Packaging Processes Food Packaging is highly dependent on packaging equipment and packaging materials, empirically developed by manufacturers. Specialized equipment is used for container preparation, product filling and closing, and aseptic packaging of foods (Kostaropoulos and Saravacos, 2002). Table 5.3 summarizes the main equipment used in Food Packaging.

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87

Table 5.1 Classification of Unit Operations of Food Processing Group of Operations

Typical Food Processing Operations

Mechanical Transport

Pumping of Fluids Pneumatic Conveying Hydraulic Conveying Mechanical Conveying

Mechanical Processing

Peeling Cutting Slicing Size Reduction Sorting Grading Mixing Emulsification Agglomeration Extrusion Forming

Mechanical Separations

Screening Cleaning Washing Filtration Mechanical Expression Centrifugation

Heat Transfer Operations

Heating Blanching Cooking Frying Pasteurization Sterilization Evaporation Cooling Freezing Thawing

Mass Transfer Operations

Drying Extraction Distillation Absorption Adsorption Crystallization from Solution Ion Exchange

Membrane Separations

Ultrafiltration Reverse Osmosis

Nonthermal Preservation

Irradiation High Pressure Pulsed Electric Fields

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Table 5.2 Mechanical Processes in Food Processing Equipment Applications Fluid Transport Pumps Centrifugal Radial, axial flow Positive Displacement Lobe, gear, piston, progressive cavity Pneumatic Conveyors Hydraulic Conveyors Mechanical Conveyors Belt Conveyors Roll Conveyors Screw Conveyors Chain Conveyors Bucket Elevators

Low viscosity fluids Dilute suspensions Viscous, sensitive fluids and pastes Particles and grains suspended in air Fruits and vegetables suspended in water Particles, pieces, packages Packages, heavy products Pastes, grains Containers Particles, grains

Mechanical Processing Operations Cutting Equipment Fruits / vegetables Slicers, dicers Meat Grinders Roll mills, hammer mills, Cereal grains disc grinders, pulpers Fruits / vegetable, meat Agglomerators Rotary pan, drum Food granules from Fluidized-bed, drying food powders Compression, palletizing Food pellets Homogenizers Milk products Pressure, colloid mills Food emulsions Mixers Liquid/liquid Agitated tanks liquid/solid mixers of solids Solid/solid Forming/Extrusion Equipment Forming extruders Forming of cereal foods Twin extrusion cookers Extrusion cooked products

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Capital Cost of Food Plants

Table 5.2 Continued Equipment

89

Applications

Mechanical Separations Screens Sieving equipment Food particles, flour Sorters Sizing of fruits Filters Cake filters, frame, Fruit juices, wine vacuum, depth filters water, air Centrifuges Centrifugal separators Milk, vegetable oil filtering centrifuges, decanters fruit juices Cyclone Separators Particles / air Mechanical Expression Expression equipment, Vegetable oil Screw presses, juice extractorsfruit juices Removal of Food Parts Peeling, pitting Fruit products Skinning equipment animal products Removal of External Parts Fruit/vegetables Wet cleaners, air cleaners grain cleaning Table 5.3 Food Packaging Equipment Container Preparation Metal, glass, plastic, paper Filling Equipment Dosing, weighing, valves Closing Equipment Metallic containers, glass closures Plastic containers, cartons and cardboard Aseptic Packaging Form-fill-seal equipment Monoblock, combiblock systems Group Packaging Wrapping Palletizing

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Chapter 5

II. QUOTATIONS FROM FABRICATORS The most accurate cost estimation for process equipment is to obtain a price quotation from a reliable manufacturer or supplier (vendor) of equipment. Specification sheets for each process unit should be prepared for the equipment, which should contain basic design data, materials of construction, and special information that will help the supplier to provide the appropriate equipment (Walas, 1988). Standardized equipment is preferred because of lower cost and faster delivery. It should be noted that very strict and detailed specifications could increase substantially the price of the equipment, while an available “off-theshelf” unit at a lower cost might be satisfactory. Second-hand equipment at a lower cost may, in some cases, be satisfactory for the intended application. Suppliers of processing equipment are found in various directories and in international equipment fairs. Table 5.4 presents the web sites of selected food process equipment suppliers.

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

91

Table 5.4 Web Sites of Selected Food Processing Equipment 1. Mechanical Processing Equipment a. Bulk storage of raw materials and products Vebe Technik www.webe-technik.se b. Fruit / vegetable preparation and expression FMC FoodTech www.fmctechnologies.com Urschel www.urschel.com Bucher-Guyer www.bucherguyer.ch/foodtech Pieralisi www.pieralisi.com Turatti www.turatti.com c. Dairy processing equipment APV Alfa Laval

www.apv.com www.alfalaval.com

2. Heating / Cooling Equipment a. Sterilizers / Pasteurizers / Blanchers Alfa Laval www.alfalaval.com APV www.apv.com FMC Corporation www.fmc.com Rossi & Catelli www.cftrossicatelli.com Cabinplant International www.cabinplant.com b. Freezing equipment Frigoscandia GEA

www.frigoscandia.com www.geaag.com

c. Baking Equipment APV APV Baker

www.apv.com www.apvbaker.com

3. Packaging Equipment Angelus Can R. Bosch Delaval (Tetrapak) FranRica Sidel Universal Filling Machine Co

www.angeluscan.com www.boschpackging.com www.delaval.com www.fmc.com www.sidel.com www.universalfilling.com

Data from Saravacos and Kostaropoulos (2002).

© 2008 by Taylor & Francis Group, LLC

92

Chapter 5

III. EQUIPMENT COST ESTIMATION When approximate cost data are required for preliminary design, empirical methods and rules are used, which will yield fast results within the accepted accuracy (Chilton, 1960). A popular method is to use the Guthrie charts of equipment cost versus capacity (Guthrie, 1969; Peters and Timmerhaus, 2003; Perry and Green, 1997; Douglas, 1988). Plotted on log-log scales, the Guthrie charts show straight lines. These charts are represented by the generalized costcapacity Guthrie equation (Maroulis and Saravacos, 2003):

⎛ A⎞ C = Co ⎜⎜ ⎟⎟ ⎝ Ao ⎠

n

(5-1)

where C and Co are the equipment costs (e.g., USD=$) at equipment capacities A and Ao (e.g., kg/h), respectively. The scale index (cost exponent) n varies with the type of equipment over the range 0.5 to 1.0, and it is often taken approximately as n=2/3. The “2/3” factor is related to the cost of spherical vessels: C=kV2/3, where V is the vessel volume and k is a constant (Biegler et al., 1997). Exponent values near n=1 are characteristic of complex mechanical or electrical units, such as motors, compressors, homogenizers, and distillation columns. In food processing, the scale index n=1 may be used for individual complex units, such as packaging machines and sterilizers. Low values near n=0.5 characterize large processing units, such as evaporators, heat exchangers, and tanks. Typical data on the unit cost and the scale index for various equipment are given in the cost diagrams (Figure 5.3) of this chapter. To take into account the effect of inflation, material of construction, and operating pressure, Equation (5-1) is modified to Equation (5-2):

⎛ A C = f I f M f P Co ⎜⎜ ⎝ Ao

⎞ ⎟⎟ ⎠

n

(5-2)

where the correction factors for inflation fI , material fM, and pressure fP are discussed in the following paragraphs.

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

93

1. Effect of Material of Construction The correction factor for a material of composite construction fM described by Equation (5-2) is estimated from the following equation:

fM = ε

CM CCS

(5-3)

where CM is the cost of material M in $/kg, CCS is the carbon steel cost in $/kg, and ε is the portion of the material M in the equipment construction, varying from 0.4 for clad construction to 0.6 for solid construction. An indication of the relative cost of some commonly used materials is given in Table 5.5. Table 5.5 Relative Cost of Some Commonly Used Construction Materials Carbon steel Low alloy steels (Cr-Mo) Nickel steel (9%) Stainless Steel 304 Stainless Steel 321 Stainless Steel 316 Stainless Steel 310 Stainless Steel High Ni Copper Aluminum Nickel Monel Titanium

© 2008 by Taylor & Francis Group, LLC

1 2 2.5 5 5.5 8 10 20 2.5 3 10 9 60

94

Chapter 5

2. Effect of Pressure on Equipment Cost The correction factor for pressure fP described by Equation (5-4) is estimated from the following equation:

⎛ P −1⎞ f P = exp⎜ ⎟ ⎝ 75 ⎠

(5-4)

The correction factor of empirical equation (5-4) for pressure 1-70 bar comes from fitting exponential equations to data presented by Biegler et al. (1997). Figure 5.1 shows the effect of pressure on the cost factor fP (Maroulis and Saravacos, 2003). The pressure correction factor may be used at pressures up to 70 bar, but not at the very high pressures of supercritical fluid extraction (about 300 bar) or the ultrahigh pressures of high-pressure food processing (1-8 kbar). 3

2

fP

1

0 0

25

P (bar)

50

Figure 5.1 Equipment cost correction factor for pressure.

© 2008 by Taylor & Francis Group, LLC

75

Capital Cost of Food Plants

95

3. Effect of Inflation on Equipment Cost

The cost of processing equipment at a given time can be estimated by multiplying the known cost of the equipment at a past time by the ratio of an appropriate index, corresponding to the same time points. The correction factor for inflation fI described by Equation (5-2) is defined by the following equation (Maroulis and Saravacos, 2003): ⎛M &S⎞ ⎛ CEP ⎞ fI = ⎜ ⎟ or ⎜ ⎟ 1100 ⎝ ⎠ ⎝ 400 ⎠

(5-5)

where M&S and CEP are the two common engineering indices in the process industries: a) The Marshall and Swift Equipment Index (M&S) (formerly Marshal and Stevens Index), published periodically in the journal “Chemical Engineering”, is the weighted average of the cost of equipment of 8 chemical process industries (chemicals, petroleum, paper, rubber, paint, glass, cement, and clay products). The M&S all-industry index is the arithmetic average of indices for 47 different industrial, commercial, and housing equipment. The M&S allindustry index is about 2% lower than the M&S equipment, and it is used in this book. The base year of both M&S indices is 1926 (= 100). b) The Chemical Engineering Plant Cost Index (CEP) shows construction costs for processing plants. It consists of the weighted average of four major components: equipment, machinery and supports; erection and installation labor; buildings materials and labor; engineering; and supervision. The major component, equipment, consists of fabricated equipment; process machinery; pipe, valves, and fittings; process instruments and controls; pumps and compressors; electrical equipment and materials; and structural supports, insulation, and paint. The base year of the CEP cost index is 1957–1959 (=100). Both M&S and CEP cost indices are used in process and plant design, giving similar results. Table 5.6 and Figure 5.2 show the cost indices M&S (allindustry) and CEP during the period 1977–2006. These data can be extrapolated to the near future using linear regression equations fitted to recent years. The following simplified equations are also presented in Figure 5.2. CEP = 480 + 10 (Year-2005)

(5-6)

M&S = 1250 + 25 (Year-2005)

(5-7)

The increases of the cost indices are caused by inflation and rises in the prices of certain expensive materials, e.g., stainless steel. The sharp increase of the cost indices during the decade 1970–1980 is mainly due to the rising costs of energy (world-wide petroleum crisis).

© 2008 by Taylor & Francis Group, LLC

96

Chapter 5

Table 5.6 CEP and M&S Cost Indices YEAR

CEP

M&S

1976

192

479

1977

204

514

1978

219

552

1979

239

607

1980

261

675

1981

297

745

1982

314

774

1983

317

786

1984

323

806

1985

325

813

1986

318

817

1987

324

814

1988

343

852

1989

355

895

1990

358

915

1991

361

931

1992

358

943

1993

359

964

1994

368

993

1995

381

1028

1996

382

1039

1997

387

1057

1998

390

1062

1999

391

1068

2000

394

1089

2001

394

1094

2002

396

1104

2003

402

1124

2004

444

1179

2005

457

1261

2006

510

1340

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

97

1600

1400

M&S 1200

Cost Index

1000

800

600

CEP 400

200

0 1975

1980

1985

1990

1995

2000

2005

2010

Calendar Year

Figure 5.2 Marshal and Swift all-industry equipment (M&S) and chemical engineering plant (CEP) cost indices in the period 1977–2006.

© 2008 by Taylor & Francis Group, LLC

98

Chapter 5

IV. DATA FOR PRELIMINARY EQUIPMENT COST ESTIMATION

Figure 5.3 plots the cost equation (Equation 5-1) for various chemical and food engineering processes, classified in suitable categories. The parameter estimates for the cost equation are also tabulated along with the application range. These results come from fitting the cost equation to various data extracted from the literature. That is, data from Ulrich (1984), Gerrard (1988), Garrett (1989), Walas (1988), and mostly from the recent edition of Peters and Timmerhaus (2003) were selected, updated, screened, and used in a regression analysis procedure to obtain the results shown in Figure 5.3. Table 5.7 summarizes these results while Figure 5.4 presents the flowsheet symbols for the examined equipment. These cost data are also incorporated in an Excel file named “Equipment Cost” included in the accompanying CD-ROM. The user can select a process category or a single process by pull down menus. New data can be introduced easily. Most food engineering processes require some type of special equipment, developed empirically in the food industry and supplied by equipment manufacturers. The cost of such equipment varies according to its complexity and capacity. Some equipment may be expensive due to the materials of construction (usually stainless steel) and the strict hygienic (sanitary) requirements. The scale index of special food equipment is usually near 1, i.e. more similar units are used for increased capacity. Most of the special food processing equipment is classified mechanical processing or packaging equipment (Tables 5.2 and 5.3), for example, washing machines and packaging systems (Saravacos and Kostaropoulos, 2002). Price quotations from manufacturers and suppliers of special food processing equipment are necessary for the design and economic analysis of food plants. Such equipment is specified for capacity (kg/h or t/h) and material of construction. Table 5.8 and Figure 5.5 list cost data of some typical mechanical processing and packaging equipment, which can be used in the application examples of food processing plants of this book (Chapters 7 and 8). The web sites of suppliers of selected food processing equipment are given in Table 5.4.

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

99

10000

Fluids transport

1000 Compressor

Cost (k$)

Pump

Electric motor

100 Fan Agitator

10

1 0.1

1

10

100

1000

10000

Power (kW) Equipment

Unit Cost (k$)

Scale Index

Min Size

Max Size

1

Electric motor

1

0.67

1

1000

2

Agitator

4

0.55

1

100

3

Compressor

5

0.8

5

500

4

Pump

5

0.6

4

700

5

Fan

1

0.8

10

200

6 7

Figure 5.3 Cost of Equipment.

© 2008 by Taylor & Francis Group, LLC

100

Chapter 5

10000

Vessels

1000

Agitated jacketed reactor

Process vessel

Cost (k$)

Storage tank

100

Silo

10

1 0.1

1

10

100

1000

10000

Volume (m3) Equipment

Unit Cost (k$)

Scale Index

Min Size

1

Silo

2

0.55

10

Max Size 200

2

Storage tank

5

0.45

5

5000

3

Process vessel

10

0.5

1

1000

4

Agitated jacketed reactor

50

0.6

1

100

5 6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

101

10000

Conveyor belts Belt freezer 1000

Belt dryer Belt washer

Cost (k$)

Conveyor belt 100

10

1 0.1

1

10

100

1000

10000

Area (m2) Equipment

Unit Cost (k$)

Scale Index

Min Size

Max Size

1

Conveyor belt

2

1

1

100

2

Belt washer

5

1

1

100

3

Belt dryer

10

0.95

1

100

4

Belt freezer

20

0.95

1

100

5 6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

102

Chapter 5

10000

Forced circulation evaporator

Heat exchangers

Tubular evaporator 1000 Plate heat exchanger Shell and tubes heat

Cost (k$)

enchanger

Scraped surface heat

100

exchanger

10

1 0.1

1

10

100

1000

10000

Area (m2) Equipment

Unit Cost (k$)

Scale Index

Min Size

1

Scraped surface heat exchanger

5

0.95

2

Max Size 20

2

Shell and tubes heat enchanger

3

0.65

1

1000 1500

3

Plate heat exchanger

7

0.6

10

4

Tubular evaporator

20

0.7

5

500

5

Forced circulation evaporator

100

0.7

5

500

6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

103

10000

Dryers Vibratory conveyor dryer Fluidized bed dryer

1000

Cost (k$)

Rotary dryer

100

Tray dryer

10

1 0.1

1

10

100

1000

10000

Area (m2) Equipment

Unit Cost (k$)

Scale Index

Min Size

1

Tray dryer

10

0.45

1

Max Size 100

2

Vibratory conveyor dryer

50

0.67

1

300

3

Rotary dryer

5

0.85

2

100

4

Fluidized bed dryer

20

0.57

1

1000

5 6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

104

Chapter 5

10000

Filters

Cost (k$)

1000

Vacuum drum filter Vibrating screen

100

Plate filter

10

1 0.1

1

10

100

1000

10000

Area (m2) Equipment

Unit Cost (k$)

Scale Index

Min Size

1

Vacuum drum filter

40

0.6

0.5

10

2

Plate filter

3

0.75

1

100

3

Vibrating screen

15

0.85

1

10

4 5 6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

Max Size

Capital Cost of Food Plants

105

10000

Size reduction

Crusher

1000 Ball mill

Cost (k$)

Grinder

Cutter

100

10

1 0.1

1

10

100

1000

10000

Capacity (kg/s) Equipment

Unit Cost (k$)

Scale Index

Min Size

1

Cutter

10

0.65

1

100

2

Crusher

40

0.67

1

1000

3

Grinder

52

0.59

0.2

10

4

Ball mill

200

0.45

0.2

10

5 6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

Max Size

106

Chapter 5

10000

Packaging equipment

Mechanical processing Centrifuge 1000

Cost (k$)

Extruder Screw press

100

10

1 0.1

1

10

100

1000

10000

Capacity (kg/s) Equipment

Unit Cost (k$)

Scale Index

Min Size

Max Size

1

Centrifuge

300

0.55

1

20

2

Screw press

120

0.45

0.01

1

3

Extruder

200

0.25

0.01

0.5

4

Packaging equipment

360

0.67

0.1

100

5 6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

107

10000

Utilities

Boiler Turbine

Cost (k$)

1000

100

10

1 0.1

1

10

100

1000

10000

Power (MW) Equipment

Unit Cost (k$)

Scale Index

Min Size

1

Turbine

750

0.6

0.1

5

2

Boiler

10

0.95

1

500

3 4 5 6 7

Figure 5.3 Continued.

© 2008 by Taylor & Francis Group, LLC

Max Size

108

Chapter 5

Table 5.7 Unit Cost and Scale Index of Miscellaneous Process Equipment Equipment

SizeUnits

UnitCost, k$

ScaleIndex

MinSize

MaxSize Operators

Vessels Silo

Volume (m3)

2

0.55

10

200

Storage tank

Volume (m3)

5

0.45

5

5000

0.10 0.10

Process vessel

Volume (m3)

10

0.50

1

1000

0.20

Agitated jacketed reactor

Volume (m3)

50

0.60

1

100

1.00 0.10

Fluids transport Electric motor

Power (kW)

1

0.67

1

1000

Agitator

Power (kW)

4

0.55

1

100

0.10

Compressor

Power (kW)

5

0.80

5

500

0.50

Pump

Power (kW)

5

0.60

4

700

0.10

Fan

Power (kW)

1

0.80

10

200

0.10

Conveyor belt

Area (m2)

2

1.00

1

100

0.10

Belt washer

Area (m2)

5

1.00

1

100

0.50

Belt dryer

Area (m2)

10

0.95

1

100

1.00

Belt freezer

Area (m2)

20

0.95

1

100

1.00

Scraped surface heat exchanger

Area (m2)

5

0.95

2

20

1.00

Shell and tubes heat enchanger

Area (m2)

3

0.65

1

1000

0.50

Plate heat exchanger

Area (m2)

7

0.60

10

1500

1.00

Tubular evaporator

Area (m2)

20

0.70

5

500

1.00

Forced circulation evaporator

Area (m2)

100

0.70

5

500

1.00

Vacuum drum filter

Area (m2)

40

0.60

0.5

10

1.00

Plate filter

Area (m2)

3

0.75

1

100

1.00

Vibrating screen

Area (m2)

15

0.85

1

10

0.50

Conveyor belts

Heat exchangers

Filters

Dryers Tray dryer

Area (m2)

10

0.45

1

100

1.00

Vibratory conveyor dryer

Area (m2)

50

0.67

1

300

1.00

Rotary dryer

Area (m2)

5

0.85

2

100

1.00

Fluidized bed dryer

Volume (m3)

20

0.57

1

1000

1.00 1.00

Size reduction Cutter

Capacity (kg/s)

10

0.65

1

100

Crusher

Capacity (kg/s)

40

0.67

1

1000

1.00

Grinder

Capacity (kg/s)

52

0.59

0

10

1.00

Ball mill

Capacity (kg/s)

200

0.45

0

10

1.00

Mechanical processing Centrifuge

Capacity (kg/s)

300

0.55

1

20

1.00

Screw press

Capacity (kg/s)

120

0.45

0.01

1

1.00

Extruder

Capacity (kg/s)

200

0.25

0.01

0.5

1.00

Packaging equipment

Capacity (kg/s)

360

0.67

0.1

100

1.00

Turbine

Power (MW)

750

0.60

0.1

5

1.00

Boiler

Power (MW)

10

0.95

1

500

1.00

.

.

Utilities

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants Vessels Silo

109

Fluids transport

Conveyor belts

Electric motor

Conveyor belt

R

R

P

P

Agitator

Storage tank

Belt washer W R

R

P

P

L

Process vessel

Compressor

Belt dryer

R

S R R

G

s

P

P

P

A

Agitated jacketed reactor

Pump

Belt freezer

R

Z z

S

R

s

R

P

P

P

Fan

R

P

Figure 5.4 Flowsheet symbols for miscellaneous process equipment.

© 2008 by Taylor & Francis Group, LLC

110

Chapter 5

Filters

Heat exchangers

Dryers

Vacuum drum filter

Scraped surface heat exchanger

Tray dryer

R

G

S

P R S

R

P

Plate filter

A

s

s

P

Shell and tubes heat enchanger

P

Vibratory conveyor dryer S

S R

P

s

R R

G

P

P s

Vibrating screen

Rotary dryer S

R

P

A

Plate heat exchanger

R

R

F

G

P

P s

A

P

P

Tubular evaporator

Fluidized bed dryer G

S

R

B

s F R

P

Forced circulation evaporator

B

S s R

Figure 5.4 Continued.

© 2008 by Taylor & Francis Group, LLC

P

A

P

Capital Cost of Food Plants

111

Size reduction

Mechanical processing

Utilities

Cutter

Centrifuge

Turbine

R

R

R

P P

P P

Crusher

Screw press R

Boiler R

G F

P

P

Grinder

A

Extruder R

R

P P

Ball mill

Packaging equipment R

R

K P

Figure 5.4 Continued.

© 2008 by Taylor & Francis Group, LLC

P

S

s

112

Chapter 5 List of Equipment

Nomenclature

Vessels Silo Storage tank Process vessel Agitated jacketed reactor Fluids transport Electric motor Agitator Compressor Pump Fan Conveyor belts Conveyor belt Belt washer Belt dryer Belt freezer Heat exchangers Scraped surface heat exchanger Shell and tubes heat enchanger Plate heat exchanger Tubular evaporator Forced circulation evaporator Filters Vacuum drum filter Plate filter Vibrating screen Dryers Tray dryer Vibratory conveyor dryer Rotary dryer Fluidized bed dryer Size reduction Cutter Crusher Grinder Ball mill Mechanical processing Centrifuge Screw press Extruder Packaging equipment Utilities Turbine Boiler

System input streams

Figure 5.4 Continued.

© 2008 by Taylor & Francis Group, LLC

R

Raw material

K

Packaging material

X

Auxiliar material

F

Fuel

W

Process water

A

Ambient air

System internal recycled streams S

Steam

s

Steam condensate

C

Cooling water

c

Cooling water return

Z

Refrigerant

z

Refrigerant return

M

Compressed air

System output streams P

Product

B

Byproduct

L

Liquid waste

G

Gas waste

Capital Cost of Food Plants

113

Table 5.8 Food Processing Equipment Cost t

t/h

k$

1. Mechanical Processing Equipment

a. Storage of raw materials and products Fluid milk tanks Flour bins Sugar silos Wine fermentation tanks Wine storage tanks

100 50 5000 40 150

100 50 200 50 100

b. Fruit/vegetable preparation Fruit/vegetable unloader Fruit/vegetable washing machine Fruit/vegetable inspection belt Fruit/vegetable sorter/sizer Fruit pitting machine (peaches, apricots) Fruit/vegetable peeler (steam, lye) Pea preparation machine Green bean cutting machine

20.0 10.0 10.0 10.0 5.00 5.00 5.00 5.00

50 50 30 50 100 100 100 100

5.00 10.0 10.0

30 80 80 150 100 100

5.00 5.00

150 250

c. Juice expression/extraction Orange juice extractor Orange/tomato juice finisher Tomato pulper Peel oil expression/recovery Grape crusher/destemmer Grape screw press

d. Dairy processing equipment Centrifuge Homogenizer

© 2008 by Taylor & Francis Group, LLC

114

Chapter 5

Table 5.8 Continued t

t/h

k$

1.26 5.00 5.00

500 200 300

2.00 2.00

250 300

1.00 1.00 1.00 3.00

2. Thermal processing equipment Rotary cooker/cooler Vegetable blancher Bread baking tunnel oven

1500 cans/h

0.84 L

3. Freezing equipment Belt freezer Fluidized bed freezer 4. Bread baking equipment Mixing tanks Fermentation tanks Dough kneading tanks Dough dividers/rounders Pre-proofing cabinet Bread moulders/ panners Conveyor belt proofer Conveyor belt oven De-panner/cooler Slicing machine Wrapping machine

5000 10000 10000 10000 5000 5000

pans/h pans/h pans/h pans/h loaves/h loaves/h

0.50 0.50 0.50 0.50 0.50 0.50

kg kg kg kg kg kg

2.50 5.00 5.00 5.00 2.50 2.50

75 125 150 60 30 50 200 300 50 40 50

1500 1000 25000 1500 1500 4000

cans/h cartons cups/h cans/h cans/h bottles/h

0.84 1.00 0.20 0.84 0.84 0.75

L L L L L L

1.26 1.00 5.00 1.26 1.26 3.00

250 400 800 50 30 250

2

5. Packaging Equipment Can seaming machine Aseptic packaging of milk Aseptic packaging of yogurt Can labeling machine Can casing machine Wine bottling machine

© 2008 by Taylor & Francis Group, LLC

Capital Cost of Food Plants

115

200

180

160

140

Cost (k$)

120

Fluid milk tanks

100

Wine storage tanks

80

Wine fermentation tanks

60

Flour bins 40 Pre-proofing cabinet 20

0 0

20

40

60

80

100

120

140

160

180

200

Capacity (t)

Figure 5.5a Food processing equipment cost: Storage of raw materials and products.

© 2008 by Taylor & Francis Group, LLC

116

Chapter 5

300

Homogenizer

250

Cost (k$)

200

Centrifuge

150

Pea preparation machine Fruit pitting machine (peaches, apricots)

100

Fruit/vegetable peeler (steam, lye)

Green bean cutting machine

Orange/tomato juice finisher Tomato pulper

Fruit/vegetable sorter/sizer

Fruit/vegetable washing machine

50

Orange juice extractor

Fruit/vegetable inspection belt

0 0

2

4

6

8

10

12

Capacity (t/h)

Figure 5.5b Food processing equipment cost: Fruit and vegetable processing.

© 2008 by Taylor & Francis Group, LLC

14

Capital Cost of Food Plants

117

600

Rotary cooker/cooler

500

Cost (k$)

400

Bread baking tunnel oven

Fluidized bed freezer

300

Belt freezer

Vegetable blancher

200

100

0 0

1

2

3

4

5

6

7

8

9

Capacity (t/h)

Figure 5.5c Food processing equipment cost: Thermal processing and freezing.

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10

118

Chapter 5

350

300

Conveyor belt oven

250

200 Cost (k$)

Conveyor belt proofer

150

Dough kneading tanks

Fermentation tanks

100

Mixing tanks Wrapping machine

50

Slicing machine

Dough dividers/rounders Bread moulders/ panners

De-panner/cooler

Pre-proofing cabinet

0 0

1

2

3

4

5

6

7

Capacity (t/h)

Figure 5.5d Food processing equipment cost: Bread baking.

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9

10

Capital Cost of Food Plants

119

1000

900

Aseptic packaging of yogurt

800

700

Cost (k$)

600

500

Aseptic packaging of milk

400

300 Can seaming machine Wine bottling machine 200

100

Can labeling machine Can casing machine

0 0

1

2

3

4

5

6

Capacity (t/h)

Figure 5.5e Food processing equipment cost: Packaging.

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7

8

9

10

120

Chapter 5

V. SHORT-CUT EQUIPMENT SIZING

Detailed design methods for the most common food processes are systematically presented by Maroulis and Saravacos (2003). Instead of these methods, short-cut process and plant design methods are adequate for preliminary sizing and cost estimating. For chemical processes short-cut design methods are presented in the literature, e.g., Douglas (1988), Walas (1990), Turton et al. (1998) [which presents the original data from Walas enhanced, updated, and transformed to the SI system], Branan (1998), Peters and Timmerhaus (2003). These references are used as a basis in constructing the procedures presented in the following paragraphs, which are suitable for food processes and plants. Simplified theoretical and empirical equations are presented for the design of selected chemical and food engineering equipment, as listed below: • Pumps and blowers • Compressors • Conveyor belts • Screw conveyors • Size reduction • Process vessels • Heat exchangers • Evaporators • Dryers • Filters • Sterilizers The design of special mass transfer equipment, applicable to food processing, such as distillation and membrane separations, is discussed by Saravacos and Kostaropoulos (2002) and Maroulis and Saravacos (2003). Food refrigeration and food packaging design is discussed by Saravacos and Kostaropoulos (2002). 1. Pumps and Blowers

The size of a pump or a blower (fan) is expressed by the electric power, which is approximately estimated by the equation: E=

F ΔP

ηρ

where E F

kW kg/s

Electric power Feed flow rate

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ΔP ρ η

kPa kg/m3 -

121

Pressure loss Fluid density Efficiency

Pump efficiency varies between 0.45 and 0.90 depending on the pump type. Blower efficiency varies between 0.60 and 0.85 depending on the blower type. Thus, minimum values should be used for more accurate estimation:

η = 0.45 for pumps η = 0.60 for blowers Special pumping conditions (velocity, shear rate, pressure) are necessary to avoid mechanical damage of the quality of food emulsions and suspensions. Positive displacement pumps are suitable for non-Newtonian food fluids. Centrifugal pumps are used in pumping Newtonian fluids, such as water, milk, and vegetable oils. Net positive suction head (NPSH) should be in the range of 1.5–6 m. Centrifugal pumps: capacity 1-30 L/s, max head 150 m Rotary pumps: capacity 0.06-30 L/s, max head 15 km Fans can raise the pressure up to 30 cm water, blowers up to 3 bar, and compressors to higher pressures. Vacuum pumps: rotary piston 0.001 Torr; 3-stage steam ejectors 1 Torr. 2. Compressors

The size of a compressor is expressed by the electric power, which is roughly estimated by the equation: E=

⎡⎛ P F C P T1 ⎢⎜⎜ 2 η ⎢⎝ P1 ⎣ 1

γ ⎤ ⎞ ⎟⎟ − 1⎥ ⎥ ⎠ ⎦

where E F T1 P1 P2 CP

γ η

kW kg/s K kPa kPa kJ/kgK -

Electric power Feed flow rate Input temperature Input pressure Output pressure Specific heat Polytropic coefficient Efficiency

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The polytropic coefficient varies from 0.40 for monatomic gases to 0.29 for diatomic and 0.23 for more complex gases. Compressor efficiency varies between 0.60 and 0.85 as the compression ratio is increased from 1.5 to 3. The following values are suggested for typical calculations:

γ = 0.29 η = 0.60 There are three main types of compressors: (1) reciprocating, (2) centrifugal, and (3) rotary. 3. Conveyor Belts

The size of a conveyor belt is calculated by the equation: A=

FL

(1 − ε ) ρ u z

where A F L D u z

ρ ε

m2 kg/s m m m/s m kg/m3 -

Belt area Feed flow rate Conveyor length Belt width Transport velocity Loading depth Particle density Void fraction of loading

Belt width from 0.35 to 2 m at velocities up to 5 m/s can be used. The loading void fraction depends on the particle shape and a typical value of 0.40 for spheres can be used. Thus, the following values are suggested for typical calculations: D=1m ε = 0.40 u = 1 m/s z = 0.10 m The required electric power is estimated by the equation:

E = kb g F L

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where E F L g kb

kW kg/s m m/s2 -

Electric power Feed flow rate Conveyor length Gravity acceleration Belt power coefficient

The belt power coefficient depends on the type of equipment. Typical value, kb = 0.2 g = 10 m/s2 Belt conveyors have lengths up to 100 m in a plant, but much longer outside. Inclination up to 30o. A 60 cm wide belt can carry 85 m3/h at a speed of 30 m/min. 4. Screw Conveyors

The size of a screw conveyor is calculated by the equation: A=

4 FL D(1 − ε ) ρ u

where m2 m kg/s m m/s kg/m3 -

A D F L u

ρ ε

Screw peripheral area Screw diameter Feed flow rate Conveyor length Transport velocity Particle density Void fraction of loading

The required electric power is estimated by the equation:

E = kS g F L where E

kW

Electric power

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F L g kS

Chapter 5

kg/s m m/s2 -

Feed flow rate Conveyor length Gravity acceleration Screw power coefficient

Screw conveyors may have lengths up to 50 m and inclination about 20o. A 30 cm diameter conveyor can handle 30–90 m3/h at speed 40–60 RPM. 5. Size Reduction

The following semitheoretical equation (Bond law) can be used for estimating the power required to form small particles from large feed particles: ⎛ 1 1 ⎞⎟ − E = kd w F ⎜ ⎜ D D1 ⎟⎠ 2 ⎝

where E F D1 D2 w kd

kW kg/s m m kJ/kg -

Electric power Feed flow rate Input particle size Output particle size Work index Size reduction power coefficient

The work index depends on the material hardness, while the size reduction power coefficient depends on the equipment type. The following typical values are proposed for preliminary design estimations: w = 40 kJ/kg kd = 0.01 Roll crushers (smooth or toothed) operate at speeds of 50–900 RPM with reduction ratios up to 4. Capacity is about 25% of the maximum, corresponding to a continuous ribbon of material passing through the rolls. Hammer mills are provided with screens, which use cutting edges for fibrous materials. Reduction ratios up to 40 may be achieved. Speed of large hammer mills 900 RPM, smaller units up to 16,000 RPM. 6. Vessels

The following equations calculate the required volume of a vessel when the residence time and the fluid flow rate are specified:

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A =π D L V=

π D2

4 ρV τ= F where V D L F

τ ρ

L

m3 m m kg/s s kg/m3

Vessel volume Vessel diameter Vessel length Feed flow rate Residence time Fluid density

When the vessel is agitated, the following equation calculates the required electrical power:

E = kG V kG = 2 where E kG

kW -

Electrical power required for agitation Power coefficient for agitation

Moreover, when heat is added or removed, the following additional equations should be taken into account:

Q = F C P (TR − T0 ) A=

Q U (TS − TR )

U = 1kW / m 2 K where Q T0

kW K

Thermal load Feed temperature

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126

TR TS U Cp

Chapter 5

K K kW/m2K kJ/kg K

Vessel temperature Hot utility temperature Overall heat transfer coefficient Food specific heat

It must also be noted that storage tanks: Volume < 5 m3 use vertical tanks on legs Volume 5–50 m3 use horizontal tank on concrete supports Volume > 50 m3 use vertical tanks on concrete foundations Use 10–15 % freeboard (top empty space) Capacity of storage tanks at least 1.5 times higher the size of transportation equipment, e.g., 30 m3 tank trucks and 100 m3 tank (railroad) cars. 7. Heat Exchangers

The following equations calculate the required heat transfer area of a typical heat exchanger:

Q = FH C pH (T2 H − T1H ) Q = FC C pC (T2C − T1C )

ΔTL =

(T1H − T1C ) − (T2 H − T2 C ) ln[(T1H − T1C 1 ) /(T2 H − T2C )]

Q = AUΔTL where FH FC T1H T2H T1C T2C ΔTL Q A U CpH CpC

kg/s kg/s o C o C o C o C o C kW m2 kW/m2K kJ/kg K kJ/kg K

Hot stream flow rate Cold stream flow rate Hot stream input temperature Hot stream output temperature Cold stream input temperature Cold stream output temperature Mean temperature difference Thermal load Heat transfer area Overall heat transfer coefficient Hot stream specific heat Cold stream specific heat

Systematic solutions of detailed mathematical models for complex heat exchangers are presented by Maroulis and Saravacos (2003).

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Shell and tube HE are operated countercurrently. Standard tubes 19 mm (3/4 in) OD, 5 m (16 ft) long. Shells of 305 mm (1 ft) diameter have a heat transfer area of about 10 m2; 600 mm (2 ft) diameter 40 m2; 900 mm (3 ft) 100 m2. Minimum temperature approach in HE, 10oC for water, 5oC for refrigerants. Cooling water inlet temperature 30oC; outlet 50oC. Double-pipe HE competitive at heat transfer surfaces < 20 m2. Plate-andfin (compact) HE have heat transfer area 1150 m2/m3, about 4 times the area per m3 than shell-and-tube units. Plate HE (stainless steel) are suitable for high hygienic services; they are about 40 % less expensive than equivalent shell-and-tube units. Applied overall heat transfer coefficients (U): water/liquid condensers 750 W/m2K; liquid/gas, gas/gas, 25 W/m2K. 8. Evaporators

The following simplified equations estimate the required thermal load, the operating average temperature difference, and the required heat transfer area per evaporator of an N-effect evaporator system in order to evaporate a given flow rate, when steam is available for heating and cold water for cooling. W ΔH S ηN TS − TC ΔT = N +1 Q A= U ΔT

Q=

where W

ΔHS

Q N

η ΔT

TS TC A U

kg/s kJ/kg kW K K K m2 kW/m2K

Solvent evaporating flow rate Latent heat of solvent vaporization The required thermal load per effect Number of evaporator units Thermal efficiency Operating average temperature difference Steam temperature Cooling water temperature Heat transfer area per evaporator effect Overall heat transfer coefficient

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Chapter 5

Systematic solutions of detailed mathematical models for N-effect evaporators under complex configurations are presented by Maroulis and Saravacos (2003). Long tube vertical evaporators (natural or forced circulation) are preferred in concentrating aqueous food solutions. Tube diameter 20–60 mm, tube length 3–9 m. Liquid velocity in forced circulation 4–6 m/s. Steam economy approximately 0.8N in an N-effect evaporator. Economic number of effects in the evaporation of sugar solutions 4–6. Efficiency of steam recompression 20–30%, mechanical recompression 70–75%. 9. Dryers

Continuous tray and belt dryers used for food pieces 3–15 mm require 10–200 min for drying. Rotary cylindrical dryers with air velocities of 2–10m/s require 5–90 min for drying. Holdup of solids 7–8%. Rotational speeds about 4 RPM. Pneumatic conveying dryers can dry particles 1–10mm. Dryer diameter 0.2–0.3 m, length up to 30m. Air velocities10–30 m/s. Residence time: single pass 0.5–3 s, normal recycling up to 60 s. Fluidized bed dryers used for particles up to 4 mm. Gas velocities twice the minimum fluidization velocity. Drying times: 1–2 min for continuous operation, up to 2 h for batch operation. Spray dryers can dry food particles in less than 60 s. Parallel flow air/ product is preferred. Length to diameter ratio of spray dryers: with spray nozzles 4–5, with spray wheels 0.5–1. Systematic solutions of detailed mathematical models for various types of dryers under complex configurations are presented by Maroulis and Saravacos (2003). Short cut sizing methods for belt and rotary dryers are presented in the following. In any case, the drying time of the material should be known and the examined dryer should ensure a residence time equal to the required drying time.

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Capital Cost of Food Plants

a. Belt dryer

A = DL (1 − ε )ρzA τ= F L u=

τ

E =k bg F L where m2 m m s kg/s m kg/m3 m/s kW m/s2 -

A D L

τ

F

ε z

ρ u E g kb

Belt area Belt width Belt length Residence time Drying material flow rate Void fraction of material loading Loading depth Drying material density Belt velocity Electrical power Gravity acceleration Power coefficient

b. Rotary dryer

V=

π D2

L 4 (1 − ε ) ρ V τ= F E = k r g N π D (1 − ε ) ρ V where D L V

m m m3

Dryer diameter Dryer length Dryer volume

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130

τ F

ε

N

ρ

E g kr

Chapter 5

s kg/s 1/s kg/m3 kW m/s2 -

Residence time Drying material flow rate Void fraction Rotating velocity Drying material density Electrical power Gravity acceleration Power coefficient

10. Filters

Continuous filtration is applicable if a 3 mm (1/8 inch) cake thickness is formed in less than 5 min. Rapid filtering: use belt or pusher-type centrifuges Medium filtering: use vacuum drums or discs Slow filtering: use pressure filters or sedimenting centrifuges For clarification of liquids without cake buildup use centrifuges, precoatdrum or sand filters. 11. Continuous Flow Sterilizers

Systematic solutions of detailed mathematical models for continuous flow sterilizers under complex configurations are presented by Maroulis and Saravacos (2003). The following equations can be used for short cut sizing of a continuous flow sterilizer where the fluid food is heated to a target temperature and then is cooled back to its initial temperature: QS = F C P ΔT

Q X = F C P (T1 − T0 − ΔT )

QC = F C P (T0 + ΔT − T2 ) AS =

QS U (TS − T1 )

QX UΔT QS AS = U (T2 − TC ) AX =

where F

kg/s

Food flow rate

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Capital Cost of Food Plants

Cp ΔT T0 T1 T2 TS TC QS QC QX AS AC AX U

kJ/kg K C o C o C o C o C o C kW kW kW m2 m2 m2 kW/m2K o

131

Food specific heat Minimum heat exchanger temperature approach Food initial temperature Food target temperature Food final temperature Hot utility temperature Cold utility temperature Hot utility load Cold utility load Heat exchanger load Heater transfer area Cooler transfer area Heat exchanger transfer area Overall heat transfer coefficient

Continuous flow sterilizers (or pasteurizers) are essentially heat exchangers (shell-and-tube or plate). They are designed by considering the heat transfer rate and the kinetics of microbial inactivation. In-container sterilizers (continuous and batch) are designed and selected empirically, based on container size and loading, and sterilization (or pasteurization) time. NOMENCLATURE

A Cp D E F g kb kd kG kr kS L N N P Q T U

m2 kJ/kg K m kW kg/s m/s2 m 1/s kPa kW K kW/m2K

Area Specific heat Diameter, width, particle size Electric power Flow rate Gravity acceleration Belt power coefficient Size reduction power coefficient Power coefficient for agitation Power coefficient for rotation Screw power coefficient Length Number of evaporator units Rotating velocity Pressure Thermal load Temperature Overall heat transfer coefficient

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132

u V W w z ΔHS ΔP ΔT ΔTL

ε γ η ρ τ

Chapter 5

m/s m3 kg/s kJ/kg m kJ/kg kPa o C o C kg/m3 s

Velocity Volume Evaporating flow rate Work index Loading depth Latent heat of solvent vaporization Pressure loss Minimum heat exchanger temperature approach Mean temperature difference Void fraction Polytropic coefficient Efficiency Density Residence time

REFERENCES

Bhatia MV, 1979-1983. Process Equipment Series, vol 1-5. Technomic. Biegler LT, Grossman IE, Westerberg AW, 1997. Systematic Methods of Chemical Process Design. Prentice Hall. Branan C, 1998. Rules of Thumb for Chemical Engineers, 2nd Edition. Gulf Publishing Company. Brennan JG, Butters JR, Cowell NP, Lilly AEV, 1990. Food Engineering Operations, 3rd ed. Applied Science. Biegler LT, Grossman IE, Westerberg AW, 1997. Systematic Methods of Chemical Process Design. Prentice Hall. Couper JR, 2003. Process Engineering Economics. McGraw-Hill. Chilton CH, 1960. Cost Estimating in the Process Industries. Mc Graw-Hill. Douglas JM, 1988. Conceptual Design of Chemical Processes. McGraw-Hill. Farkas DF, 1977. Unit operations concepts optimize operations. Chemical Technology 7:428-433. Farkas DF, 1980. Optimizing unit operations in food processing. In: Linko P, Malkki Y, Olkku J, Larinkari J, eds. Food Process Engineering, vol 1. Applied Science, pp 103-115. Garrett DE, 1989.Chemical Engineering Economics. Van Nostrand Reinhold. Gerrard AM, 1998. Guide to Capital Cost Estimating, 4th Edition. IChemE. Gould WA, 1996. Unit Operations for the Food Industry. CTI. Guthrie KM, 1969. Capital and operating costs for 54 chemical processes. Chemical Engineering 77: 140–156. Holland FA, Bragg R, 1995. Fluid Flow for Chemical Engineers. Edward Arnold.

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Holland FA, Wilkinson JK, 1997. Process Economics. In: Perry RH, Green DW, Maloney JO, Perry’s Chemical Engineers’ Handbook, 7th Edition. McGraw-Hill. Jowitt R. Hygienic Design and Operation of Food Plant. Ellis Horwood. Maroulis ZB, Saravacos GD, 2003. Food Process Design. Marcel Dekker. Perry RJ, Green JH, 1997. Perry's Chemical Engineers' Handbook, 7th ed. McGraw-Hill. Peters MS, Timmerhaus KD, West RE 2003. Plant Design and Economics for Chemical Engineers, 5th Edition. McGraw-Hill. Saravacos GD, Kostaropoulos AE, 2002. Handbook of Food Processing Equipment. Kluwer Academic / Plenum Publishers. Troller JA, 1993. Sanitation in Food Processing, 2nd ed. Academic Press. Turton R, Builie RC, Whiting WB, Shaeiwitz JA, 1998. Analysis, Synthesis and Design of Chemical Processes. Prentice Hall. Ulrich GD, 1984. A Guide to Chemical Engineering Process Design and Economics. J Wiley. Valentas KJ, Levine L, Clark JP, 1991. Food Processing Operations and Scaleup. Marcel Dekker. Walas SM, 1988. Chemical Process Equipment. Butterworths.

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6 Operating Cost of Food Plants

I. INTRODUCTION The total operating cost (or expenses) of a food industry consists of the plant operating (manufacturing) cost and the general (administrative and selling) cost. The plant operating cost is the sum of the costs of raw materials, utilities, labor, maintenance, depreciation, and local taxes (Brennan, 1998). The Food Processing Industry is materials-intensive, capital-intensive, and labor-extensive. There are 5 main categories of operating costs in food processing plants: Raw materials, packaging, capital, labor, energy, and business services. Agricultural food raw materials and packaging materials constitute the major plant operating cost. Average food processing industry costs: Raw materials 64%, labor 11%, gross margin 25% (including capital utilization, services and profits). During the recent years, semi-finished (ingredient) food materials constitute about 40% of the total food raw materials (Connor and Schiek, 1997). II. RAW MATERIALS The food processing industry uses large amounts of agricultural raw materials, produced in local or distant farms. An increasing portion of semi-processed or ingredient foods are also used as special raw materials of a variety of food products. The cost of raw materials (excluding packaging) is high in soybean oil extraction (90% of the product cost) and in wheat milling (76%), but low in mayonnaise (42%), and breakfast cereals (26%). 135

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Chapter 6

Raw materials for food plants include fruits and vegetables, cereal products (grains), oil seeds. dairy products, animal products, and marine products. In growing agricultural raw materials for food processing, product variety (cultivar), soil, and climatic conditions are important considerations. Mechanical harvesting, postharvest handling, and transportation to the plant contribute to plant economics (Luh and Woodroof, 1988; Woodroof and Luh, 1986; Salunkhe and Kadam, 1995, 1998). Raw materials should have the suitable composition and quality for processing, i.e. the basic chemical constituents (carbohydrates, proteins), and the needed vitamins, flavor components, and dietary fibers.). The price of some raw materials may be related to the percent content of a major component, e.g., percent soluble solids content (oBrix) of sugar beets used in sugar processing, and tomatoes used for tomato paste. Supply of food raw materials should aim at improving overall product quality, lowering processing costs, and improving company profitability. Some difficulties in the supply process are caused by the biological nature (variation) of the agricultural raw materials. Various types of contracts are used, e.g., forward price contracting, futures contracting, and supplier partnership. Some large food processing companies use vertical integration, i.e. the processor produces his own raw materials. The suppliers are usually responsible for the transportation and delivery of raw materials, packaging materials, food ingredients, food chemicals, and process equipment. R&D services to improve existing products and processes and develop new ones are usually supplied by external contractors, except in large corporations, which operate their own research facilities. The cost of agricultural raw materials is affected strongly by the country and the location of the growing land. Some agricultural products are subsidized by individual countries (e.g., USA) or confederations (e.g., the European Union, EU). Subsidies increase the income of the farmers, while keeping the cost of raw materials and processed foods competitive in the world markets. Subsidized products in the USA (about $15 billion in 2004) include wheat, corn, cattle and hogs. In the EU subsidies (about $60 billion in 2004) cover the production of milk, wine, orange juice, olive oil, and sugar beets. The food packaging materials cost increased on the average from 4% (1947) to about 10% (1987) of the total product cost. Packaging costs are very important in soft drinks, canning, freezing, and confectionery. Paper is the most important packaging material, followed by plastics.

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III. FOOD PRODUCT COST DATA 1. Retail Prices Raw materials cost is the most significant operating cost in food industry. Thus, the accuracy of the estimation is a crucial point in economics evaluations. Cost data for food materials or food-related commodities can be found in US or international statistical organizations. For example the Bureau of Labor Statistics is suggested for the US: • http://www.bls.gov Monthly average prices are presented for more than • 1200 food products • 40 US coded areas • 20 years For example, Figure 6.1 depicts the retail prices for tomatoes at an average US city since 1980, based on the data which have been retrieved and compiled from the above source.

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Chapter 6

6.00

5.00

4.00

Price ($/kg)

3.00

2.00

1.00

0.00 1975

1980

1985

1990

1995

2000

2005

Calendar year

Figure 6.1 Tomato retail prices. Data from the US Bureau of Labor Statistics.

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2010

Operating Cost of Food Plants

139

Similarly, annual averaged data for selected food materials are presented in Table 6.1 and in Figure 6.2. Table 6.1 Annual Average Retail Prices for Selected Food Products. Data from the Bureau of Labor Statistics Apples

1996 2.05

1997 2.00

1998 2.08

1999 1.98

2000 2.03

2001 1.91

2002 2.09

2003 2.16

2004 2.30

2005 2.09

Bread, white

1.93

1.92

1.90

1.96

2.05

2.20

2.24

2.21

2.14

2.29

Bread, whole whea

2.76

2.83

2.85

2.93

2.99

3.17

3.22

3.14

2.92

2.98

Carrots

1.13

1.13

1.23

1.24

1.24

Flour

0.63

0.67

0.66

0.65

0.64

0.67

0.69

0.69

0.67

0.71

Milk

0.69

0.69

0.71

0.75

0.73

0.76

0.73

0.73

0.83

0.84

Orange juice

3.60

3.65

3.44

3.78

3.89

4.00

3.90

3.91

3.99

3.87

Oranges Navel

1.36

1.32

1.07

1.86

1.38

1.59

1.84

1.85

1.89

2.20

Oranges Valencia

1.55

1.39

1.45

2.09

1.34

1.16

1.25

1.27

1.52

1.98

Peaches

2.59

2.31

2.99

3.15

2.91

3.28

3.34

3.24

3.13

3.49

Pears

2.02

1.86

2.06

2.09

2.13

2.13

2.20

2.18

2.57

2.46

Potato chips

6.74

6.91

6.97

7.18

7.41

7.55

7.40

7.71

7.50

7.42

Potatoes, frozen

1.97

2.06

2.22

2.24

2.31

2.37

2.45

2.25

2.16

2.05

Potatoes

0.84

0.78

0.83

0.87

0.84

0.86

1.09

1.01

1.00

1.04

Rice

1.20

1.25

1.19

1.18

1.08

1.06

1.03

1.00

1.18

1.22

Tomatoes

2.67

2.85

3.25

3.02

3.05

2.91

2.92

3.33

3.54

3.55

Wine

4.93

5.17

5.07

5.24

5.41

5.96

6.23

6.39

6.92

7.77

Yogurt

2.87

2.92

2.97

3.02

2.80

2.84

3.00

3.46

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Chapter 6 4.00

4.00 Tomatoes

Retail price

Retail price

Bread, whole

($/kg)

($/kg) 3.00

wheat

3.00 Bread, white

Apples 2.00

2.00

1.00

1.00

Flour

Potatoes

0.00 1994

0.00 1996

1998

2000

2002

2004

2006

1994

1996

1998

Calendar year

2000

2002

2004

2006

Calendar year

8.00

8.00

Retail price

Retail price

($/kg)

($/kg) 7.00

7.00

Potato chips

Wine

6.00

6.00

5.00

5.00

Orange juice 4.00

4.00

3.00

3.00

Potatoes, frozen

2.00

2.00 Milk 1.00

1.00

0.00

0.00

Potatoes

1994

1996

1998

2000

2002

Calendar year

2004

2006

1994

1996

1998

2000

2002

2004

2006

Calendar year

Figure 6.2 Annual average retail prices for selected food products. Data from the Bureau of Labor Statistics.

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141

2. Farm Prices While retail price is the value paid by the consumer to get the goods from the market, farm price is the value received by the farmers for raw farm commodities. Farm prices can be found in US or international statistical organizations. For example, the National Agricultural Statistics Services is suggested for the US: • http://www.nass.usda.gov Figure 6.3 depicts, for example, a comparison between retail and farm prices for tomatoes during last years, while Figure 6.4 presents the corresponding retail-to-farm price ratio. Furthermore, Table 6.2 includes average farm prices for selected foods. The original data have been retrieved and compiled from the above source.

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6.00

5.00

4.00 Retail value Price ($/kg)

3.00

2.00

Farm value

1.00

0.00 2000

2001

2002

2003

2004

Calendar year

Figure 6.3 Retail and farm prices comparison for tomatoes.

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2005

2006

Operating Cost of Food Plants

143

12

10

8

Retail to farm price ratio

6

4

2

0 2000

2001

2002

2003 Calendar year

Figure 6.4 Retail-to-farm price ratio for tomatoes.

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2005

2006

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Table 6.2 Farm Prices for Selected Foods. Average Values during the twoyears period 2002–2003. Data Compiled from NASS/USDA Food

Price

Food

$/kg Commodities:

Price $/kg

Vegetables for fresh market:

Wheat

0.13

Artichokes, California

1.62

Rice

0.14

Asparagus

2.48

Corn

0.09

Broccoli

0.71

Peanuts

0.41

Cabbage

0.29

All milk, sold to plants

0.27

Cantaloups

0.38

Milk, fluid market

0.27

Carrots

0.42

Milk, manufacturing grade

0.25

Cauliflower

0.74

Honey

3.01

Celery

0.29

Field crops and miscellaneous:

Cucumbers

0.43

Garlic

0.59 0.66

Barley

0.13

Green peppers

Beans, dry edible

0.39

Honeydew melons

0.41

Cotton seed

0.11

Lettuce

0.43 0.29

Flaxseed

0.23

Onions

Hay, all, baled

0.09

Snap beans

1.07

Hops

4.16

Spinach

0.79

Oats

0.11

Sweet corn

0.42

Peas, dry edible

0.17

Tomatoes

0.76

Peppermint oil

26.3

Watermelons

0.19

Potatoes

0.14

Rye

0.12

Sorghum grain

0.09

Asparagus

1.14

Soybeans

0.24

Cucumbers

0.27

Spearmint oil

20.3

Green peas

0.25

Sweet potatoes

0.40

Lima beans

0.44

Snap beans

0.15

Livestock and livestock products:

Vegetables for processing:

Spinach

0.11

1.61

Sweet corn

0.07

Calves

2.19

Tomatoes

0.06

Chickens, broilers, live

0.72

Beef cattle

Eggs

0.93

Hogs

0.78

For all sales

0.49

Lambs

1.85

Crushed for oil

0.24

Sheep

0.69

For canning

0.56

Turkeys, live

0.80

Papayas

0.66

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Table 6.2 Continued Food

Price

Food

$/kg Citrus

Price $/kg

Peaches:

Grapefruit

0.11

For all sales

0.39

Lemons

0.22

For fresh consumption

0.60

Limes, Florida

0.16

Dried, California (dried basis)

0.45

Oranges

0.09

Tangelos, Florida

0.07

Pears:

Tangerines

0.25

For all sales

0.30

Temples, Florida

0.04

For fresh consumption

0.36

Apples: For fresh consumption

0.61

For processing

0.13

Apricots: For fresh consumption

Dried, California (dried basis)

1.33

Fo rprocessing (except dried)

0.20

Plums (California): For all sales

0.40

Prunes, dried (California)

0.79

0.65

Dried, California (dried basis)

1.68

For processing (except dried)

0.27

For fresh consumption

0.42

Avocados

1.81

For processing (except dried)

0.23

Blackberries (Oregon)

1.25

For fresh consumption

1.61

Boysenberries (California & Oregon)

1.69

For processing

0.67

Berries for processing:

Prunes and plums (excl. California):

Strawberries:

Loganberries (Oregon)

1.98

Raspberries, black (Oregon)

1.95

Grapes:

Raspberries, red (Oregon & Washington)

1.19

For all sales

Cherries: Sweet

1.48

Tart

0.89

Cranberries

0.73

Dates, California

1.60

Sugar crops:

0.40

Raisin varieties dried, California (dried basis)

0.48

Other dried grapes

0.48

Kiwi

0.82

Tree nuts: Almonds

2.95

Hazelnuts

1.02

Pecans, all

2.14

Maple syrup

5.58

Pistachios

2.56

Sugarbeets

0.04

Walnuts

1.16

Sugarcane for sugar

0.03

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3. Retail-to-Farm Price Ratios Retail-to-farm price spread is the difference between retail price and farm price. It represents the cost of: • processing • wholesaling • retailing Retail-to-farm price ratio is an alternative magnitude to express this difference. Retail-to-farm price ratio is a useful measure in techno-economic calculations. Data for calculating the retail-to-farm price ratio can be found in US or international statistical organizations. For example, the Economic Research Service is proposed: • http://www.ers.usda.gov For example, Table 6.3 and Figure 6.5 depicts the retail-to-farm price ratio for selected foods, based on the data which have been retrieved and compiled from the above source. Finally, Figure 6.6 and Table 6.4 summarize average values of retail-tofarm price ratios for some processed food products. These values can be used for preliminary calculations in techno-economical analysis.

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Table 6.3 Retail-to-farm price ratios Food

1998

1999

2000

2001

2002

Animal products: Eggs

1.93

2.13

1.90

1.65

1.62

Beef, choice

2.11

2.04

2.05

2.18

2.29

Chicken, broiler

1.86

2.04

2.10

2.30

2.34

Milk

2.45

2.55

2.98

3.47

3.86

Pork

3.98

4.03

3.27

3.32

4.29

Cheese, natural cheddar

2.55

3.12

3.45

3.81

4.44

5.00

Crop products: Sugar

3.15

3.23

3.73

4.44

Flour, wheat

5.00

5.44

5.37

5.30

5.42

Shortening

3.86

5.59

6.54

7.88

10.32

Margarine

3.91

5.87

6.77

8.00

9.78

Rice, long grain

4.46

5.27

7.25

9.50

11.40

Prepared foods: Peanut butter

3.91

4.44

4.50

4.67

5.03

Pork and beans, 303 can (16 oz.)

9.00

9.20

9.20

11.75

11.75 14.88

Potato chips, regular, 1-lb. bag

12.64

10.87

12.92

15.04

Chicken, fried, frozen, 11 oz.

7.93

8.00

7.12

6.83

6.53

Potatoes, french fried, frozen

9.18

9.27

10.50

12.00

13.75

Bread

21.50

22.00

22.00

24.25

25.25

Corn flakes, 18-oz. box

26.25

26.25

23.78

27.25

27.50

Oatmeal regular, 42-oz. box

16.06

18.86

19.14

19.43

21.31

Corn syrup, 16-oz. bottle

34.20

34.60

34.60

34.60

34.60

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Table 6.3 Continued Food

1998

1999

2000

2001

2002

Fruit and vegetables:

Fresh Lemons

4.00

4.29

4.45

4.46

4.64

Apples, red delicious

5.22

5.29

4.84

4.48

4.23

Potatoes

6.48

5.25

5.76

6.10

6.15

Oranges, California

4.69

3.60

6.89

5.91

5.23

Grapefruit

5.45

5.42

6.10

6.33

6.44

Lettuce

4.75

4.19

4.11

3.73

3.52

Frozen Orange juice conc., 12 fl. oz.

2.65

2.68

3.07

3.16

3.28

Broccoli, cut

9.29

9.57

8.06

7.05

6.59

Corn

12.89

13.22

13.56

15.63

16.00

Green beans, cut

15.29

15.57

20.29

20.86

16.71

Peas, 303 can (17 oz.)

4.00

4.55

4.64

4.25

4.33

Corn, 303 can (17 oz.)

4.30

4.50

4.50

5.63

5.75

Canned and bottled

Applesauce, 25-oz. jar

7.12

6.94

6.35

5.82

5.53

Pears, 2-1/2 can

6.30

7.79

7.84

7.84

7.95

Peaches, cling, 2-1/2 can

6.89

7.06

6.94

6.89

6.89

Apple juice, 64-oz. bottle

3.09

5.38

5.50

5.59

5.75

Green beans, cut, 303 can

7.33

7.50

7.50

7.50

7.67

Tomatoes, whole, 303 can

14.25

14.75

11.80

11.80

12.00

Beans

4.93

4.93

5.21

5.54

6.00

Raisins, 15-oz. box

3.50

2.81

6.10

2.21

3.33

Dried

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8.00

7.00

Apples, juice

6.00 Retail to farm ratio

Apples, sauce

5.00 Apples, fresh 4.00

3.00 1997

1998

1999

2000

2001

2002

2003

Calendar year 8.00

7.00

Potatoes, fresh 6.00 Retail to

Oranges, fresh

farm ratio 5.00

Apples, fresh

4.00

3.00 1997

1998

1999

2000

2001

Calendar year

Figure 6.5 Retail-to-farm price ratio for selected foods.

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2003

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14.00

12.00

Frozen

10.00

8.00 Canned and bottled

Retail to farm ratio

6.00 Fresh

4.00

2.00

0.00 1997

1998

1999

2000

2001

2002

Calendar year

Figure 6.6 Average retail-to-farm price for processed foods. Table 6.4 Averaged Retail-to-farm Price Values for Processed Foods Fresh

5.07

Frozen

10.8

Canned and bottled

6.95

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IV. PACKAGING MATERIALS The packaging materials used for processed foods include metal, paper, plastics, and glass. Bulk packing is used for food products delivered to institutional consumers or to re-processors. Individual consumer packages are more expensive per unit mass (kg) of product. Cost data of various packaging materials can be obtained from local or international suppliers (Saravacos and Kostaropoulos, 2002). The cost of selected packaging materials, used in the application examples of Chapters 7 and 8, is presented in Table 6.5. Table 6.5 Cost of Selected Food Packaging Materials (Application Examples of Chapters 7, 8) Description

Capacity

Use

$/p

kg/p

$/kg

Plastic drums

208 L

Pulps

20.0

235

0.09

Metallic cans

0.85 L (No 2 1/2)

Canned fruits

0.10

0.85

0.12

Glass bottles

0.75 L

Wine

0.15

0.75

0.20

Paper cartons

1L

Milk

0.10

1.00

0.10

Plastic cups

150 g

Yogurt

0.12

0.15

0.80

Plastic bags

0.5 kg

Frozen vegetables

0.05

0.50

0.10

V. UTILITITIES Food processing consumes relatively less energy than other industries, e.g., chemicals, petroleum, and steel. The US food system (agriculture, processing, distribution, and consumption) consumes about 13% of the total national energy. Food processing consumes about 4% of the total (Connor and Schiek, 1997). Fuel cost represents about 1.8% of the total product cost or 4.5% of the value added in food processing, which is considerably lower than the fuel cost of all manufacturing. The energy crisis (sharp increase of oil prices) of the 1970s led to considerable savings and improved technology in energy use. The average increase in energy consumption in recent years (3%) is about one-half of the increase in food processing production (6%). The food industry is, in general, less affected from energy crises than some energy-consuming industries, such as chemicals and metals. Table 6.6 shows typical energy consumption in various food processing plants. The energy values (MJ/kg or GJ/ton of product) were derived from data of a survey of the US food processing industry in the period 1980–1985 (Singh,

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1986). Energy (mainly heat) losses in the food processing industries varied according to the process and equipment used, ranging between 10–30 % of the total energy. Steam and hot water are used mainly in thermal food processing operations, such as evaporation, drying, blanching, pasteurization, and sterilization. Heating fuel (mainly gas or oil) is used for direct heating of food products, such as drying, roasting, and cooking. Most of the electrical power in the food processing industries is used in refrigeration and freezing processes, and for running motors of processing equipment. Electricity is also essential in space air conditioning and illumination. High energy consumption characterizes energy-intensive operations, such as drying, evaporation, extraction, grinding, roasting, and distillation. High energy consuming products, such as instant coffee, beet and cane sugar, breakfast cereals, and citrus juice concentrate, involve more than one of these operations. Fuels used in food processing plants include, natural gas, LPG, fuel oil, and coal. Cost of petroleum fuels depends on the cost of oil ($/barrel); oil prices fluctuate widely, due to international crises. The cost of coal is relatively stable, but its use in food processing is limited to heating some steam boilers. Typical heating values of fuels are: natural gas 37.2 MJ/m3, LPG 50.4 MJ/m3, and fuel oil 41.7 MJ/kg. The cost of electricity depends directly on oil prices. A significant part of electricity is derived from nonfossil sources, e.g., hydroelectric, nuclear, and renewable sources. Renewable energy sources include wind and solar power. Significant electrical energy can be provided from windmills and direct conversion of solar energy (photoelectric cells). Thermal energy can be derived from solar heaters of water or air. The use of renewable energy sources in food processing is confined to low-energy application, such as solar panels to heat air for drying of foods (Saravacos and Kostaropoulos, 2002), or heating water in a dairy plant . It should be noted that a significant investment is needed for the installation of a solar heating system, since the incident solar radiation is relatively low, e.g., 0.6 kW/m2 for a 7-hour operation per day, or 15 MJ/m2 day in a temperate zone. Energy losses in food processing industries are about 25%.

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Table 6.6 Energy Use in Food Processing Plants Total Energy Use Percent Energy (%) Food Product MJ / kg product Steam Fuel Electricity High Energy Use Instant coffee Potato granules Beet sugar Cheese and dry whey Breakfast cereals Milk powder Citrus juice concentrate

60.2 25.2 20.5 14.3 12.8 12.0 10.8

41 38 56 75 34 62 24

54 53 40 18 54 32 39

5 9 4 7 12 6 37

Intermediate Energy Use Chocolate / candy Soybean oil Canned meat Bread rolls Sausages Frozen cooked food Canned evaporated milk Milk chocolate Beer Canned fruits/vegetables

8.4 8.2 5.8 4.9 4.3 4.0 3.6 3.0 2.4 2.2

69 92 75 62 51 15 88 47 58 94

5 16 20 22 40 23 30 -

26 8 9 8 27 45 12 30 12 6

Low Energy Use Yogurt Wine Wheat flour Fluid milk

1.2 0.6 0.5 0.5

60 34 38 54

14 -

26 66 62 46

Data adapted from Singh (1986).

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VI. UTILITY COST ESTIMATING MODEL Utility operating cost is usually the most significant variable operating cost after raw materials. The effectiveness of an investment depends on the accuracy in estimating the cost of the utilities. In order to obtain a consistent and reliable estimation of the utilities cost, a robust model is needed to reconcile (compensate) the market fluctuations. Such a model is proposed in this section. Utility operating costs include: a. Energy related utilities • Fuel (fuel oil, natural gas, etc.) • Electricity (purchased, self-generated) • Steam (high, medium, and low pressure) • Cooling water • Refrigeration b. Nonenergy related utilities • Process water • Compressed air c. Waste treatment utilities • Waste disposal • Waste treatment The best way to estimate the cost of utilities is to relate the cost of any utility to the corresponding fuel cost by using thermodynamics and typical efficiencies of power plants. Market fluctuations should also be taken into account. 1. Fuel oil Cost Fuel oil cost varies significantly due to market fluctuations. Figure 6.7 depicts the fuel oil evolution during the last twenty years. The values refer to annual average data in an average city in USA (Bureau of Labor Statistics). Diachronic values of the fuel oil cost follows the crude oil market price variation, which is presented in Figure 6.8. The relationship is linear as revealed in Figure 6.9 and expressed by the equation:

C f = 8.37 × 10 −4 Cb + 1.23 × 10 −2 where Cb ($/bbl) is the crude oil cost and Cf ($/kWh) the fuel oil cost.

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0.60

0.50

0.40 Fuel oil cost ($/L) 0.30

0.20

0.10

0.00 1985

1990

1995

2000

2005

2010

Calendar year

Figure 6.7 Fuel oil cost during the 20-year period 1986–2005. Data from the Bureau of Labor Statistics. 60

50

40 Crude oil cost ($/bbl) 30

20

10

0 1985

1990

1995

2000

2005

2010

Calendar year

Figure 6.8 Crude oil cost during the 20-year period 1986–2005. Data from the Bureau of Labor Statistics.

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0.06

0.05

0.04 Fuel oil cost ($/kWh) 0.03

0.02

0.01

0.00 0

10

20

30

40

50

60

Crude oil cost ($/bbl)

Figure 6.9 Effect of crude oil cost on fuel oil cost during the period 1986–2005.

2. Natural gas Cost Natural gas cost varies less than fuel oil cost. Figure 6.10 depicts the natural gas cost during the last twenty years. The values refer to annual average data in an average city in USA (Bureau of Labor Statistics). Diachronic values of the natural gas cost is related to the fuel oil cost as presented in Figure 6.7. The relationship is linear as revealed in Figure 6.11 and expressed by the equation:

C g = 0.652C f − 0.009 where Cg ($/kWh) is the natural gas cost and Cf ($/kWh) the fuel oil cost.

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0.020

0.015

Natural gas cost ($/kWh) 0.010

0.005

0.000 1985

1990

1995

2000

2005

2010

Calendar year

Figure 6.10 Natural gas cost during the 20-year period 1986–2005. Data from the Bureau of Labor Statistics. 0.020 y = 0.652x - 0.009

0.015

Natural gas cost ($/kWh) 0.010

0.005

0.000 0.01

0.02

0.03

0.04

0.05

0.06

Fuel oil cost ($/kWh)

Figure 6.11 Relationship between the natural gas and the fuel oil cost during the period 1986–2005.

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3. Electricity Cost When electricity is bought from centralized power generation companies, the price tends to be more stable than fuel costs. Figure 6.12 depicts the electricity cost evolution during the last twenty years. The values refer to annual average data in an average city in USA (Bureau of Labor Statistics). The diachronic variation is more smooth than the fuel oil cost as concluded by comparing Figures 6.12 and 6.7. The effect of fuel oil cost on electricity cost is revealed in Figure 6.13 and expressed adequately by the equation:

Ce = 0.425 C f + 0.076 where Ce ($/kWh) is the electricity cost and Cf ($/kWh) the fuel oil cost. The above cost of electricity refers to average cost from a public provider. Instead, the self-generating cost can be estimated using a typical process efficiency according to the following equation:

Ce' =

Cf

ηe

where Ce’ ($/kWh) is the self generating electricity cost, Cf ($/kWh) is the fuel oil cost, and ηe the system efficiency.

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0.12

0.10

0.08 Electricity cost ($/kWh) 0.06

0.04

0.02

0.00 1985

1990

1995

2000

2005

2010

Calendar year

Figure 6.12 Electricity cost during the 20-year period 1986–2005. Data from Bureau of Labor Statistics. 0.12

0.11

0.10 Electricity cost ($/kWh) 0.09 y = 0.425x + 0.076 0.08

0.07

0.06 0.01

0.02

0.03

0.04

0.05

0.06

Fuel oil cost ($/kWh)

Figure 6.13 Effect of fuel oil cost on electricity cost during the period 1986–2005.

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4. Steam Cost Steam costs vary with the price of fuel. If steam is generated only for heating purposes and not used for power generation in steam turbines, then the cost can be estimated from local fuel costs assuming a boiler efficiency.

Cs =

Cf

ηb

where Cs ($/kWh) is the steam cost at a reference pressure of 42.5 bar, Cf ($/kWh) is the fuel oil cost, and ηb the boiler efficiency. When combined heat and power generating systems are used, the following equation estimates the steam cost versus the steam pressure:

Cs (P ) = (0.20 ln( P) + 0.25)Cs where Cs ($/kWh) is the high-pressure steam cost and Cs (P) is the cost of the steam at pressure P(bar). 5. Cooling Water Cost Cooling water costs tend to be low relative to the value of both fuel and electricity. The cost of cooling duty provided by cooling water is of the order of 10% that of the cost of power.

Cw = cpr Ce where Cw ($/kWh) is the cooling water cost and cpr = 0.100 for tower water 0.085 for river or sea water 0.115 for well water

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6. Refrigeration Cost The cost of power required to operate a refrigeration system can be estimated approximately by the following model:

Cr =

⎛ 1 1 ⎞⎟ Ce + ⎜ 1 + C ⎜ η cop ⎟ w η r cop r ⎝ ⎠

where Cr ($/kWh) is refrigeration cost, Ce ($/kWh) is the electricity cost, and Cw ($/kWh) the cooling water cost. ηr is the system efficiency and cop the coefficient of performance defined by the equation:

cop =

Te Tc − Te

Te = Tr − dTmin Tc = Tw + dTmin where Te(K) the refrigerant temperature at evaporator, Tc(K) the refrigerant temperature at condenser, Tr(K) the required process temperature, Tw(K) the cooling water temperature, and dTmin(K) the minimum heat exchanger temperature difference. 7. Energy-Related Utilities Cost The above suggested model estimates adequately the cost of the energy-related utilities versus the crude oil price. The results are summarized in Figures 6.14 and 6.15 for crude oil price of 67 and 80 $/bbl, respectively. For comparison the cost of coal as well as the cost of thermal systems (for chemical processes) are also presented.

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0.15

Refrigeration

Purchased electricity 0.10

Thermal systems Self-generated electricity

Utility cost ($/kWh) Steam 0.05

Crude oil cost ($/bbl) =

67.0

Cooling water 0.00 -200

0

200

400

600

800

Temperature (oC) Utility Electricity Crude Fuels

Thermal systems

Steam

Cooling water

Refrigeration

Description Purshased Self generated

$/kWh 0.105 0.085

Fuel oil Natural gas Coal 300 C 400 C 600 C 40 bar 10 bar 5 bar 1 bar tower river or sea well 5oC -20oC -50oC

0.068

0.083 0.089 0.105 0.075 0.054 0.043 0.019 0.011

0.073 0.091 0.135

$/ Common unit

67.0 0.68 0.46 65.0

$/bbl $/L $/m3 $/t

37.4 26.9 21.7 9.5 0.244 0.208 0.281

$/t $/t $/t $/t $/m3 $/m3 $/m3

Figure 6.14 Cost estimation for energy related utilities. Crude oil price = 67 $/bbl.

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0.15

Thermal systems

Refrigeration Purchased electricity 0.10

Self-generated electricity

Utility cost ($/kWh) Steam 0.05

Crude oil cost ($/bbl) =

80.0

Cooling water 0.00 -200

0

200

400

600

800

Temperature (oC) Utility Electricity Crude Fuels

Thermal systems

Steam

Cooling water

Refrigeration

Description Purshased Self generated

$/kWh 0.110 0.099

Fuel oil Natural gas Coal 300 C 400 C 600 C 40 bar 10 bar 5 bar 1 bar tower river or sea well 5oC -20oC -50oC

0.079

0.096 0.103 0.122 0.087 0.062 0.050 0.022 0.011

0.076 0.095 0.141

$/ Common unit

80.0 0.79 0.53 65.0

$/bbl $/L $/m3 $/t

43.3 31.2 25.1 11.0 0.255 0.217 0.293

$/t $/t $/t $/t $/m3 $/m3 $/m3

Figure 6.15 Cost estimation for energy related utilities. Crude oil price = 80 $/bbl.

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8. Nonenergy-Related Utilities Cost Nonenergy related utilities cost is generally more stable than the energy-related utilities cost. Typical values for 2006 are presented in Table 6.7. A general inflation index can be used for updating the next years. Table 6.7 Nonenergy-related Utilities Cost Utility Air

Water

Description Process Instrument Process Boiler feed Deionized

Cost 0.025 0.050 0.50 2.50 1.00

$/m3 $/m3 $/m3 $/m3 $/m3

9. Waste Treatment Cost Waste treatment is not strictly considered as utility, but since it has the same characteristics as an operating cost as the utilities, it is presented here. Typical values are presented in Table 6.8. Table 6.8 Nonenergy-related Utilities Cost Utility Waste disposal

Waste Treatment

Description Non hazardous Hazardous Primary Secondary Tertiary

Cost 35 145 0.40 0.45 0.55

$/t $/t $/t $/t $/t

The high disposal costs shown in Table 6.8 refer to general processing plants, which generate solid and semi-solid wastes. The undesirable wastes are either removed by track to special disposal / treatment sites, or treated in plant by drying or combustion. The dried waste is either used as a by-product of the plant or disposed to an outside site. Disposal of hazardous wastes, usually chemicals, requires special combustion facilities or safe packaging and disposal to special outside sites. Primary wastewater treatment consists of sedimentation and/or filtration of suspended particles. Secondary treatment involves biological oxidation of organic waste in aerated tanks or basins. Tertiary treatment, usually not practiced in food plants, involves removal of mineral components and odors. Organic solid wastes and wastewater from small to medium sized food plants, located away from inhabited areas, can be disposed to nearby agricultural land for irrigation and fertilizing of growing plants. For the examples of food processing plants, considered in Chapters 7–9 of this book, the combined cost of treatment and disposal of the generated solid and water wastes can be taken as approximately equal to 5 $/t.

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VII. LABOR The food processing industry employs full-time and part-time labor. The food preservation plants utilize various seasonal raw materials and employ several part-time workers. Seasonal labor of relatively low cost can be recruited from local areas, with the workers returning to farm jobs, after the processing “campaign”. Production workers, up to the working foreman, are engaged in fabricating, processing, assembling, inspecting, receiving, storing, handling, packaging, warehousing, shipping, maintenance, repair, product development, power plant operation, and record keeping. Nonproduction workers are engaged in factory supervision above the working foremen level, sales, advertising, credit, installation and servicing, clerical and routine office functions, executive, purchasing, financing, legal, personnel, professional, and technical. Labor cost in food processing plants average 13%, is lower than the labor cost in all US manufacturing sector (20%). High labor cost is found in baking (29%) and ice cream/confectionery 15%. Low labor cost is met in soybean oil, cheese, and milling industries. These industries use large labor-saving machinery to increase worker productivity. The process labor requirements can be estimated from the process flowsheet and the material and energy balances. The supporting labor (maintenance, supervision, staffing (engineering support, laboratory, accounting, clerical, and secretarial) can be estimated using empirical factors, such as: total personnel = 3 x (process labor). Estimation of labor hours: (hours/shift) x (shifts/day) x (days/year) = hours/year. Assuming a continuous plant operation, we have 7 x 24 = 168 h/wk. For a 40 h/wk, 168 / 40 = 4 x (operators per shift). Food processing plants employ several unskilled workers (labor), some of them on temporary basis.

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VIII. LABOR COST ESTIMATING MODEL 1. Factorial Method A factorial method is proposed in order to estimate the labor cost in a food plant. The method is based on the equation:

CLab = t y f LabCL M where CLab the annual labor cost ($/y) ty the annual operating time (h/y) CL the production worker hourly rate ($/h) M the required manpower (production workers) fLab the labor cost correction factor The labor cost correction factor is a product of the following individual correction factors:

f Lab = f C f S fT f Q f B f O where the country effect fC fS the supervising and clerical assistance fT the advanced technological and automating level fQ the skilled and qualified level of the personnel fB the social benefits the overtime work fO B

The country effect factor fC is expressing the average country wage rates comparative to US for which fC=1.00. The supervising factor is usually considered for preliminary calculation as fS=1.20. The automating level factor varies between 0.80 and 1.20 according to the automation level of the plant and an average value may be assumed fT=1.00. The personnel qualified factor varies according to the personnel qualifications and a value of fQ =1.50 is proposed for preliminary calculations. The social benefits factor is adequately estimated using a value of fB=1.40. The overtime factor is estimated according to the working schedule comparative to standard with no overtime schedule fO=1.00. B

Thus, an overall labor factor (fLab) of 2.50 is appropriate for typical calculations:

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167

=1.00 =1.20 =1.00 =1.50 =1.40 =1.00

2. Annual Operating Time The annual operating time ty (hours) is calculated by the following equation:

t y = wpy × dpw × spd × hps where wpy weeks per year dpw days per week spd shifts per day hps hours per shift Food plants are characterized by seasonal operation. Typical annual operating times are presented in Table 6.9 for various operating modes. Table 6.9 Typical Modes of Operation for Food Plants Mode

wpy

dpw

spw

ty

1 season 5 days 1 shift 5 days 2 shifts 7 days 2 shifts 5 days 3 shifts continuous

12.5 12.5 12.5 12.5 12.5

5 5 7 5 7

1 2 2 3 3

500 1000 1400 1500 2100

2 seasons 5 days 1 shift 5 days 2 shifts 7 days 2 shifts 5 days 3 shifts continuous

25 25 25 25 25

5 5 7 5 7

1 2 2 3 3

1000 2000 2800 3000 4200

All the year 5 days 1 shift 5 days 2 shifts 7 days 2 shifts 5 days 3 shifts continuous

50 50 50 50 50

5 5 7 5 7

1 2 2 3 3

2000 4000 5600 6000 8400

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3. Manpower The required manpower can be estimated for preliminary analysis by several short-cut methods, two of which are suggested in this book: a. The first method counts the processes included in the plant and assigns typical values for each process. That is, the required manpower M is calculated by the equation: N

M = ∑mj j =1

where mj is the typical requirements for the j process. Table 6.10 represents some typical requirements for the purposes of this book. b. The second method uses existing data and scales-up according to the plant capacity. That is:

M = M 0 F nL where F is the plant capacity (t/h) and the empirical parameters M0 and nL characterize the specific plant category. For food plants a good estimation can be obtained by fitting the above equation to systematic data by Bartholomai (1987). The results are presented in Figure 6.16. 4. Labor Rates Detailed data for Labor hourly rates for various personnel categories at various locations are presented systematically by the Bureau of Labor Statistics: • http://www.bls.gov Figure 6.17 depicts, for example, the US average production worker hourly rate (not including benefits) during the last decade. Comparative labor cost for various personnel categories used in food plants are presented in Table 6.11. Overtime work is taken into account by considering a 50% addition for night operation and 100% addition for weekend operation as shown in Table 6.12. The labor cost for other than US countries is presented in Table 6.13 and Figure 6.18.

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Table 6.10 Typical Personnel Requirements for Various Food Processes Eqipment

Operators

Silo

0.10

Storage tank

0.10

Process vessel

0.20

Agitated jacketed reactor

1.00

Electric motor

0.10

Agitator

0.10

Compressor

0.50

Pump

0.10

Fan

0.10

Conveyor belt

0.10

Belt washer

0.50

Belt dryer

1.00

Belt freezer

1.00

Scraped surface heat exchanger

1.00

Shell and tubes heat enchanger

0.50

Plate heat exchanger

1.00

Tubular evaporator

1.00

Forced circulation evaporator

1.00

Vacuum drum filter

1.00

Plate filter

1.00

Vibrating screen

0.50

Tray dryer

1.00

Vibratory conveyor dryer

1.00

Rotary dryer

1.00

Fluidized bed dryer

1.00

Cutter

1.00

Crusher

1.00

Grinder

1.00

Ball mill

1.00

Centrifuge

1.00

Screw press

1.00

Extruder

1.00

Packaging equipment

1.00

Turbine

1.00

Boiler

1.00

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slaughter products seafood

100

milk products

dry yeast

frozen vegetables

blue cheese fruit puree frozen fish

Workers

tortilla chips

ice cream tomato paste lasagna pasta concentrated juice apple products

egg powder frozen shrimp

frozen bread quenelles (dumplings) mozzarella cheese

10

corn snacks

sausages

corn starch

soybean oil

fruit juice

cooking oil

yogurt

arabic bread white bread

skim milk powder

parboiled rice protein

vinegar

M = 10 F 2/3 1 0.1

1

10

100

Plant capacity F (t/h)

Figure 6.16 Personnel requirements for several food plants. Data compiled from Bartholomai (1987).

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20

15

Unskilled labor rate ($/h) 10

5

0 1994

1996

1998

2000

2002

2004

2006

Calendar year

Figure 6.17 Average hourly rates of production workers during the 10-year period 1996–2005. Data from the Bureau of Labor Statistics. Table 6.11 Comparative Labor Cost for Various Categories Category Unskilled operator Skilled operators Mechanics Technicians Foremen Plant managers

Relative cost 1.00 2.00 3.00 3.50 4.00 5.00

Table 6.12 Comparative Labor Cost for Overtime Work hours per week 1 - 88 89 - 144 145 - 168

Relative cost 1.00 1.50 2.00

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Table 6.13 Comparative National Labor Cost Relative to USA Country

1999

2000

2001

2002

2003

2004

Norway Denmark Germany Netherlands Finland Switzerland Belgium Sweden Austria Luxembourg United Kingdom France United States Australia Ireland Japan Canada Italy Spain New Zealand Israel Korea Greece Singapore Portugal Taiwan Hungary Hong Kong Czech Republic Brazil Mexico Sri Lanka

1.31 1.29 1.30 1.13 1.14 1.23 1.17 1.14 1.14 1.04 0.91 0.90 1.00 0.84 0.73 1.08 0.85 0.82 0.63 0.47 0.56 0.39 0.44 0.37 0.27 0.30 0.15 0.28 0.15 0.18 0.10 0.02

1.15 1.11 1.15 0.98 0.99 1.07 1.02 1.02 0.97 0.89 0.85 0.78 1.00 0.73 0.65 1.12 0.84 0.70 0.54 0.40 0.58 0.42 0.46 0.36 0.23 0.31 0.14 0.28 0.14 0.18 0.11 0.02

1.13 1.07 1.09 0.96 0.96 1.05 0.96 0.89 0.93 0.84 0.81 0.76 1.00 0.65 0.66 0.94 0.79 0.66 0.52 0.37 0.60 0.38 0.53 0.34 0.22 0.29 0.15 0.28 0.15 0.14 0.12 0.02

1.28 1.13 1.13 1.03 1.02 1.11 1.02 0.95 0.97 0.87 0.85 0.80 1.00 0.72 0.71 0.87 0.78 0.69 0.56 0.40 0.52 0.41 0.53 0.31 0.24 0.26 0.18 0.26 0.18 0.12 0.12 0.02

1.42 1.35 1.33 1.23 1.22 1.25 1.19 1.13 1.14 1.04 0.95 0.95 1.00 0.89 0.86 0.91 0.87 0.81 0.67 0.50 0.52 0.45 0.50 0.32 0.28 0.26 0.22 0.25 0.21 0.12 0.11 0.02

1.50 1.46 1.40 1.33 1.32 1.31 1.29 1.23 1.22 1.15 1.07 1.03 1.00 1.00 0.95 0.95 0.92 0.88 0.74 0.56 0.53 0.50 0.47 0.32 0.30 0.26 0.25 0.24 0.23 0.13 0.11 0.02

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1.50

Norway Germany

1.25

United Kingdom

1.00 Japan

Labor cost relative to USA

0.75

Spain

0.50

Greece

0.25

Brazil Sri Lanka

0.00 2000

2001

2002

2003

Calendar year

Figure 6.18 Comparative National Labor Cost Relative to USA.

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2004

2005

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REFERENCES Bartholomai A, 1987. Food Factories: Processes, Equipment, Costs. VCH Publishers. Brennan D, 1998. Process Industry Economics. ICHEME, Rugby, UK. Connor JM, Schiek WA, 1997. Food Processing. An Industrial Powerhouse in Transition 2nd Edition. John Wiley. Couper JR, 2003. Process Engineering Economics. Marcel Dekker. Luh BS, Woodroof JG, 1988. Commercial Vegetable Processing. 2nd Edition, Van Nostrand Reinhold. Maroulis ZB, Saravacos GD, 2003. Food Process Design. Marcel Dekker. Moresi M, 1984. Economic study of concentrated citrus juice production. In: McKenna B ed. Engineering and Food, Vol. 2. Elsevier Applied Science Publ. Peters MS, Timmerhaus KD, West RE, 2003. Plant Design and Economics for Chemical Engineers, 5th Edition. McGraw-Hill. Salunkhe DK, Kadam SS, 1995. Handbook of Fruit Science and Technology. Marcel Dekker. Salunkhe DK, Kadam SS, 1998. Handbook of Vegetable Science and Technology. Marcel Dekker. Saravacos GD, Kostaropoulos AE, 2002. Handbook of Food Processing Equipment. Kluwer Academic/Plenum Publ. Singh RP, 1986. Energy in Food Processing. Elsevier. Woodroof JG, Luh BS, 1986. Commercial Fruit Processing, 2nd Edition, Van Nostrand Reinhold.

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7 Food Preservation Plants

INTRODUCTION The food preservation plants utilize agricultural and marine raw materials to process and preserve food products, applying the principles and technology of thermal processing, refrigeration and freezing, and concentration/dehydration. Novel food preservation methods, such as irradiation and super–high pressure, are in the development stage, and industrial production is at the present time limited. The food preservation industry is highly depended on the raw materials, some of which (e.g., fruits and vegetables) are seasonal and depend on the soil and climate of the growing area. The raw materials should be tailored to processing requirements, i.e. good yield, maturity, special harvesting properties, good transportation and storage stability, and good quality attributes, such as color, flavor, texture, and total solids content (%TS). The cost of raw food material affects strongly the cost of the preserved food products, especially in high quality fruits, such as oranges (50–60% of the product cost). The food preservation plants are usually located near the agricultural production of the raw materials. For seasonal products, the processing plant is not utilized fully, e.g., operation for only 3–4 months a year. Longer operating periods can be achieved by processing raw materials which mature at different times. Transportation of raw materials by trucks from longer distances may improve the economics of food plant operation. Fish processing (canning, freezing) plants are located near sea ports for ready access to seafoods, transported by fishing ships from the catch areas. Similarly, meat and poultry processing plants should be located near slaughter houses and chicken raising farms. 175

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The plant utilities of these plants, especially energy and water, represent a significant operating cost. Energy in the form of steam is required in evaporation, dehydration, and thermal processing operations (Singh, 1986). Large amounts of water are required for washing the raw materials and water–cooling operations. Significant amounts of wastewater are generated during food processing, which should be treated or disposed to protect the environment. Food packaging in consumer packages is a major operating cost item in canning and freezing processes. Concentrated and dehydrated food products are usually bulk–packed economically in large containers. Hygienic (sanitary) and food safety considerations, such as HACCP, ISO, GMP, and government regulations increase significantly the cost of food processing plants and food products. 1. Food Preservation Plants Table 7.1 lists several food preservation plants of economic importance. A large number of such plants use fruits and vegetables as raw materials, which are available only during the growing period, e.g., 2–4 months during summer and fall. Milk (mainly cow’s), meat, poultry, and fish can be available throughout the year. A large portion of the operating labor of the fruit and vegetable preservation plants may be seasonal workers from the plant surroundings. The permanent labor consists of technicians and equipment operators, who can do maintenance work and product handling (storage, packaging) during off–season. Table 7.1 Food Preservation Plants Preservation Process Processing Plant Pasteurization

Milk pasteurization Fruit juice pasteurization

Sterilization

Canning of fruit and vegetable products Canning of fish and meat products Canning of food and ready meals

Aseptic processing

UHT milk sterilization Aseptic packing of juices and concentrates

Freezing

Freezing of vegetable products Freezing of fish and meat Freezing of ready meals

Dehydration

Air dehydration of fruits and vegetables Spray drying of milk products Vacuum / freeze drying of sensitive foods

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Solid and liquid wastes in some small plants can be disposed in agricultural land, if available, near the food plant to comply with the local environmental laws. Refrigeration (temperatures 0–10oC) is often used in the storage of heat– sensitive products, such as fruits, fish, and animal products. 2. Application Examples The economics of 6 different food preservation plants is analyzed in this section. They represent conventional food processes of economic importance, which can be applied to various food industries around the world. They are medium–sized plants, resembling actual commercial food processing plants, which can be operated in any country with an elementary technological infrastructure. The hypothetical food plants are designed by normal engineering procedures, based on material and energy balances, unit operations, and capital and operating cost estimates (Chapters 3–6). Several simplifying assumptions, necessary in the design and economic analysis procedures, are made using engineering judgment, and literature data from food plants. They represent preliminary designs, useful for cost estimations. Detailed final designs are prepared by experienced engineers. Application examples 7.1 and 7.2 are concerned with the design and economics of food preservation plants, employing concentration and thermal treatment of fruit and vegetable juices (tomato and orange). Raw material, labor, and utility costs in the form of steam and fuel are very important in process economics. Preliminary designs of the tomato paste and orange juice concentrate plants were published, respectively, by Maroulis and Saravacos (2003) and Saravacos and Kostaropoulos (2002). The economics of citrus juice concentration was analyzed by Moresi (1984). Example 7.3 outlines the design and economics of ultra high temperature sterilization and aseptic packaging of fluid milk. Raw material (milk), labor, and packaging costs are the most important operating cost items. Example 7.4 outlines the design and economics of a fruit canning plant (peaches and apricots), which is traditional canning industry. Raw materials, labor, and packaging materials are the major operating costs. Example 7.5 outlines the technology and economics of commercial freezing of two vegetable products (peas and green beans). Raw materials, labor, and energy (refrigeration) costs are important. Example 7.6 describes the technology and economics of air dehydration of two typical vegetable products (potatoes and carrots). Raw materials, labor, and energy costs for dehydration operations are the major operating costs.

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I. TOMATO PASTE PLANT 1. Process Technology a. Raw Materials Tomato varieties used for tomato paste and tomato puree (pulp) should have high solids content, a bright red color, and a characteristic tomato flavor. The tomato fruits mature almost simultaneously, and so harvesting of the entire tomato field can be carried out in only one operation. In the U.S., mechanical harvesting is normally used, requiring special tomato varieties (Gould, 1992). Tomatoes are a commercial vegetable grown in several countries during the summer period, for both fresh market and food processing (Salunkhe and Kadam, 1997). Ripe tomatoes contain 4.5–7.0% TS (total solids), determined quickly by refractometer. The refractometer readings (oBrix) represent the % soluble solids content, which in tomato products is about 1% lower than the % TS. The oBrix values are converted to exact %TS or specific gravity, using special analytical tables for tomato products (Luh and Woodroof, 1988; NFPA, 1997). Tomatoes used for processing should have an acidity of 0.35–0.55% (citric acid), a pH less than 4.2, and an ascorbic acid (vitamin C) content of at least 20 mg/100 g. The high acidity classifies the tomato products as acid foods, which simplifies thermal processing and preservation operations. There is no danger of growth of the toxin–producing spoilage microorganism Clostridium Botulinum (Downing, 1996). The tomato processing plant should be located near the tomato growing fields, since harvested ripe tomatoes are very sensitive to mechanical damage and spoilage during transportation by truck in bulk or in lugs (boxes) at long distances. Tomatoes are processed as fast as possible, when received in the plant. Intermediate storage before processing is avoided, because of the danger of spoilage, since harvesting of tomatoes takes place during the summer period, when high ambient temperatures prevail. b. Concentrated Tomato Products The U.S. standards of identity define tomato paste as a concentrated product made by evaporation of pulped ripe tomatoes and containing at least 24% TS, salt–free, as determined by refractometer. Commercial tomato paste contains usually about 32% TS. Tomato puree or tomato pulp, made from pulped ripe tomatoes, contains less than 24 % TS, salt–free, as determined by refractometer (Downing, 1996). Tomato ketchup (catsup) is made by blending a tomato product (pulped ripe tomatoes, tomato juice, or tomato paste) with salt, vinegar, onions, and

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various seasonings, and cooking the mixture in open–kettles (boilers) to a concentration of 25–30% TS. c. Inspecting/Washing Samples of tomatoes, received in the plant, are inspected for color and percent of defective fruit (green, bruised, or spoiled) unfit for processing. The inspected sound tomatoes are washed thoroughly in washing machines to remove any soil or external material. The tomatoes are soaked and brushed in hot water (54oC) for 3–5 min, and subsequently they are sprayed with pressure (9 bar) water jets. The washed tomatoes are sorted and any unfit product is rejected. d. Crushing/Finishing The washed sound tomatoes are crushed by the “hot break” process, i.e. heating to about 93oC for 5 min and crushing to extract the pectin and inactivate the pectic enzymes. The crushed tomatoes are cooled to about 40oC and passed through a cylindrical finisher (screen) to remove any skins, cores, and seeds from the tomato juice. e. Concentration The thick tomato juice is concentrated in multiple–effect evaporators until the total solids content reaches 32%. Usually, 3–effect evaporation systems are used in order to reduce energy (steam) consumption. Forced–circulation evaporator units are applied to prevent thermal fouling and increase the heat transfer (evaporation) rate. Tomato products are not very heat sensitive, and they can be subjected to relatively high temperatures and long residence times in the evaporation system. f. Sterilization/Packing The tomato paste product of this example will be packed aseptically in polyethylene–lined fiber drums of 55 gallons (208 L) capacity for commercial and institutional use. Continuous flow sterilization and packaging equipment will be used (Downing, 1996). Larger aseptic packing containers and tanks can be used for storage and transportation of tomato paste. Part of the tomato paste may be packaged for the consumers in small–size enameled metal cans. g. Plant Effluents Solids waste (seeds, skins, cores, unfit fruit) can be used as an animal feed, or disposed to the soil (agricultural use). Wastewater can be used for agricultural field irrigation, or disposed at the local sewage system, if available. In some large plants, a wastewater treatment (biological oxidation) facility may be required.

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2. Process Flowsheet A material and energy balance diagram of the tomato paste plant is shown in Figure 7.1a. The balances are based on 1 kg product. Thus, 5.62 kg of raw tomatoes are required for 1 kg tomato paste. In the same diagram the utilities requirements are presented in kWh/kg, excluding electricity. The requirements in electricity, used mainly for electrical motors, will be presented in the next paragraphs after the equipment sizing procedure. A process flowsheet based on the above technology is presented in Figure 7.1b. The flowsheet depicts the main processes and defines their interrelations. Three intermediate storage tanks are included (processes No. 8, 10, 12), while pumps and other equipment of minor importance are not shown in the flowsheet. The basic assumption is that the examined system consists of a processing plant with central utilities, e.g., steam, cooling water, waste treatment, etc. Thus, the utilities system is not included in the flowsheet, but an operating allocated cost is considered in the cost analysis section. Steam (S) is used in heating (No. 5), evaporation (No. 9) and sterilizing (No. 11). Cooling water (C) is used in condenser (No. 14) and sterilizer (No. 11). Process water (W) is used in washing (No. 1 and 2) along with the pure water (w) produced in the condenser which is recycled. Liquid and solid wastes (L) are extracted from washing (No. 2) and finishing (No. 7). Processed tomato products are not very heat-sensible and they can withstand relatively high temperatures for long times. Thus, tomato juice evaporators can be operated at relatively high temperatures, using forced circulation to increase the heat transfer rate. Sterilization of tomato paste can be achieved in tubular heat exchangers, which are less costly than plate and scraped surface units. The bulk packing of sterilized tomato paste, used in this example, is costeffective for commercial and institutional use of the product. However, more expensive packaging materials will be needed if tomato paste is packaged in small sized metallic, plastic, or paperboard containers. The high acidity of tomato products facilitates the food sanitation and food safety procedures, required in a food process plant.

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Tomatoes

5.62 kg 7 %TS

Water 5.62 kg

Washing

Waste 5.62 kg 5.62 kg 7 %TS

Inspecting

Waste 0.08 kg

5.54 kg 7 %TS Pulping

0.65 kWh Heating

Finishing

Waste 0.20 kg

5.34 kg 6 %TS 1.26 kWh Evaporation

Water

1.26 kWh

4.34 kg 1.00 kg 32 %TS

0.01 kWh Sterilization 0.01 kWh

Cans Packaging 1.00 kg 32 %TS

Steam

Cooling water

Figure 7.1a Material and energy balances in the tomato paste plant.

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W

W

R

1 Dumping

2 Washing

3 Inspecting

L

L 7 Finishing

L

G

L

4 Pulping

S 6 Flash

5 Heating G

s

15 Vacuum C

8 Juice tank 9 Evaporators

w 14 Condenser c

S 10 Concentrate tank

s

C

S

12 Aseptic storage

13 Packaging P

K

c 11 Sterilizer

Figure 7.1b Process flowsheet of the tomato paste plant.

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3. Material and Energy Requirements Table 7.1a lists the material and energy requirements of the tomato paste plant, based on the material and energy diagram of Figure 7.1a. The heat requirements of the process were estimated using the thermophysical properties of the product and the water/steam (Appendix). The annual data corresponds to 960 h/y, according to the operating scheme described in the next paragraph. The Labor refers only to seasonal unskilled workers which is obtained by the process counting method (See Chapter 6). The supervising, and technical support is taken into account using the factorial method (Chapter 6). The solid waste of the plant, shown in the flowsheet is shown in Table 7.1a, along with the waste water treatment. It is disposed at $36/t, according to Chapter 6. The combined water and solid wastes, shown in Table 7.1a, are treated and disposed at an average cost of 5 $/t. The packaging material refers to 208 L or 235 kg plastic drums. Table 7.1a Material and Energy Requirements of a Tomato Paste Plant Per Product

Hourly basis

Annual

Products Tomato paste

1.00 kg/kg

2.00 t/h

1 920 t/y

11.2 t/h

10 790 t/y

9 p/h

8 170 p/y

2 460 t/y

Raw materials Raw Materials

Fr.

5.62 kg/kg

Packaging Material

Fg.

235 kg/p

Utilities Process Water

Fw.

1.28 kg/kg

2.56 t/h

Electricity

Fe.

0.08 kWh/kg

0.16 MW

150 MWh/y

Steam

Fs.

1.92 kWh/kg

3.84 MW

3 690 MWh/y

Cooling Water Refrigeration

Fc. Fz.

1.27 kWh/kg 0.00 kWh/kg

2.54 MW 0.00 MW

2 440 MWh/y 0 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

5.90 kg/kg

M.

10.0 h/t

Wastes Waste Treatment

11.8 t/h

11 330 t/y

Labor Manpower

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19 200 h/y

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4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 7.1a are estimated and the results are summarized in Table 7.1b. The most expensive equipment refers to a 3-effect evaporator, while the packaging equipment follows. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 7.1c. The design of the major thermal processing equipment, i.e. evaporation and sterilization is discussed, using application examples, by Maroulis and Saravacos (2003). The required thermal and transport properties of the system were taken from the related Tables of the Appendix. Table 7.1b Equipment Cost Estimation of a Tomato Paste Plant No

Process

Qty

1

Dumping

2

Size Units 5 t/h

Cost 50

2

Washing

2

5 t/h

50

3

Inspecting

2

10 m2

40

4

Pulping

2

5 kW

20

5

Heating

2

20 m2

80

6

Flash

2

1 m3

10

7

Finishing

2

5 t/h

100

8

Juice tank

2

10 m3

20

9

Evaporators

3

50 m2

1800

10

Concentrate tank

1

2 m3

10

11

Sterilizer

1

25 m2

80

12

Aseptic storage

1

2 m3

10

13

Aseptic packaging

1

2 t/h

200

14

Condenser

1

60 m2

30

15

Vacuum

1

10 kW

20 2520 k$

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Table 7.1c Capital Cost Estimation of a Tomato Paste Plant Purchased Equipment Cost

Ceq

2.52 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost

CF

Working Capital Cost

CW

Total Capital Cost

CT

7.56 1.01 8.57 M$

5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 7.1d, and the results are summarized in Table 7.1e and in Figure 7.1c. The cost of raw material (tomatoes), the labor, and the manufacturing cost are the major components of the product cost. The utilities cost is also important. A typical cost of 60 $/t tomatoes was assumed, although lower cost can be obtained in some areas of mass production and low growing and harvesting expenses. A labor rate of 15 $/h was assumed, which is representative of unskilled production workers. The annual operating time refers to 12 week per year, 5 days per week, 2 shifts per day, and 8h per shift. The waste water produced in the plant is disposed to a sewage system or it is used for irrigation. The solid waste (skins and seeds) is disposed away from the plant.

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Table 7.1d Assumptions for Operating Cost Estimation Tomato paste Plant Product Rate

PR

Operating Season

wpy

2.00 t/h 12 w/y

Annual Operating Time

ty

960 h/y

Operating Cost Factors Data Fixed Manufacturing Cost Factor

fMF

0.10 -

Overhead Cost Factor

fOver

0.05 -

Utilities Cost Crude Oil Cost

Cb.

67.0 $/bbl

Fuel Cost

Cf.

0.07 $/kWh

Electricity Cost

Ce.

0.11 $/kWh

Steam Cost

Cs.

0.08 $/kWh

Cooling Water Cost

Cc.

0.01 $/kWh

Freezing Cost

Cz.

Process Water Unit Cost

Cw.

0.50 $/m3

Waste Treatment Cost

Cj.

5 $/m3

0.11 $/kWh

Labor Cost Characteristics Labor Rate Cost

CL

15.0 $/h

Labor Cost Correction Factor

fL

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00 -

2.50 $/kg

Material Unit Cost Product

Cp.

Raw Materials

Cr.

Packaging Material

Cg.

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Table 7.1e Operating Cost Estimation of the Tomato Paste Plant Manufacturing Cost Raw Materials

Cmat

Packaging

Cpack

0.77 0.16

Utilities

Cutil

0.32

Waste Treatment

Cwst

0.06

Labor

Clab

0.90

Variable Manufacturing

Cmv

2.21

Fixed Manufacturing

Cmf

0.76 0.20

Overheads

Cover

Manufacturing

CM

Capital Charge

e CT

0.71 -

Total Annualized

TAC

3.89 M$/y

3.17 M$/y

Unit Cost ($/kg)

…

2.50

2.00 Capital Charge Overheads

1.50

Fixed Manufacturing

1.00

Labor Waste

0.50

Utilities

Treatment Packaging

Raw Materials 0.00 1 Cost Operating

Figure 7.1c Operating cost estimation of the tomato paste plant.

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6. Plant Profitability Table 7.1f summarizes all the required economic assumptions in order to calculate the plant profitability, that is: A tax rate of 35% is considered. The Negative Tax Permission Index is 1 when the examined plant is a part of larger factory and the plant taxation is consolidated with the total factory, and 0 otherwise, which means that the tax reduction may be lost. The annual depreciation is estimated according to the MACRS method described in Chapter 4. According to this method, the equipment is depreciated in 7 years. It is assumed that 50% of the required capital is covered by loan with interest of 5% for 15 y. It is also assumed that the plant lifetime is 27 y, but after 20 y the equipment has no salvage value. A discounted interest rate of 7% is assumed in order to express the time value of money. The calculated capital recovery factor (Equation 4.24), for i=0.07, and N=27, is e=0.083. Based on these assumptions, the annual cash flow of the examined system during its life time is presented in Figure 7.1d. Figure 7.1.d also presents the Cumulated Cash Flow CCF and the Net Present Value NPV for the project life time (see Chapter 4). The characteristic time intervals are the depreciated period ND, the loan payment period NL, the positive salvage period NS, and the project life time NE. Moreover, CCF intercepts the time axis at the simple payback period SPB, while NPV intercepts the time axis at the depreciated payback period DPB. Table 7.1f Assumptions for Plant Profitability Estimation Tax Characteristics Depreciation Method

jd MACRS -

Depreciation Period Tax Rate

ND t

7 y 0.35 -

Negative Tax Permission Index

ntp

1 -

Debt Characteristics Leverage

L

0.50 -

Loan Interest Rate

iL

0.05 -

Loan Period

NL

15 y

Discounted Interest Rate

i

0.07 -

Plant Lifetime

N

27 y

Nonzero Salvage Value Period

NS

20 y

Other

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Cash flow (M$)

1.5

1.0 Tax Reduction

Tax

0.5 Net Profit

Loan Payment 0.0 1

2 3

4 5

6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Operating year

2

Net present value / Own Capital

CCF

NPV 0 0

5

10

15

ND

20

NL

25

NS

30

NE

-2 Operating year

Figure 7.1d Annual cash flow (upper) and cumulated cash flow (CCF) and net present value (NPV) of the tomato paste plant.

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Table 7.1g Plant Profitability of the Tomato Paste Plant Profitability

Sales Income

S

Manufacturing Cost

CM

4.04 M$/y 3.17 M$/y

Gross Profit

Pg

0.87 M$/y

Net Present Value

NPV

1.25 M$

Own Capital Cost

Co

4.28 M$

Capital Return Ratio

CRR

0.29 -

Internal Rate of Return

IRR

0.10 -

Based on these data, the resulting profitability indices are summarized in Table 7.1g.

7. Sensitivity Analysis All the above results refer to a basic reference point. The sensitivity of these results to the variation of basic data constitutes a crucial concept in the design and analysis of the food plants. Several sensitivity analysis situations could be formulated, depending on the factors and the response variables selected. In this section the effect of the following factors on the plant profitability will be examined: • The annual operating time (break-even analysis), and the product price • The resources prices (raw materials, labor, utilities, equipment) • The economic environment (e.g., tax and debt characteristics) a. Break-Even Analysis A typical break-even analysis is presented in Figure 7.1e. The three crucial operating magnitudes, that is, the annual sales income, the annual manufacturing cost, and the corresponding annual gross profit are plotted versus the annual operating time. The profit curve indicates three characteristic points:

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• The lower break-even point • The maximum profit point • The upper break-even point It is obvious that the plant operation in the range between the lower and the upper break-even points is profitable. The optimum operating point happens to an annual operating time of about 1000 h, which corresponds to operation of 2 shifts daily for 5 days per week. The optimum is not sharp and consequently an annual operating time between 500 and 1200 h is accepted, as near optimum operation. These results are further analyzed in Figure 7.1f, which presents the profit versus the annual operating time for three different values of the product price. The main conclusion suggests that when the product price approaches the value of 2.25 $/kg, the annual operating time should be decreased to about 500 h (1shift per day, 5 days per week). Instead, when higher value of product price is expected, the annual operating time should be increased to about 1500 h (3 shifts per day, 5 days per week). In conclusion, these graphs reveal the economical operation of the plant and suggest the required changes in order to match external changes in the economic environment of the plant. In a world of rapid changes, the plant flexibility is a crucial matter towards profitability. b. Effect of Resource Prices and Tax and Debt Characteristics Figure 7.1g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

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10 1 shift

2 shifts

+ weekends

3 shifts

Annual income/outcome (M$/y)

.

8

6 Sales Manufacturing cost 4

2

Profit

0 0

500

1000

1500

2000

2500

Annual operating time (h/y)

Figure 7.1e Break-even analysis of the tomato paste plant. 2.0

Annual profit (M$/y)

Product price ($/kg) = 1.5

1.0

2.75 2.50

0.5

2.25

0.0 0

500

1000

1500

Annual operating time (h/y)

Figure 7.1f Break-even analysis of the tomato paste plant.

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2500

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3.00 Ceq

Capital Return Ratio

.

2.00 1.00 0.00

CL Cr

Cb

Cb

-1.00

Cr CL

-2.00

Ceq

-3.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

Relative variation

1.00

Capital Return Ratio

.

i

L

0.50

0.00

t iL iL t

L -0.50

i -1.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

Relative variation

Figure 7.1g Sensitivity analysis of the tomato paste plant.

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0.30

0.40

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II. ORANGE JUICE CONCENTRATE PLANT 1. Process Technology a. Raw Materials Fruit varieties used for processing of orange juice concentrate include Valencia and Navel oranges. Mature oranges of proper solids content (at least 8 oBrix in Florida) are required. The fruit maturity is expressed by the oBrix/acid ratio, which should be at least 8 (California) or 10 (Florida).The oBrix value is the % soluble solids (sugar), measured with a refractometer. The acid is expressed as % by weight of citric acid (Kimbal, 1999; Nagy et al., 1993). Oranges are harvested and processed during the winter months, i.e. December to March in the northern Hemisphere. They are transported to the food plant by trucks in boxes or in bulk, and they can be stored, usually in bulk, for up to one week before processing. Spoilage of the fruit during transportation and storage is relatively small, due to the low ambient temperatures of the winter season. Oranges for processing are tested for % rot, fruit size, juice content, and o Brix/acid ratio. Rejected fruit is used for animal feed or it is dumped. Orange juice is an acid food with a pH in the range of 2.6–4.4, which facilitates thermal processing and preservation. b. Washing/Grading The oranges are transported from the storage area to the processing area usually in water flumes (hydraulic transport). The fruit is fed to the washing machines, in which the fruit is soaked in chlorinated water, brushed, and sprayed with pressurized water. The consumption of wash water is about 150 L/t of fruit. The washed oranges are graded for size, which facilitates the operation of the juice extractors. c. Juice Extraction /Finishing Orange juice is extracted in special FMC cup extractors or Brown reamers, each unit having a capacity of about 4 t/h of oranges. The extractors have a number of cups, which can receive a range of fruit sizes. The extractors should extract only a minimum amount of peel oil into the juice. The extracted juice contains large amounts of orange pulp, which is removed down to about 12% in the juice finishers. The cylindrical finishers operate in two stages, pressing the juice through screens (openings of 1.0 and 0.5 mm), using screws or paddles. The extractors should extract only a minimum amount of peel oil into the juice (Saravacos and Kostaropoulos, 2002).

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d. Centrifuging/Debittering In order to facilitate concentration of the juice (reduced viscosity), the pulp content can be removed down to 3–5% using centrifugal separators or ultrafiltration membranes. Bitter components and excessive acidity of some orange juices can be removed by ion exchange treatment, using special resins. Ion exchange columns require clarified orange juice, which is prepared by centrifugation or ultrafiltration. The orange juice used in this application example requires no debittering treatment. e. Juice Pasteurization The orange juice must be pasteurized before further processing in order to reduce the spoilage microorganisms and inactivate the pectic enzymes, which may reduce the juice viscosity by breaking down the pectins. High temperature short time pasteurization at 90–95oC for 15–60 s may be applied, using plate heat exchangers. Pasteurization of juice destined for evaporation may be omitted, if the juice is processed immediately after extraction and a high temperature short time evaporator, e.g., the TASTE system, is used. f. Juice Concentration The orange juice is concentrated in multiple–effect falling film evaporators from about 12 to 65 oBrix. The high temperature short time evaporation (TASTE) system is used, since the heat–sensitive juice is subjected to high temperature only for a short residence time (Chen and Hernandez 1997). Multiple effect systems reduce substantially the steam requirements of evaporation. A 4–effect system is commonly used in citrus juice concentration, although more effects are also applied. A combined multiple effect evaporator– mechanical vapor recompression system can reduce further the energy (steam) requirements (Maroulis and Saravacos, 2003). The volatile flavor components of orange juice can be recovered as a concentrated essence solution, using a stripping–distillation system, combined with the juice evaporator (Sarravacos and Kostaropoulos, 2002). No volatile flavor recovery is used in this application example. g. Aseptic Packing and Storage The orange juice concentrate (65 oBrix) is cooled to about 0oC in a scraped surface heat exchanger. The product is usually packed aseptically in 55 gallons (208 L) drums, lined with a polyethylene film. The aseptically packed orange juice concentrate can be stored at refrigeration temperatures (0–2oC) for 6–12 months.

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The orange juice concentrate (65 oBrix) can be stored aseptically in larger containers and tanks up to 400 t capacity, which are kept at about 0oC for up to 1 year. It can be transported in refrigerated tanks or boats for re–processing, food service, and institutional use. h. Peel/Pulp Drying The peels and the pulp, separated from the orange juice, are mixed and pressed in a continuous press, and then dried to a moisture content of less than 10%, using a rotary air–dryer. The dried product is used as an animal feed, and relatively high drying temperatures can be used, without significant damage to the product nutritive value. Natural gas or LPG is a suitable fuel for supplying the required energy for drying. i. Peel Oil Extraction The orange peels, after extraction of the orange juice, are normally used to recover the peel oil, which is sold as valuable byproduct. The oil is expressed by mechanical pressing, emulsification in water, and centrifugation (Kimball, 1999). j. Plant Effluents The solid orange wastes (peels, seeds etc.) are usually dehydrated to produce animal feed. The plant wastewater of large installations may require secondary treatment before discharging to the environment. 2. Process Flowsheet A material and energy balance diagram of the orange juice plant is shown in Figure 7.2a. The balances are based on an 1 kg product. Thus, 10.85 kg of oranges are required for 1 kg orange juice concentrate. In the same diagram the utilities requirements are presented in kWh/kg, excluding electricity. The requirements in electricity will be presented in the next paragraphs after the equipment sizing procedure. A process flowsheet based on the above technology is presented in Figure 7.2b. The flowsheet depicts the main processes and defines their interrelations. The basic assumption is that the examined system consists of a processing plant with central utilities, e.g., steam, cooling water, waste treatment, etc. Thus, the utilities system is not included in the flowsheet, but an operating allocated cost is considered in the cost analysis section. The waste solids of the plant, consisting mainly of orange peels, are dehydrated and sold as animal food (a plant byproduct). The waste water is disposed to a sewage system or it is used for irrigation.

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197

10.85 kg 13.6 %

Water

Washing

Waste

10.85 kg

10.85 kg

Inspecting

Juice extraction

Oil extraction

Peels

Oil

5.20 kg Pulp/Juice

0.03 kg

5.65 kg

Finishing

5.17 kg

Mixing

Pulp 0.23 kg

Juice

5.42 kg

5.40 kg

12.0 % 0.08 kWh Pasteurizing

Drying

0.1 kWh

Water

3.15 kWh

4.5 kg 0.90 kg

3.09 kWh Evaporators

Water

3.09 kWh

4.42 kg

Juice Concentrated

1.00 kg 65.0 %

Cooling 0.15 kWh

Packaging

Steam

Cooling water

Figure 7.2a Material and energy balances in the orange juice concentrate plant.

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Chapter 7 3 Juice extraction

W

R

L

C

2 Inspecting

L

1 Washing S

4 Finishing 5 Pasteurizing

s

c

10 Mixing

F

P 9 Oil extraction

G

A

G

12 Condenser 11 Dryer

P

C

6 Evaporators

c S s

C

K

P

c

7 Cooling

8 Packaging

Figure 7.2b Process flowsheet of the orange juice concentrate plant.

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w

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3. Material and Energy Requirements Table 7.2a lists the material and energy requirements of the orange juice concentrate plant, based on the material and energy diagram of Figure 7.2a. The annual data corresponds to 1280 h/y, according to the operating scheme described in the next paragraph. The labor refers only to seasonal unskilled workers which is obtained by the process counting method (See Chapter 6). The supervising and technical support is taking into account using the factorial method (Chapter 6). The packaging material refers to 208 L plastic drums. Table 7.2a Material and Energy Requirements of an Orange Juice Plant Per Product

Hourly basis

Annual

Products Orange juice

1.00 kg/kg

1.00 t/h

1 280 t/y

Dried peels

0.90 kg/kg

0.90 t/h

1 150 t/y

Peel oil

0.03 kg/kg

0.03 t/h

38 t/y

10.85 kg/kg 230 kg/p

10.9 t/h 4 p/h

13 890 t/y 5 570 p/y

Raw materials Raw Materials Packaging Material

Fr. Fg.

Utilities Process Water Electricity

Fw. Fe.

1.93 kg/kg 0.12 kWh/kg

1.93 t/h 0.12 MW

2 470 t/y 150 MWh/y

Steam

Fs.

3.18 kWh/kg

3.18 MW

4 060 MWh/y

Cooling Water

Fc.

3.33 kWh/kg

3.33 MW

4 260 MWh/y

Refrigeration

Fz.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fuel

Ff.

3.15 kWh/kg

3.15 MW

4 030 MWh/y

Wh Wastes Waste Treatment

Fj.

10.85 kg/kg

M.

15.0 h/t

10.9 t/h

13 890 t/y

15.0 p

19 200 h/y

Labor Manpower

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4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 7.2a are estimated and the results are summarized in Table 7.2b. The most expensive equipment refers to a tubular 4-effect evaporator. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 7.2c. Table 7.2b Equipment Cost Estimation of an Orange Juice Concentrate Plant No

Process

Qty

1

Washing

2

Size Units 5 t/h

Cost 50

2

Inspecting

2

10 m2

40

3

Juice extraction

1

10 t/h

100

4

Finishing

1

5 t/h

50

5

Pasteurizing

1

80 m2

80

6

Evaporators

4

30 m2

700

7

Cooling

1

15 m2

20

8

Aseptic packaging

1

1 t/h

200 100

9

Oil extraction

2

5 t/h

10

Mixing

1

1 m3

20

11

Dryer

1

100 m2

240

12

Condenser

1

30 m3

20 1620 k$

Table 7.2c Capital Cost Estimation of an Orange Juice Concentrate Plant Purchased Equipment Cost

Ceq

1.62 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost

CF

Working Capital Cost

CW

Total Capital Cost

CT

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5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 7.2d and the results are summarized in Table 7.2e and in Figure 7.2c. The cost of raw material, the labor, and the utilities (steam and fuel) are the major components of the product cost. The annual operating time refers to 16 week per year, 5 days per week, 2 shifts per day, and 8h per shift. Table 7.2d Assumptions for Operating Cost Estimation Orange juice Plant Product Rate

PR

Operating Season

wpy

1.00 t/h 16 w/y

Annual Operating Time

ty

1280 h/y

Operating Cost Factors Data Fixed Manufacturing Cost Factor Overhead Cost Factor

fMF fOver

0.10 0.05 -

Utilities Cost Crude Oil Cost Fuel Cost

Cb. Cf.

67.0 $/bbl 0.07 $/kWh

Electricity Cost

Ce.

0.11 $/kWh

Steam Cost Cooling Water Cost

Cs. Cc.

0.08 $/kWh 0.01 $/kWh

Freezing Cost

Cz.

Process Water Unit Cost

Cw.

0.50 $/m3

0.11 $/kWh

Waste Treatment Cost

Cj.

5 $/m3

Labor Cost Characteristics Labor Rate Cost

CL

15.0 $/h

Labor Cost Correction Factor

fL

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00 -

3.60 $/kg

Material Unit Cost Product

Cp.

Raw Materials

Cr.

Packaging Material

Cg.

0.12 $/kg 20.00 $/p

The product price (3.60 $/kg) includes the value of the by-products, expressed in $/kg of orange juice concentrate: Orange juice concentrate, 3.10 $/kg; dried peels, 0.20 $/kg; peel oil, 0.30 $/kg.

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Table 7.2e Operating Cost Estimation of the Orange Juice Concentrate Plant Manufacturing Cost Raw Materials

Cmat

Packaging

Cpack

1.67 0.11

Utilities Waste Treatment

Cutil Cwst

0.65 0.07

Labor Variable Manufacturing

Clab Cmv

0.72 3.21

Fixed Manufacturing Overheads

Cmf Cover

0.49 0.23

Manufacturing Capital Charge

CM e CT

3.93 M$/y 0.50 -

Total Annualized

TAC

4.43 M$/y

Unit Cost ($/kg)

…

4.00 3.50 Capital Charge 3.00

Fixed

Overheads

Manufacturing

2.50 Labor Waste

2.00 1.50

Treatment

Utilities Packaging

1.00 0.50

Raw Materials

0.00 1 Cost Operating

Figure 7.2c Operating cost estimation of the orange juice concentrate plant.

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6. Plant Profitability A plant profitability analysis of the design and economics of the orange juice concentrate plant was performed according to the procedure described for the tomato paste plant (see Section I.6 of this chapter). Similar results were obtained. The assumptions for the plant profitability estimation are summarized in Table 7.1f of this chapter. Figure 7.2d presents the annual cash flow CCF, the cumulated cash flow CCF, and the net present value NPV of the orange juice concentrate plant during its lifetime. The characteristic economic quantities are indicated in this Figure: Depreciated period ND, loan payment period NL, positive salvage period NS, and project life time NE. The simple payback period SPB and the depreciated payback period DPB are obtained as the intercepts with the time axis of the CCF and NPV curves, respectively. Based on these data, the resulting profitability indices are also summarized in Table 7.2f. Table 7.2f Plant Profitability of the Orange Juice Concentrate Plant Profitability Sales Income

S

4.61 M$/y

Manufacturing Cost Gross Profit

CM Pg

3.93 M$/y 0.68 M$/y

Net Present Value

NPV

1.30 M$

Own Capital Cost

Co

Capital Return Ratio

CRR

0.43 -

Internal Rate of Return

IRR

0.12 -

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Cash flow (M$)

1.0

Tax Tax Reduction

0.5

Net Profit

Loan Payment 0.0 1

2 3

4 5

6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Operating year

3

CCF

Net present value / Own Capital

2

1 NPV

0 0

5

-1

10

ND

15

20

NL

25

NS

30

NE

-2 Operating year

Figure 7.2d Annual cash flow (upper) and cumulated cash flow (CCF) and net present value (NPV) of the orange juice concentrate plant.

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7. Sensitivity Analysis A sensitivity analysis of the orange juice concentrated plant was performed according to the procedure described for the tomato paste plant (see Section 1.7 of this chapter). Similar results were obtained. Figure 7.2e shows the three characteristic points of the break-even analysis with an optimum at an annual operating time of about 1000 h, corresponding to operation of 2 shifts daily for 5 days per week. Figure 7.2.f presents the annual profit for three different values of the product price. Figure 7.2g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL, and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

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10

2 shifts

1 shift

+ weekends

3 shifts

Annual income/outcome (M$/y)

.

8

6

Sales 4

Manufacturing cost

2 Profit

0 0

500

1000

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.2e Break-even analysis of the orange juice concentrate plant. 1.5

Annual profit (M$/y)

Product price ($/kg) =

1.0

0.5

3.15 4.05

3.50 4.50

3.85 4.95

0.0 0

500

1000

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.2f Break-even analysis of the orange juice concentrate plant (the product price includes the value of the by-products).

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2.00

Capital Return Ratio

.

Cr 1.00

Ceq CL Cb

0.00 Cb -1.00

Ceq CL

Cr

-2.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

Relative variation

Capital Return Ratio

.

1.00

0.50

i

L

t 0.00

iL

iL t

L

i

-0.50

-1.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

Relative variation

Figure 7.2g Sensitivity analysis of the orange juice concentrate plant.

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0.40

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III. UHT STERILIZED MILK PLANT 1. Process Technology Commercial milk (cow’s or other milking animal) is preserved by pasteurization, sterilization, or dehydration (spray drying). Fresh milk is pasteurized in continuous flow equipment at 72oC for 15s and it is preserved in refrigeration for about 1 week. The shelf life of pasteurized milk can be extended beyond one week by high temperature pasteurization at 85oC for 2s. Ultra high temperature (UHT) processing of milk at 135oC for 2s and aseptic packaging will sterilize the milk and preserve it for longer time (Lewis and Heppell, 2000). a. Raw Material The plant will use cow’s milk from nearby dairy farmers. The milk will be transported to the processing plant with refrigerated truck tanks, where it will be stored for a short time in refrigerated tanks. The raw cow milk contains 12% TS, including 3.5% fat. b. Separation/Homogenization The milk is first clarified in centrifugal separators, and the fat content is reduced to 2.0 %. in a centrifugal separator. The milk is subsequently homogenized in a high pressure homogenizer at 200 bar and 55oC. c. UHT Sterilization The milk is sterilized in a continuous flow system using steam injection (Maroulis and Saravacos, 2003; Lewis and Heppel, 2000). d. Aseptic Packaging The sterilized milk is packaged aseptically in 1 liter paper cartons, using an automatic form–fill–seal (FFS) system (Saravacos and Kostaropoulos, 2002). 2. Process Flowsheet A material and energy balance diagram of the UHT sterilized milk plant is shown in Figure 7.3a. The balances are based on 1 kg product. Thus, 1.08 kg of raw milk is required for 1 kg UHT sterilized milk. In the same diagram the utilities requirements are presented in kWh/kg, excluding electricity. The requirements in electricity will be presented in the next paragraphs after the equipment sizing procedure. A process flowsheet based on the above technology is presented in Figure 7.3b. The flowsheet depicts the main processes and defines their interrelations. The basic assumption is that the examined system consists of a process-

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ing plant with central utilities, e.g., steam, cooling water, waste treatment, etc. Thus, the utilities system is not included in the flowsheet, but an operating allocated cost is considered in the cost analysis section. Steam (S) is used in homogenization (No. 3) and sterilization (No. 4). Cooling water (C) is used in sterilization (No. 4). Process water (W) is used in equipment washing. Milk

1.08 kg

Storage

Centrifugal

Cream 0.08 kg

1.00 kg

Homogenization

0.015 kWh Sterilization 0.015 kWh Cartons Packaging 1.00 kg

Steam

Cooling water

Figure 7.3a Material and energy balances in the UHT sterilized milk plant.

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1 Storage

R

P

S

2 Centrifugal

S

s

C 3 Homogenization 4 Sterilization

s Z

c

z

K 5 Packaging 6 Cold Storage

Figure 7.3b Process flowsheet of the UHT sterilized milk plant.

3. Material and Energy Requirements Table 7.3a lists the material and energy requirements of the UHT sterilized milk plant, based on the material and energy diagram of Figure 7.3a. The annual data corresponds to 3840 h/y, according to the operating scheme described in the next paragraph. The Labor refers only to production workers and it is obtained by the process counting method (See Chapter 6). The supervising, and technical support is taken into account using the factorial method (Chapter 6). The packaging material refers to 1 L paper cartons.

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Table 7.3a Material and Energy Requirements of the HUT Sterilized Milk Plant Per Product

Hourly basis

Annual

Products Milk

1.00 kg/kg

2.00 t/h

7 680 t/y

Raw materials Raw Materials

Fr.

1.08 kg/kg

Packaging Material

Fg.

1.00 p/kg

2.2 t/h

8 290 t/y

2000 p/h

7 680 000 p/y

8 290 t/y

Utilities Process Water

Fw.

1.08 kg/kg

2.16 t/h

Electricity

Fe.

0.06 kWh/kg

0.12 MW

460 MWh/y

Steam

Fs.

0.02 kWh/kg

0.04 MW

150 MWh/y

Cooling Water

Fc.

0.02 kWh/kg

0.04 MW

150 MWh/y

Refrigeration

Fz.

0.08 kWh/kg

0.16 MW

610 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

1.08 kg/kg

Wastes Waste Treatment

2.2 t/h

8 290 t/y

Labor Manpower

M.

2.5 h/t

5.0 p

19 200 h/y

4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 7.3a are estimated and the results are summarized in Table 7.3b. The most expensive equipment refers to the packaging equipment. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 7.3c. The detailed design of the sterilizing equipment is discussed, using application examples, by Maroulis and Saravacos (2003). The required thermal and transport properties of the system were taken from the related Tables of the Appendix.

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Table 7.3b Equipment Cost Estimation of the UHT Sterilized Milk Plant No

Process

Qty

1

Storage

1

50.0 m3

Size Units

50

2

Centrifuge

1

2.50 t/h

100

4

Homogenizer

1

2.50 t/h

150

5

Sterilizer

1

400 m2

250 600

6

Packaging

1

2.00 t/h

7

Cold Storage

1

250 t

Cost

50 1200 k$

5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 7.3d and the results are summarized in Table 7.3e and in Figure 7.3c. The cost of raw material is the major component of the product cost, followed by labor and packaging costs. A labor rate of 15 $/h was assumed, which is representative of unskilled production workers. The annual operating time refers to 48 week per year, 5 days per week, 2 shifts per day, and 8h per shift. Table 7.3c Capital Cost Estimation of the UHT Sterilized Milk Plant Purchased Equipment Cost

Ceq

1.20 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost

CF

Working Capital Cost

CW

Total Capital Cost

CT

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Table 7.3d Assumptions for Operating Cost Estimation Milk UHT Plant Product Rate

PR

Operating Season

wpy

2.00 t/h 48 w/y

Annual Operating Time

ty

3840 h/y

Operating Cost Factors Data Fixed Manufacturing Cost Factor

fMF

0.10 -

Overhead Cost Factor

fOver

0.05 -

Utilities Cost Crude Oil Cost

Cb.

67.0 $/bbl

Fuel Cost

Cf.

0.07 $/kWh

Electricity Cost

Ce.

0.11 $/kWh

Steam Cost

Cs.

0.08 $/kWh

Cooling Water Cost

Cc.

0.01 $/kWh

Freezing Cost

Cz.

Process Water Unit Cost

Cw.

0.50 $/m3

Waste Treatment Cost

Cj.

5 $/m3

0.11 $/kWh

Labor Cost Characteristics Labor Rate Cost

CL

15.0 $/h

Labor Cost Correction Factor

fL

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00 -

0.92 $/kg

Material Unit Cost Product

Cp.

Raw Materials

Cr.

0.30 $/kg

Packaging Material

Cg.

0.08 $/p

The material unit cost of the product (0.92 $/kg) is UHT sterilized milk. The cost of the separated milk fat is neglected (relatively small quantity).

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Table 7.3e Operating Cost Estimation of the UHT Sterilized Milk Plant

Manufacturing Cost Raw Materials

Cmat

2.96

Packaging

Cpack

0.61

Utilities

Cutil

0.13

Waste Treatment

Cwst

0.04 0.90

Labor

Clab

Variable Manufacturing

Cmv

4.65

Fixed Manufacturing

Cmf

0.36

Overheads

Cover

Manufacturing

CM

0.30

Capital Charge

e CT

0.42 -

Total Annualized

TAC

5.73 M$/y

5.30 M$/y

Unit Cost ($/kg)

…

1.00

Fixed

Capital Charge Overheads

Manufacturing

0.50

Labor

Utilities

Waste Treatment Packaging

Raw Materials

0.00 1 Cost Operating

Figure 7.3c Operating cost estimation of the HUT sterilized milk plant.

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6. Plant Profitability A plant profitability analysis of the design and economics of the UHT sterilized milk plant was performed according to the procedure described for the tomato paste plant (see Section I.6 of this chapter). Similar results were obtained. The assumptions for the plant profitability estimation are summarized in Table 7.1f of this chapter. Figure 7.3d presents the annual cash flow CCF, the cumulated cash flow CCF, and the net present value NPV of the orange juice concentrate plant during its lifetime. The characteristic economic quantities are indicated in this Figure: Depreciated period ND, loan payment period NL, positive salvage period NS, and project life time NE. The simple payback period SPB and the depreciated payback period DPB are obtained as the intercepts with the time axis of the CCF and NPV curves, respectively. Based on these data, the resulting profitability indices are summarized in Table 7.3f. Table 7.3f Plant Profitability of the UHT Sterilized Milk Plant Profitability Sales Income

S

5.94 M$/y

Manufacturing Cost

CM

5.30 M$/y

Gross Profit

Pg

0.64 M$/y

Net Present Value

NPV

1.47 M$

Own Capital Cost

Co

2.54 M$

Capital Return Ratio

CRR

0.58 -

Internal Rate of Return

IRR

0.13 -

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Cash flow (M$)

1.0

Tax Reduction

0.5

Tax

Net Profit

Loan Payment 0.0 1

2 3

4 5

6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Operating year

3 CCF

Net present value / Own Capital

2

1 NPV

0 0

5

-1

10

ND

15

20

NL

25

NS

30

NE

-2 Operating year

Figure 7.3d Annual cash flow (upper) and cumulated cash flow (CCF) and net present value (NPV) of the UHT sterilized milk plant.

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7. Sensitivity Analysis A sensitivity analysis of the UHT sterilized milk plant was performed according to the procedure described for the tomato paste plant (see Section 1.7 of this chapter). Similar results were obtained. Figure 7.3e shows the three characteristic points of the break-even analysis with an optimum at an annual operating time of about 2000 h, corresponding to operation of 2 shifts daily for 5 days per week. Figure 7.3.f presents the annual profit for three different values of the product price. Figure 7.3g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL, and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

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10 1 shift

2 shifts

+ weekends

3 shifts

Annual income/outcome (M$/y)

.

8

6

4 Sales

Manufacturing cost

2 Profit

0 0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Annual operating time (h/y)

Figure 7.3e Break-even analysis of the UHT sterilized milk plant. 1.5

Annual profit (M$/y)

Product price ($/kg) = 1.0

1.01

0.5 0.83

0.92

0.0 0

1000

2000

3000

4000

5000

6000

7000

8000

Annual operating time (h/y)

Figure 7.3f Break-even analysis of the UHT sterilized milk plant.

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10000

Food Preservation Plants

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3.00

Cr Ceq

Capital Return Ratio

.

2.00 1.00 0.00

CL Cb

Cb

-1.00

Ceq CL

-2.00

Cr

-3.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

Relative variation

Capital Return Ratio

.

1.00

0.50

i

L

t 0.00

iL

iL t

L -0.50

i

-1.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

Relative variation

Figure 7.3g Sensitivity analysis of the UHT sterilized milk plant.

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0.30

0.40

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IV. FRUIT CANNING PLANT 1. Process Technology a. Raw Materials The economics of canning of two different commercial fruits, i.e. apricots and peaches, is analyzed in this application example. Both fruits can be processed in the same equipment with some minor variations. They mature and are available for processing in a short time during the summer (northern Hemisphere), apricots in June–July and peaches in August–September. Thus, a combined apricot–peach processing plant can operate for a 4-month period per year, improving the economics of the processing plant. The two fruits may be produced in two different agricultural areas, due to climate conditions, the apricots requiring warmer weather. In such a case, the processing plant may be located near the growing areas of the major fruit, e.g., peaches, while the other fruit is transported by truck to the plant. Apricots have a higher solids content, about 15%, compared to peaches (11%). Both fruits, destined for canning, should be mature with good color and pleasant flavor. Particular attention is placed on the texture of apricots, which should be firm after thermal processing. Both fresh fruits can be stored for a few days at 0–4oC and 85% RH before processing (Woodroof and Luh, 1986). Fruit varieties suitable for canning should be used, e.g., Blenheim apricots and clingtone peaches in the U.S. Apricots are usually canned unpeeled after halving and pitting, while some small fruit may be used as whole with pits. Peaches are normally pitted and peeled. b. Washing/Pitting/Peeling/Grading The fruit is first sorted for spoiled and unfit product and then washed with water in fruit-washing machines to remove any soil and unwanted material. The peaches are pitted mechanically by halving the fruit and removing the pits. The fruits are sorted by size and they are aligned before feeding the pitting machines. The minimum peach diameter for passing the U.S. grade is 6.0 cm. The halved peaches are peeled in a hot alkali solution, followed by thorough washing with water and a weak acid solution. Peach halves and peach slices are used in canning. The halved apricots are inspected and graded for size using screens of openings 3.18, 3.81, 4.45, 5.10, or 5.40 cm. Grades Fancy, Choice, and Standard are based not only on the size, but mainly on the color, texture, and absence of defects.

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b. Filling/Syruping The sound fruit halves are filled into the can in accordance to the required minimum fruit weight, e.g., 524 g of peaches for the No. 2 ½ cans. Liquid sugar (sucrose or corn syrup solutions of about 67 oBrix) is used to prepare the syrups, which fill the fruit–containing cans. The syrup strength is measured in the product after canning and equilibration (cut–out test). In peaches the “cut–out” syrup concentration is related to the grade of the canned product, e.g., Fancy > 26 oBrix, Choice > 21 oBrix, and Standard > 17 oBrix. c. Sealing/Sterilization of Cans The filled cans are pre–vacuumized and sealed in a double seaming machine, using a steam–flow sealer. The No 2½ cans of both fruits are sterilized at 100oC for 20 min in a still retort, or for 15 min in a agitating cooker. For adequate sterility, the minimum can center temperature should be 90oC prior to water cooling. The sterilized cans are cooled in a agitating water cooler to about 38oC. Chlorinated cooling water (2 ppm available chlorine) is used to prevent any microbial contamination during the cooling process. d. Labeling/Packing/Storage The cans are labeled mechanically and packed in cardboard cases containing 24 No. 2½ cans. The yield of peaches is about 55 standard cases per t of fruit. The peach and apricot cases can be stored at room temperature of about 20oC for up to one year before consumption. 2. Process Flowsheet A material and energy balance diagram of the fruit canning plant is shown in Figure 7.4a. The balances are based on an 1 kg product. In the same diagram the utilities requirements are presented in kWh/kg, excluding electricity. The requirements in electricity will be presented in the next paragraphs after the equipment sizing procedure. A process flowsheet based on the above technology is presented in Figure 7.4b. The flowsheet depicts the main processes and defines their interrelations. The basic assumption is that the examined system consists of a processing plant with central utilities, e.g., steam, cooling water, waste treatment, etc. Thus, the utilities system is not included in the flowsheet, but an operating allocated cost is considered in the cost analysis section.

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Apricots

Peaches

0.90 kg Water

Water 0.9 kg

1.02 kg

Waste

Washing

Washing

1.02 kg

Waste 1.02 kg

0.9 kg 1.02 kg

0.9 kg

Inspecting

Inspecting

Halving/Pitting

Halving/Pitting

Pits

Apricot halves

Pits 0.10 kg

0.09 kg Peach halves

0.81

0.075 kWh

0.92

Lye peeling

Peels 0.08 kg

0.84

Grading

By product

Grading

By product

0.04 kg

0.07 kg

0.77 Syrup

0.77 Syrup

0.23 kg

0.23 kg

Filling/Syruping Cans

Filling/Syruping Cans

1.00 kg

1.00 kg

Vacuum seaming

0.015 kWh

Vacuum seaming

0.015 kWh

Sterilization 0.015 kWh

Sterilization 0.015 kWh

Labeling/Casing

Labeling/Casing

1.00 kg

Steam

1.00 kg

Cooling water

Figure 7.4a Material and energy balances of the fruit canning plant.

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W

R

2 Inspecting

L

L

1 Washing

3 Halving

S 4 Lye peeling 5 Grading L

s R W

G

6 Syruping K

7 Filling

8 Vacuum seaming

C

S

c

s

P

10 Labeling/Casing

9 Sterilization

Figure 7.4b Process flowsheet of the fruit canning plant.

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Since the same equipment is used for both fruits, the analysis in the next paragraphs could be based on one of the following assumptions: • Charge the half of the equipment cost to each process and use the actual annual operating time. • Charge all the equipment cost to each process and use double the annual operating time The second assumption is used in this chapter in order to obtain the effect of the particular product characteristics on the plant profitability. 3. Material and Energy Requirements Table 7.4a lists the material and energy requirements of the fruit canning plant, based on the material and energy diagram of Figure 7.4a. The annual data corresponds to 1280 h/y, according to the operating scheme described in the next paragraph. The labor refers only to seasonal unskilled workers and it is obtained by the process counting method (see Chapter 6). The supervising, and technical support is taken into account using the factorial method (Chapter 6). The packaging material refers to 0.85 L metallic cans.

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Table 7.4a Material and Energy Requirements of the Fruit Canning Plant Apricot Per Product

Hourly basis

Annual

Products Appricot canned

1.00 kg/kg

2.00 t/h

2 560 t/y

Raw materials Raw Materials

Fr.

0.90 kg/kg

Packaging Material

Fg.

0.85 kg/p

1.8 t/h

2 300 t/y

2353 p/h

3 011 760 p/y

2.26 t/h

2 890 t/y

Utilities Process Water

Fw.

Electricity

Fe.

0.09 kWh/kg

1.13 kg/kg

0.17 MW

220 MWh/y

Steam

Fs.

0.02 kWh/kg

0.03 MW

40 MWh/y

Cooling Water Refrigeration

Fc. Fz.

0.02 kWh/kg 0.00 kWh/kg

0.03 MW 0.00 MW

40 MWh/y 0 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

1.03 kg/kg

Wastes Waste Treatment

2.1 t/h

2 640 t/y

Labor Manpower

M.

5.0 h/t

10.0 p

12 800 h/y

Peach Per Product

Hourly basis

Annual

Products Peach canned

1.00 kg/kg

2.00 t/h

2 560 t/y

Raw materials Raw Materials

Fr.

1.02 kg/kg

Packaging Material

Fg.

0.85 kg/p

2.0 t/h

2 610 t/y

2353 p/h

3 011 760 p/y

Process Water

Fw.

Electricity

Fe.

1.25 kg/kg

2.50 t/h

3 200 t/y

0.10 kWh/kg

0.19 MW

Steam

250 MWh/y

Fs.

0.09 kWh/kg

0.18 MW

230 MWh/y

Cooling Water Refrigeration

Fc. Fz.

0.02 kWh/kg 0.00 kWh/kg

0.03 MW 0.00 MW

40 MWh/y 0 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

1.27 kg/kg

Utilities

Wastes Waste Treatment

2.5 t/h

3 250 t/y

Labor Manpower

© 2008 by Taylor & Francis Group, LLC

M.

5.0 h/t

10.0 p

12 800 h/y

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4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 7.4a are estimated and the results are summarized in Table 7.4b. The sizing is based in the peaches data. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 7.4c. Table 7.4b Equipment Cost Estimation of the Fruit Canning Plant No

Process

Qty

1

Washing

1

Size Units 5 t/h

Cost 50

2

Inspecting

1

10 m2

20

3

Halving

1

2 t/h

50

4

Peeling

1

2 t/h

100

5

Grading

1

2 m2

30

6

Syrup tank

1

12 m3

30

7

Filling

1

2 t/h

200

8

Seaming

1

2 t/h

200

9

Sterilization

1

2 t/h

400

10

Labeling / Casing

1

2 t/h

200 1280 k$

Table 7.4c Capital Cost Estimation of the Fruit Canning Plant Purchased Equipment Cost

Ceq

1.28 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost

CF

3.84

Working Capital Cost

CW

0.89

Total Capital Cost

CT

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4.73 M$

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5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 7.4d and the results are summarized in Table 7.4e and in Figure 7.4c. The cost of raw materials is the major cost component, followed by the labor and the packaging costs. The annual operating time refers to 16 week per year, 5 days per week, 2 shifts per day, and 8h per shift. Table 7.4d Assumptions for Operating Cost Estimation of the Fruit Canning Plant Appricot canning Plant

Appricot

Peach

Product Rate

PR

2.00

Operating Season

wpy

16

2.00 t/h 16 w/y

Annual Operating Time

ty

1280

1280 h/y

Operating Cost Factors Data Fixed Manufacturing Cost Factor

fMF

0.10

0.10 -

Overhead Cost Factor

fOver

0.05

0.05 -

Crude Oil Cost

Cb.

67.0

67.0 $/bbl

Fuel Cost

Cf.

0.07

0.07 $/kWh

Electricity Cost

Ce.

0.11

0.11 $/kWh

Steam Cost

Cs.

0.08

0.08 $/kWh

Cooling Water Cost

Cc.

0.01

0.01 $/kWh

Freezing Cost

Cz.

0.11

Process Water Unit Cost

Cw.

0.50

0.50 $/m3

Waste Treatment Cost

Cj.

5

5 $/m3

Utilities Cost

0.11 $/kWh

Labor Cost Characteristics Labor Rate Cost

CL

15.0

15.0 $/h

Labor Cost Correction Factor

fL

2.50

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00

2.00 -

Material Unit Cost Product

Cp.

1.40

1.65 $/kg

Raw Materials

Cr.

0.30

0.40 $/kg

Packaging Material

Cg.

0.16

0.16 $/p

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Table 7.4e Operating Cost Estimation of the Fruit Canning Plant Manufacturing Cost

Manufacturing Cost

Raw Materials

Cmat

0.82

Raw Materials

Cmat

Packaging

Cpack

0.48

Packaging

Cpack

0.48

Utilities Waste Treatment

Cutil Cwst

0.03 0.01

Utilities Waste Treatment

Cutil Cwst

0.05 0.02

Labor Variable Manufacturing

Clab Cmv

0.60 1.95

Labor Variable Manufacturing

Clab Cmv

0.60 2.39

Fixed Manufacturing Overheads

Cmf Cover

0.35 0.15

Fixed Manufacturing Overheads

Cmf Cover

0.38 0.18

Manufacturing Capital Charge

CM e CT

2.45 M$/y 0.36 -

Manufacturing Capital Charge

CM e CT

2.95 M$/y 0.39 -

Total Annualized

TAC

2.81 M$/y

Total Annualized

TAC

3.34 M$/y

Appricot

Peach 1.50

1.00

Unit Cost ($/kg)

…

…

1.50

Unit Cost ($/kg)

1.24

Capital Charge Fixed

Overheads

Manufacturing

Capital Charge Fixed 1.00

Overheads

Manufacturing

Labor

Utilities

Waste

Labor

Utilities

Waste

0.50 Packaging

Treatment

Packaging

Treatment

0.50

Raw Materials Raw Materials 0.00

0.00

1 Cost Operating

1 Cost Operating

Apricot

Peach

Figure 7.4c Operating cost estimation of the fruit canning plant. 6. Plant Profitability A plant profitability analysis of the design and economics of the fruit canning plant was performed according to the procedure described for the tomato paste plant (see Section I.6 of this chapter). Similar results were obtained. The assumptions for the plant profitability estimation are summarized in Table 7.1f of this chapter. Figure 7.4d presents the annual cash flow CCF, the cumulated cash flow CCF and the net present value NPV of the orange juice concentrate plant during its lifetime. The characteristic economic quantities are indicated in this Figure: Depreciated period ND, loan payment period NL, positive salvage period NS, and project life time NE. The simple payback period SPB and the depreciated payback period DPB are obtained as the intercepts with the time axis of the CCF and NPV curves, respectively. Based on these data, the resulting profitability indices are also summarized in Table 7.4f.

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Tax Reduction

0.5

Cash flow (M$)

Cash flow (M$)

1.0

Tax

Tax Reduction

0.5

Tax

Net Profit

Net Profit

Loan Payment

Loan Payment

0.0

0.0 1

2 3

4 5

6

7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

1

2 3

4 5

6

7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Operating year

Operating year

3

3

CCF

CCF

2

1

NPV

0 0

-1

5

10

ND

15

20

NL

-2

25

NS

30

NE

Net present value / Own Capital

Net present value / Own Capital

2

1

NPV

0 0

-1

5

10

ND

15

20

NL

25

NS

30

NE

-2

Operating year

Apricot

Operating year

Peach

Figure 7.4d Annual cash flow of the fruit canning plant. 7. Sensitivity Analysis A sensitivity analysis of the fruit canning plant was performed according to the procedure described for the tomato paste plant (see Section 1.7 of this chapter). Similar results were obtained. Figure 7.4e shows the three characteristic points of the break-even analysis with an optimum at the operating time of 1200 h, corresponding to operation of 2 shifts daily for 5 days per week. Figure 7.4.f presents the annual profit for three different values of the product price. Figure 7.4g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL, and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

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Table 7.4f Plant Profitability of the Fruit Canning Plant Apricot Profitability Sales Income

S

3.01 M$/y

Manufacturing Cost Gross Profit

CM Pg

2.45 M$/y 0.56 M$/y

Net Present Value

NPV

Own Capital Cost

Co

Capital Return Ratio

CRR

0.73 -

Internal Rate of Return

IRR

0.15 -

1.57 M$ 2.15 M$

Peach Profitability Sales Income

S

3.55 M$/y

Manufacturing Cost Gross Profit

CM Pg

2.95 M$/y 0.60 M$/y

Net Present Value

NPV

1.59 M$

Own Capital Cost

Co

2.36 M$

Capital Return Ratio

CRR

0.67 -

Internal Rate of Return

IRR

0.14 -

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2 shifts

1 shift

231

10

+ weekends

3 shifts

2 shifts

1 shift

+ weekends

3 shifts

8

Annual income/outcome (M$/y)

Annual income/outcome (M$/y)

.

.

8

6

4 Sale Manufacturing 2

6

4 Sale Manufacturing 2

Profit

Profit

0

0 0

500

1000

1500

2000

2500

3000

3500

0

500

1000

Annual operating time (h/y)

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.4e Break-even analysis of the fruit canning plant. 1.5

1.5 Product price ($/kg) = Annual profit (M$/y)

Annual profit (M$/y)

Product price ($/kg) = 1.0

0.5

1.54

1.40 1.26

0.0

1.0

0.5

1.65

1.82

1.49

0.0 0

500

1000

1500

2000

2500

3000

3500

0

500

1000

Annual operating time (h/y)

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.4f Effect of raw material price on the profit of the fruit canning plant. 2.00

2.00 Cr

Capital Return Ratio

1.00

0.00

.

Cr

1.00

CL

Capital Return Ratio

.

Ceq

Cb

Cb

CL Ceq Cr

-1.00

0.00

Ceq CL Cb

Cb

CL Ceq

-1.00

Cr -2.00 -0.40

-2.00 -0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

-0.40

-0.30

-0.20

Relative variation

0.00

0.10

0.20

0.30

0.40

Relative variation

1.00

1.00

.

.

i

0.50

L Capital Return Ratio

0.50 Capital Return Ratio

-0.10

t 0.00

iL

iL

L

t i

-0.50

-1.00 -0.40

i

L

t 0.00

iL

iL t

L

i

-0.50

-1.00 -0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

-0.40

-0.30

-0.20

Relative variation

Apricot

0.00

0.10

Relative variation

Peach

Figure 7.4g Sensitivity analysis of the fruit canning plant.

© 2008 by Taylor & Francis Group, LLC

-0.10

0.20

0.30

0.40

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V. VEGETABLE FREEZING PLANT 1. Process Technology a. Raw Materials The economics of freezing of two different commercial vegetables, i.e. green peas and green beans, is analyzed in this application example. Both vegetables can be processed in the same plant with some variations in the processing equipment. They mature and are available for processing in a short time during the summer period (northern Hemisphere). Thus, a combined green pea–green bean processing plant can operate for a 4-month period per year, making the plant more economical. Vegetables of highest quality should be used for freezing, in terms of color, flavor, tenderness, and lack of defects. Lower quality vegetable raw materials could be used in thermal processing (canning) or dehydration. Green peas are harvested mechanically in the U.S. and they are transported immediately by truck to the processing plant. The peas are vined (removed from the clusters and shells) either in the field or in the plant. Green beans are harvested by hand or mechanically. The tenderness and size of green peas and beans are very important in both frozen products. Texture, size, and specific gravity measurements are necessary in determining the quality of raw materials for freezing. Tender green vegetables deteriorate rapidly after harvesting and they should be processed and frozen immediately after harvesting, in order to maintain high quality. b. Cleaning/Grading/Cutting Both vegetables are cleaned from dirt and external materials before further processing. The cleaned vegetables are separated for size before blanching and freezing. The green beans are graded into 6 sizes according to the thickness. The bean pods are snipped mechanically to remove the stems and the tips. The snipped beans are cut mechanically into pieces 2.54–3.81 cm (Luh and Woodroof, 1986). c. Blanching Blanching of both vegetables before freezing is necessary to prevent flavor deterioration (enzymatic oxidation) during storage. Green peas are blanched in steam at 100oC for 1½ minutes, while blanching of cut green beans requires 3 min. The blanched vegetables are cooled rapidly in cold water to prevent quality degradation.

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d. Freezing/Packing Peas are usually frozen in a fluidized bed (individually quick freezing, IQF). Freezing in consumer packages (waxed cartons) may be also used. Frozen peas are packed in 208 L (55 gallon) fiberboard drums, lined with polyethylene film (Cleland and Valentas, 1997). Cut green beans are usually packaged in individual waxed cartons 3 cm thick and frozen in air–blast freezers (straight or helical conveyor belts). e. Storage Bulk–packed or individually packaged vegetables are stored at –18oC for several months. They are transported and distributed to the consumers as frozen products. 2. Process Flowsheet A material and energy balance diagram of the vegetable freezing plant is shown in Figure 7.5a. The balances are based on an 1 kg product. In the same diagram the utilities requirements are presented in kWh/kg, excluding electricity. The requirements in electricity will be presented in the next paragraphs after the equipment sizing procedure. A process flowsheet based on the above technology is presented in Figure 7.5b. The flowsheet depicts the main processes and defines their interrelations. The basic assumption is that the examined system consists of a processing plant with central utilities, e.g., steam, cooling water, waste treatment, etc. Thus, the utilities system is not included in the flowsheet, but an operating allocated cost is considered in the cost analysis section. Since the same equipment is used for both vegetables, the analysis in the next paragraphs could be based on one of the following assumptions: • Charge the half of the equipment cost to each process and use the actual annual operating time. • Charge all the equipment cost to each process and use double the annual operating time. The second assumption is used in this chapter in order to obtain the effect of the particular product characteristics on the plant profitability. 3. Material and Energy Requirements Table 7.5a lists the material and energy requirements of the vegetable freezing plant, based on the material and energy diagram of Figure 7.5a. The annual data corresponds to 1280 h/y, according to the operating scheme described in the next paragraph.

© 2008 by Taylor & Francis Group, LLC

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Chapter 7

The labor refers only to seasonal unskilled workers which is obtained by the process counting method (see Chapter 6). The supervising, and technical support is taken into account using the factorial method (Chapter 6). The packaging material refers to 208 L fiber board drums for green peas and 0.5 kg waxed paper cartons for green beans. Grean beans

1.18 kg

Water 1.18 kg

Waste

Cleaning

1.18 kg

Pea vines

1.18 kg

Pod separation

Vining

Rejects

Shells

0.06 kg Beans

Green peas

1.12 kg

Size Separation

Waste

Grading

1.15 kg

Peas

1.06 kg

Waste

Cutting

Rejects 0.10 kg

0.06 kg

1.05 kg

Blanching

0.15 kWh

0.06 kg Beans

0.15 kWh

1.00 kg

Inspecting

Blanching

Rejects 0.05 kg

Peas

1.00 kg

Cartons

Freezing

Packaging

Frozen peas Drums Packaging

Freezing Frozen beans

Frozen peas

1.00 kg

1.00 kg

Storage

Storage

Steam

Cooling water

Figure 7.5a Material and energy balances in the vegetable freezing plant.

© 2008 by Taylor & Francis Group, LLC

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W 2 Pod separation

R

1 Cleaning

L 3 Grading

4 Cutting

L

S

s

5 Blanching K

6 Packaging

Z Z

z

z

7 Freezing 8 Storage

Figure 7.5b Process flowsheet of the green bean freezing plant.

© 2008 by Taylor & Francis Group, LLC

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Chapter 7

1 Vining

R

2 Size separation

L

L

S

4 Inspecting

s

3 Blanching

Z z

5 Freezing

Z z

K

6 Packaging 7 Storage

Figure 7.5b Process flowsheet of the green pea freezing plant.

© 2008 by Taylor & Francis Group, LLC

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Table 7.5a Material and Energy Requirements of a Vegetable Freezing Plant Peas Per Product

Hourly basis

Annual

Products Peas frozen

1.00 kg/kg

2.00 t/h

2 560 t/y

2.3 t/h

2 940 t/y

10 p/h

12 800 p/y

2 560 t/y

Raw materials Raw Materials

Fr.

1.15 kg/kg

Packaging Material

Fg.

200 kg/p

Process Water

Fw.

1.00 kg/kg

2.00 t/h

Electricity

Fe.

0.10 kWh/kg

0.19 MW

240 MWh/y

Steam

Fs.

0.15 kWh/kg

0.30 MW

380 MWh/y

Cooling Water Refrigeration

Fc. Fz.

0.00 kWh/kg 0.24 kWh/kg

0.00 MW 0.48 MW

0 MWh/y 610 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

0.20 kg/kg

M.

4.0 h/t

8.0 p

Per Product

Hourly basis

Utilities

Wastes Waste Treatment

0.4 t/h

510 t/y

Labor Manpower

10 240 h/y

Beans Annual

Products Beans frozen

1.00 kg/kg

2.00 t/h

2 560 t/y

Raw materials Raw Materials

Fr.

Packaging Material

Fg.

1.18 kg/kg 0.50 kg/p

2.4 t/h

3 020 t/y

4000 p/h

5 120 000 p/y

3 020 t/y

Utilities Process Water

Fw.

1.18 kg/kg

2.36 t/h

Electricity

Fe.

0.11 kWh/kg

0.22 MW

290 MWh/y

Steam

Fs.

0.15 kWh/kg

0.30 MW

380 MWh/y

Cooling Water Refrigeration

Fc. Fz.

0.00 kWh/kg 0.24 kWh/kg

0.00 MW 0.48 MW

0 MWh/y 610 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

1.36 kg/kg

Wastes Waste Treatment

2.7 t/h

3 480 t/y

Labor Manpower

© 2008 by Taylor & Francis Group, LLC

M.

4.0 h/t

8.0 p

10 240 h/y

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4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 7.5a are estimated and the results are summarized in Table 7.5b. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 7.5c. Table 7.5b Equipment Cost Estimation of the Vegetable Freezing Plant Beans No

Process

Qty

1

Cleaning

1

Size Units 2 t/h

Cost 20

2

Pod separation

1

2 t/h

40

3

Grading

1

2 t/h

50

4

Cutting

1

2 t/h

50

5

Blanching

1

2 t/h

100

6

Packaging

1

2 t/h

250

7

Freezing

1

40 m2

680

8

Storage

1

240 t

60 1250 k$

Peas No

Process

Qty

1

Vining

1

Size Units 2.3 t/h

Cost 60

2

Size Separation

1

2 t/h

50 100

3

Blanching

1

2 t/h

4

Inspecting

1

4 m2

20

5

Freezing

1

40 m2

670

6

Packaging

1

2 t/h

240

7

Storage

1

240 t

60 1200 k$

5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 7.5d and the results are summarized in Table 7.5e and in Figure 7.5c. The cost of raw materials and labor are the major components of the product cost. A labor rate of 15 $/h was assumed, which is representative of unskilled production workers. The annual operating time refers to 16 week per year, 5 days per week, 2 shifts per day, and 8h per shift.

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Table 7.5c Capital Cost Estimation of the Vegetable Freezing Plant Peas Purchased Equipment Cost

Ceq

1.25 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost Working Capital Cost

CF CW

3.75 0.67

Total Capital Cost

CT

4.42 M$

Purchased Equipment Cost

Ceq

1.20 M$

Beans

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost Working Capital Cost

CF CW

3.60 0.62

Total Capital Cost

CT

4.22 M$

6. Plant Profitability A plant profitability analysis of the design and economics of the vegetable freezing plant was performed according to the procedure described for the tomato paste plant (see Section I.6 of this chapter). Similar results were obtained. The assumptions for the plant profitability estimation are summarized in Table 7.1f of this chapter. Figure 7.5d presents the cumulated cash flow CCF and the net present value NPV of the vegetable freezing plant during its lifetime. The characteristic economic quantities are indicated in this Figure: Depreciated period ND, loan payment period NL, positive salvage period NS, and project life time NE. The simple payback period SPB and the depreciated payback period DPB are obtained as the intercepts with the time axis of the CCF and NPV curves, respectively. Based on these data, the resulting profitability indices are summarized in Table 7.5f.

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Chapter 7

Table 7.5d Assumptions for Operating Cost Estimation of the Vegetable Freezing Plant Freezing Plant

Peas

Beans

Product Rate

PR

2.00

Operating Season

wpy

16

2.00 t/h 16 w/y

Annual Operating Time

ty

1280

1280 h/y

fMF fOver

0.10 0.05

0.10 0.05 -

Operating Cost Factors Data Fixed Manufacturing Cost Factor Overhead Cost Factor Utilities Cost Crude Oil Cost

Cb.

67.0

67.0 $/bbl

Fuel Cost

Cf.

0.07

0.07 $/kW

Electricity Cost

Ce.

0.11

0.11 $/kW

Steam Cost

Cs.

0.08

0.08 $/kW

Cooling Water Cost Freezing Cost

Cc. Cz.

0.01 0.11

0.01 $/kW 0.11 $/kW

Process Water Unit Cost

Cw.

0.50

0.50 $/m3

Waste Treatment Cost

Cj.

5.00

5.00 $/m3

Labor Cost Characteristics Labor Rate Cost

CL

15.0

15.0 $/h

Labor Cost Correction Factor

fL

2.50

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00

2.00 -

Material Unit Cost

© 2008 by Taylor & Francis Group, LLC

Product

Cp.

1.25

Raw Materials

Cr.

0.25

Packaging Material

Cg.

20.0

1.15 $/kg

0.20 $/kg

0.05 $/p

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Table 7.5e Operating Cost Estimation of the Vegetable Freezing Plant Manufacturing Cost

Manufacturing Cost

Raw Materials

Cmat

0.88

Raw Materials

Cmat

Packaging

Cpack

0.26

Packaging

Cpack

0.26

Utilities Waste Treatment

Cutil Cwst

0.12 0.00

Utilities Waste Treatment

Cutil Cwst

0.13 0.02

Labor Variable Manufacturing

Clab Cmv

0.48 1.73

Labor Variable Manufacturing

Clab Cmv

0.48 1.60

Fixed Manufacturing Overheads

Cmf Cover

0.38 0.13

Fixed Manufacturing Overheads

Cmf Cover

0.36 0.12

Manufacturing Capital Charge

CM e CT

2.24 M$/y 0.37 -

Manufacturing Capital Charge

CM e CT

2.08 M$/y 0.35 -

Total Annualized

TAC

2.61 M$/y

Total Annualized

TAC

2.43 M$/y

1.50

0.72

…

…

Unit Cost ($/kg)

Unit Cost ($/kg)

1.00

1.00

Capital Charge

Fixed

Overheads

Manufacturing

Manufacturing

Labor

0.50

Waste

Utilities

Labor 0.50

Capital Charge Overheads

Fixed

Treatment

Waste

Utilities

Treatment

Packaging

Packaging Raw Materials

Raw Materials 0.00

0.00 1 Cost Operating

1 Cost Operating

Figure 7.5c Operating cost estimation of the vegetable freezing plant. 1.0

Tax Reduction

0.5

Cash flow (M$)

Cash flow (M$)

1.0

Tax

Tax Reduction

0.5

Tax

Net Profit

Net Profit

Loan Payment

Loan Payment

0.0

0.0 1

2 3

4 5

6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

1

2 3

4 5

6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Operating year

Operating year

4

4 CCF

NPV 1

0 0

5

10 ND

15

20 NL

25 NS

30 NE

Net present value / Own Capital

Net present value / Own Capital

2

-1

CCF

3

3

2

NPV

1

0 0

5

-1

10

15

ND

20 NL

-2

-2

Operating year

Operating year

Peas

Beans

Figure 7.5d Annual cash flow of the vegetable freezing plant.

© 2008 by Taylor & Francis Group, LLC

25 NS

30 NE

242

Chapter 7

Table 7.5f Plant Profitability of the Vegetable Freezing plant Peas Profitability Sales Income

S

2.69 M$/y

Manufacturing Cost Gross Profit

CM Pg

2.02 M$/y 0.67 M$/y

Net Present Value

NPV

Own Capital Cost

Co

Capital Return Ratio

CRR

1.07 -

Internal Rate of Return

IRR

0.18 -

2.36 M$ 2.21 M$

Beans Profitability Sales Income

S

2.48 M$/y

Manufacturing Cost Gross Profit

CM Pg

1.88 M$/y 0.60 M$/y

Net Present Value

NPV

Own Capital Cost

Co

Capital Return Ratio

CRR

0.92 -

Internal Rate of Return

IRR

0.17 -

1.93 M$ 2.11 M$

7. Sensitivity Analysis A sensitivity analysis of the fruit canning plant was performed according to the procedure described for the tomato paste plant (see Section 1.7 of this chapter). Similar results were obtained. Figure 7.5e shows the three characteristic points of the break-even analysis with an optimum at the operating time of 1200 h, corresponding to operation of 2 shifts daily for 5 days per week. Figure 7.5.f presents the annual profit for three different values of the product price. Figure 7.5g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL, and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively. © 2008 by Taylor & Francis Group, LLC

Food Preservation Plants

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6

.

.

6

Sales Manufacturing

2

4

Annual income/outcome (M$/y)

Annual income/outcome (M$/y)

4

Profit

Sales Manufacturing

2

Profit

0

0 0

500

1000

1500

2000

2500

3000

3500

0

500

1000

Annual operating time (h/y)

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.5e Break-even analysis. 1.5

1.5 Product price ($/kg) = Annual profit (M$/y)

Annual profit (M$/y)

Product price ($/kg) = 1.0 1.38 1.25

0.5 1.13

0.0

1.0 1.27 1.15

0.5 1.04

0.0 0

500

1000

1500

2000

2500

3000

3500

0

500

1000

Annual operating time (h/y)

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.5f Break-even analysis of the vegetable freezing plant. 1.50

Ceq Cr Capital Return Ratio

0.50

.

Ceq Cr

. Capital Return Ratio

1.50

CL Cb

Cb

CL

-0.50

Ceq Cr

-1.50 -0.40

CL

0.50

Cb

Cb

CL

-0.50

Ceq Cr

-1.50 -0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

-0.40

-0.30

-0.20

Relative variation

0.00

0.10

0.20

0.30

0.40

Relative variation

1.00

.

1.00

.

0.50

L

i

Capital Return Ratio

0.50 Capital Return Ratio

-0.10

t 0.00

iL

iL t

L

i

-0.50

-1.00 -0.40

L

i t

0.00

iL

iL t

L

i

-0.50

-1.00 -0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

-0.40

-0.30

Relative variation

Peas

-0.20

-0.10

Beans

Figure 7.5g Sensitivity analysis of the vegetable freezing plant.

© 2008 by Taylor & Francis Group, LLC

0.00

0.10

Relative variation

0.20

0.30

0.40

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Chapter 7

VI. VEGETABLE DEHYDRATION PLANT 1. Process Technology a. Raw Materials The economics of a carrot and potato dehydration plant is analyzed in this application example. Carrots and potatoes are two commercially dehydrated vegetables, which can be processed in the same plant with some variations in the processing equipment. They mature and are available for processing for a relatively long time period, and the dehydration plant could be operated for several months each year, making the plant more economical. Carrots contain about 12% TS and they can be stored for long time at 0oC and 95% RH before dehydration. They should be of good color and free of defects. The solids content of potatoes (about 24%) is about twice that of carrots, requiring significantly less energy for dehydration. b. Washing/Peeling The carrots and potatoes are first dry-cleaned on a conveyor belt to remove any dirt and external materials, and then they are washed in conventional water washing machines. The washed root vegetables are normally peeled in a steam peeler at 7 bar for 30 s. Lye peeling can also be used, although it has the disadvantage of environmental pollution (Greensmith, 1998). c. Dicing/Blanching/Sulfiting Peeled carrots and potatoes are diced mechanically (sliced into die shape) to sizes 9.5x9.5x9.5 mm, and then they are blanched for 6 min on a conveyor belt, using saturated steam at atmospheric pressure (Luh and Woodroof, 1988). The blanched carrot dice are usually sulfited with sprays of sulfurous solutions to preserve the color (carotene) during dehydration and subsequent storage. d. Drying The diced carrots and potatoes are dehydrated in a conveyor belt air–dryer until a moisture content of about 8% is reached. The product may require further dehydration to 3% moisture content in a bin dryer, using dehumidified air.

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e. Packing The dehydrated product is inspected, and the fines and defects are rejected. The product is packed in No. 10 cans or fiber drums, lined with polyethylene film. The containers of dehydrated carrots are flashed with nitrogen to prevent oxidation and discoloration of the dehydrated product. The packed dehydrated product can be stored at room temperature for several months. 2. Process Flowsheet A material and energy balance diagram of the vegetable dehydration plant is shown in Figure 7.6a. The balances are based on an 1 kg product. In the same diagram the utilities requirements are presented in kWh/kg, excluding electricity. The requirements in electricity will be presented in the next paragraphs after the equipment sizing procedure. A process flowsheet based on the above technology is presented in Figure 7.6b. The flowsheet depicts the main processes and defines their interrelations. The basic assumption is that the examined system consists of a processing plant with central utilities, e.g., steam, cooling water, waste treatment, etc. Thus, the utilities system is not included in the flowsheet, but an operating allocated cost is considered in the cost analysis section. Since the same equipment is used for both vegetables, the analysis in the next paragraphs could be based on one of the following assumptions: • Charge the half of the equipment cost to each process and use the actual annual operating time. • Charge all the equipment cost to each process and use double the annual operating time. The second assumption is used in this chapter in order to obtain the effect of the particular product characteristics on the plant profitability. 3. Material and Energy Requirements Table 7.6a lists the material and energy requirements of the vegetable dehydration plant, based on the material and energy diagram of Figure 7.6a. The annual data corresponds to 2560 and 1280 h/y for potato and carrot drying, respectively, according to the operating scheme described in the next paragraph. The labor refers only to seasonal unskilled workers which is obtained by the process counting method (See Chapter 6). The supervising, and technical support is taking into account using the factorial method (Chapter 6). The packaging material refers to 208 L fiberboard drums.

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246

Chapter 7 Potatoes

4.75 kg

Carrots

9.25 kg

24 %TS

12 %TS

Water 4.75 kg

Water Waste

Washing

9.25 kg

Waste

Washing

4.75 kg

9.25 kg

4.75 kg

9.25 kg

0.10 kWh

0.19 kWh Waste

Peeling

Waste

Peeling

0.50 kg

0.75 kg

4.25 kg

8.50 kg

Waste

Inspecting

Waste

Inspecting

0.25 kg

0.50 kg

4.00 kg

8.00 kg

Cutting

Cutting 4.00 kg

8.00 kg

0.48 kWh

0.96 kWh Blanching

Blanching

4.00 kg

8.00 kg

24 %TS

12 %TS

2.10 kWh

4.90 kWh Drying

Water

Water

Drying

3.00 kg

7.00 kg

1.00 kg

1.00 kg

96 %TS Cans

96 %TS Cans

Packaging

Packaging

1.00 kg

1.00 kg

96 %TS

Steam

96 %TS

Cooling water

Figure 7.6a Material and energy balances of the vegetable dehydration plant.

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L

W

R

1 Washing

2 Peeling

L

S 3. Inspecting

4 Cutting

L

S

L

6 Drying

S

G

s

5 Blanching

A

K

P

7 Packaging

Figure 7.6b Process flowsheet of the vegetable dehydration plant.

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Chapter 7

Table 7.6a Material and Energy Requirements of the Vegetable Dehydration Plant Potato Per Product

Hourly basis

Annual

Products Potato dried

1.00 kg/kg

1.00 t/h

2 560 t/y

4.8 t/h

12 160 t/y

5 p/h

12 800 p/y

12 160 t/y

Raw materials Raw Materials

Fr.

4.75 kg/kg

Packaging Material

Fg.

200 kg/p

Utilities Process Water

Fw.

4.75 kg/kg

4.75 t/h

Electricity

Fe.

0.33 kWh/kg

0.33 MW

850 MWh/y

Steam

Fs.

2.68 kWh/kg

2.68 MW

6 850 MWh/y

Cooling Water Refrigeration

Fc. Fz.

0.00 kWh/kg 0.00 kWh/kg

0.00 MW 0.00 MW

0 MWh/y 0 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

5.50 kg/kg

M.

10.0 h/t

Wastes Waste Treatment

5.5 t/h

14 080 t/y

Labor Manpower

10.0 p

25 600 h/y

Carrot Per Product

Hourly basis

Annual

Products Carrot dried

1.00 kg/kg

1.00 t/h

1 280 t/y

9.3 t/h

11 840 t/y

5 p/h

6 400 p/y

11 840 t/y

Raw materials Raw Materials

Fr.

9.25 kg/kg

Packaging Material

Fg.

200 kg/p

Utilities Process Water

Fw.

9.25 kg/kg

9.25 t/h

Electricity

Fe.

0.72 kWh/kg

0.72 MW

930 MWh/y

Steam

Fs.

6.05 kWh/kg

6.05 MW

7 750 MWh/y

Cooling Water Refrigeration

Fc. Fz.

0.00 kWh/kg 0.00 kWh/kg

0.00 MW 0.00 MW

0 MWh/y 0 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Wastes Waste Treatment

Fj.

10.50 kg/kg

M.

12.0 h/t

10.5 t/h

13 440 t/y

12.0 p

15 360 h/y

Labor Manpower

© 2008 by Taylor & Francis Group, LLC

Food Preservation Plants

249

4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 7.6a are estimated and the results are summarized in Table 7.6b. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 7.6c. Table 7.6b Equipment Cost Estimation of the Vegetable Dehydration Plant Potato No

Process

Qty

1

Washing

1

Size Units 5 t/h

Cost 50

2

Peeling

1

5 t/h

100

3

Inspecting

1

10 m2

20

4

Cutting

1

4 t/h

60

5

Blanching

1

5 t/h

100

6

Drying

1

100 m3

800

7

Packaging

1

1 t/h

150 1280 k$

Carrot No

Process

Qty

1

Washing

1

Size Units 20 m2

Cost 100

2

Peeling

2

5 t/h

200

3

Inspecting

1

20 m2

30

4

Cutting

1

8 t/h

120

5

Blanching

1

10 t/h

200

6

Drying

1

160 m3

1200

7

Packaging

1

1 t/h

150 2000 k$

© 2008 by Taylor & Francis Group, LLC

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Table 7.6c Capital Cost Estimation of the Vegetable Dehydration Plant Potato Purchased Equipment Cost

Ceq

1.28 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost Working Capital Cost

CF CW

3.84 1.35

Total Capital Cost

CT

5.19 M$

Purchased Equipment Cost

Ceq

2.00 M$

Carrot

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost Working Capital Cost

CF CW

6.00 1.59

Total Capital Cost

CT

7.59 M$

5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 7.6d and the results are summarized in Table 7.6e and in Figure 7.6c. The cost of raw materials, the labor, and the utilities (fuel for drying) are the major components of the product cost. A labor rate of 15 $/h was assumed, which is representative of unskilled production workers. The annual operating time refers to 32 (potato) and 16 (carrot) weeks per year, 5 days per week, 2 shifts per day, and 8h per shift.

© 2008 by Taylor & Francis Group, LLC

Food Preservation Plants

251

Table 7.6d Assumptions for Operating Cost Estimation of the Vegetable Dehydration Plant Drying Plant

Potato

Carrot

Product Rate

PR

1.00

Operating Season

wpy

32

1.00 t/h 16 w/y

Annual Operating Time

ty

2560

1280 h/y

fMF fOver

0.10 0.05

0.10 0.05 -

Crude Oil Cost

Cb.

67.0

67.0 $/bbl

Fuel Cost

Cf.

0.07

0.07 $/kW

Electricity Cost

Ce.

0.11

0.11 $/kW

Steam Cost

Cs.

0.08

0.08 $/kW

Cooling Water Cost Freezing Cost

Cc. Cz.

0.01 0.11

0.01 $/kW 0.11 $/kW

Process Water Unit Cost

Cw.

0.50

0.50 $/m3

Waste Treatment Cost

Cj.

5

5 $/m3

Labor Cost Characteristics Labor Rate Cost

CL

15.0

15.0 $/h

Labor Cost Correction Factor

fL

2.50

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00

2.00 -

5.90 $/kg

Operating Cost Factors Data Fixed Manufacturing Cost Factor Overhead Cost Factor Utilities Cost

Material Unit Cost Product

Cp.

2.50

Raw Materials

Cr.

0.12

Packaging Material

Cg.

20.00

© 2008 by Taylor & Francis Group, LLC

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Table 7.6e Operating Cost Estimation of the Vegetable Dehydration Plant Manufacturing Cost

Manufacturing Cost

Raw Materials

Cmat

1.74

Raw Materials

Cmat

Packaging

Cpack

0.26

Packaging

Cpack

0.13

Utilities Waste Treatment

Cutil Cwst

0.62 0.07

Utilities Waste Treatment

Cutil Cwst

0.69 0.07

Labor Variable Manufacturing

Clab Cmv

1.20 3.88

Labor Variable Manufacturing

Clab Cmv

0.72 4.14

Fixed Manufacturing Overheads

Cmf Cover

0.38 0.27

Fixed Manufacturing Overheads

Cmf Cover

0.60 0.32

Manufacturing Capital Charge

CM e CT

4.53 M$/y 0.43 -

Manufacturing Capital Charge

CM e CT

5.06 M$/y 0.63 -

Total Annualized

TAC

4.96 M$/y

Total Annualized

TAC

5.69 M$/y

2.50 … Unit Cost ($/kg)

Unit Cost ($/kg)

…

5.00

2.00 Capital Charge

Fixed

Overheads

Manufacturing 1.50 Labor 1.00

2.53

4.00 3.50

Treatment

Utilities Packaging

Overheads

Labor

Waste Treatment

Utilities Packaging

2.00 1.50 1.00

Raw Materials

Capital Charge Fixed Manufacturing

3.00 2.50

Waste

0.50

4.50

Raw Materials

0.50

0.00

0.00 1 Cost Operating

Potato

1 Cost Operating

Carrot

Figure 7.6c Operating cost estimation of the vegetable dehydration plant. 6. Plant Profitability A plant profitability analysis of the design and economics of the vegetable dehydration plant was performed according to the procedure described for the tomato paste plant (see Section I.6 of this chapter). Similar results were obtained. The assumptions for the plant profitability estimation are summarized in Table 7.1f of this chapter. Figure 7.6d presents the cumulated cash flow CCF and the net present value NPV of the vegetable freezing plant during its lifetime. The characteristic economic quantities are indicated in this Figure: Depreciated period ND, loan payment period NL, positive salvage period NS, and project life time NE. The simple payback period SPB and the depreciated payback period DPB are obtained as the intercepts with the time axis of the CCF and NPV curves, respectively. Based on these data, the resulting profitability indices are summarized in Table 7.6f.

© 2008 by Taylor & Francis Group, LLC

Food Preservation Plants

253 1.5

Cash flow (M$)

Cash flow (M$)

1.5

1.0

Tax Reduction

Tax

0.5

1.0

Tax Reduction

Tax

0.5 Net Profit

Net Profit

Loan Payment

Loan Payment

0.0

0.0 1

2 3

4 5

6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

1

2 3

4 5

6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Operating year

Operating year

5

5

2 NPV 1

0 0 -1

5

10 ND

15

20 NL

-2

25 NS

30 NE

CCF

4

CCF

3

Net present value / Own Capital

Net present value / Own Capital

4

3

2 NPV 1

0 0 -1

5

10

15

ND

20 NL

25 NS

30 NE

-2

Operating year

Potato

Operating year

Carrot

Figure 7.6d Annual cash flow of the vegetable dehydration plant. 7. Sensitivity Analysis A sensitivity analysis of the vegetable dehydration plant was performed according to the procedure described for the tomato paste plant (see Section 1.7 of this chapter). Similar results were obtained. Figure 7.6e shows the three characteristic points of the break-even analysis with an optimum at the operating time of 1200 h, corresponding to operation of 2 shifts daily for 5 days per week. Figure 7.6.f presents the annual profit for three different values of the product price. Figure 7.6g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

© 2008 by Taylor & Francis Group, LLC

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Chapter 7

Table 7.6f Plant Profitability of the Vegetable Dehydration Plant Potato Profitability Sales Income

S

5.38 M$/y

Manufacturing Cost Gross Profit

CM Pg

4.53 M$/y 0.85 M$/y

Net Present Value

NPV

3.11 M$

Own Capital Cost

Co

2.59 M$

Capital Return Ratio

CRR

1.20 -

Internal Rate of Return

IRR

0.19 -

Carrot Profitability Sales Income

S

6.35 M$/y

Manufacturing Cost Gross Profit

CM Pg

5.06 M$/y 1.29 M$/y

Net Present Value

NPV

5.01 M$

Own Capital Cost

Co

3.79 M$

Capital Return Ratio

CRR

1.32 -

Internal Rate of Return

IRR

0.20 -

© 2008 by Taylor & Francis Group, LLC

Food Preservation Plants

255

10

10

2 shifts

1 shift

+ weekends

3 shifts

2 shifts

1 shift

8

+ weekends

3 shifts

Annual income/outcome (M$/y)

Annual income/outcome (M$/y)

.

.

8

6 Sales 4 Manufacturing 2

Sales

6

Manufacturing cost

4

2 Profit

Profit 0 0

1000

2000

3000

4000

5000

6000

0

7000

0

500

1000

Annual operating time (h/y)

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.6e Break-even analysis of the vegetable dehydration plant. 2.0

Product price ($/kg) =

1.5

1.0

Annual profit (M$/y)

Annual profit (M$/y)

2.0

2.75 2.50

0.5

2.25

0.0

Product price ($/kg) =

1.5

6.49

1.0

5.90 5.31

0.5

0.0

0

1000

2000

3000

4000

5000

6000

7000

0

500

1000

Annual operating time (h/y)

1500

2000

2500

3000

3500

Annual operating time (h/y)

Figure 7.6f Break-even analysis of the vegetable dehydration plant. 1.50

1.50

Cr Ceq

.

CL Ceq 0.50

Capital Return Ratio

Capital Return Ratio

.

Cr

Cb Cb -0.50

Ceq CL

0.50

CL Cb

Cb CL

-0.50

Ceq Cr

Cr -1.50

-1.50 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

-0.40

0.40

-0.30

-0.20

.

0.50

L

i

Capital Return Ratio

.

0.00

0.10

0.20

0.30

0.40

1.00

1.00

Capital Return Ratio

-0.10

Relative variation

Relative variation

t 0.00

iL

iL

L

t i

-0.50

0.50

L

i t

0.00

iL

iL

L

t i

-0.50

-1.00

-1.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

Relative variation

Potato

0.20

0.30

0.40

-0.40

-0.30

-0.20

-0.10

0.00

Carrot

Figure 7.6g Sensitivity analysis of the vegetable dehydration plant.

© 2008 by Taylor & Francis Group, LLC

0.10

Relative variation

0.20

0.30

0.40

256

Chapter 7

VII. TECHNO-ECONOMIC COMPARISON In this section the results presented in the previous sections of Chapter 7 are summarized and compared. This procedure reveals the main techno-economic characteristics of the food preservation plants. Table 7.7a summarizes the total energy requirements of the examined 6 food preservation plants. The theoretical energy requirements were calculated from the material and energy balances of each process. The estimated energy was calculated from the theoretical assuming an average 25% loss. High energy requirements are observed in food plants using evaporation and drying processes (examples 7.1, 7.2, and 7.6). The energy requirements are similar to the data reported by Singh (1986). Figures 7.7a, 7.7b, and 7.7c summarize the plant requirements in raw materials, equipment cost, and manpower, respectively. The main conclusions are as follows: • Tomato paste, orange juice, potato drying, and carrot drying plants require large amount of raw material, since they remove a large amount of water by evaporation or drying. The remainder plants require quantities of raw material which is about equal to the product. • Due to requirements in evaporators and dryers, the above plants also require more expensive equipment. • The same happens to the manpower requirements. Figure 7.7d presents the product to raw material price ratio for the examined food preservation plants. This ratio varies from 2.78 (UHT milk) to 5.93 (tomato paste. Figures 7.7e and 7.7f reveal the plant profitability in terms of internal rate of return (IRR) and capital return ratio (CRR), respectively. The vegetable drying plants seem to be the most promising, while the vegetable freezing plants follow. Figure 7.7g depicts the correlation between the product price and the annual plant capacity. The results verify the general rule that the most expensive products are produced in less quantities (e.g., Holland and Wilkinson, 1997). Figure 7.7h reveals a linear correlation between the annual turnover and the own capital invested. The main conclusion is that in food preservation plants the annual turnover to own capital ratio is constant about 1.75. Figures 7.7i and 7.7j reveal the effect of own capital invested on the plant profitability in terms of internal rate of return (IRR) and net present value (NPV), respectively. Figure 7.7k compares the plant profitability between the examined food preservation plants in both terms of net present value (NPV) and internal rate of return (IRR). Again, the drying plants seem to be the most promising and the freezing plants follow.

© 2008 by Taylor & Francis Group, LLC

Food Preservation Plants

257

Table 7.7a Energy Requirements of Food Preservation Plants Food Plant Theoretical Estimated (25% losses) MJ/kg product MJ/kg product 1 Tomato paste 2 Orange juice concentrate 3 UHT sterilized milk 4 Fruit canning Apricots Peaches 5 Vegetable freezing Green peas Green beans 6 Vegetable dehydration Potato Carrots Note: To convert MJ/kg to kWh/kg divide by 3.60.

© 2008 by Taylor & Francis Group, LLC

9.70 8.00 0.16

13.0 10.7 0.21

0.96 0.81

1.28 1.08

0.52 0.50

0.70 0.67

13.8 27.4

18.4 36.5

258

Chapter 7

12.00

Raw material requirements (kg/kg)

10.00

8.00

6.00

4.00

2.00

0.00 Tomato

Orange

Peach

Appricot

Pea

Bean

Potato

Carrot

paste

juice

canning

canning

freezing

freezing

drying

drying

Milk UHT

Figure 7.7a Raw material requirements for various preservation plants. 2.00

Equipment cost required (M$) per 1t/h product rate

1.80 1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 Tomato

Orange

Peach

Appricot

Pea

Bean

Potato

Carrot

paste

juice

canning

canning

freezing

freezing

drying

drying

Figure 7.7b Equipment cost requirements for various preservation plants.

© 2008 by Taylor & Francis Group, LLC

Milk UHT

Food Preservation Plants

259

16.00

Manpower required (p) per 1 t/h product rate

14.00

12.00

10.00

8.00

6.00

4.00

2.00

0.00 Tomato

Orange

Peach

Appricot

Pea

Bean

Potato

Carrot

paste

juice

canning

canning

freezing

freezing

drying

drying

Milk UHT

Figure 7.7c Manpower requirements for various preservation plants. 8.00

7.00

Product to raw material price ratio

6.00

5.00

4.00

3.00

2.00

1.00

0.00 Tomato

Orange

Peach

Appricot

Pea

Bean

Potato

Carrot

paste

juice

canning

canning

freezing

freezing

drying

drying

Milk UHT

Figure 7.7d Product to raw material price ratio for various preservation plants.

© 2008 by Taylor & Francis Group, LLC

260

Chapter 7

0.25

Internal rate of return (IRR)

0.20

0.15

0.10

0.05

0.00 Tomato

Orange

Peach

Appricot

Pea

Bean

Potato

Carrot

paste

juice

canning

canning

freezing

freezing

drying

drying

Milk UHT

Figure 7.7e Internal rate of return (IRR) for various preservation plants. 1.40

1.20

Capital return ratio (CRR)

1.00

0.80

0.60

0.40

0.20

0.00 Tomato

Orange

Peach

Appricot

Pea

Bean

Potato

Carrot

paste

juice

canning

canning

freezing

freezing

drying

drying

Figure 7.7f Capital return ratio (CRR) for various preservation plants.

© 2008 by Taylor & Francis Group, LLC

Milk UHT

Food Preservation Plants

261

7.00

6.00

Carrot drying

5.00

Product price ($/kg)

Orange juice 4.00

3.00 Potato drying Tomato paste 2.00 Peach canning Appricot canning Pea freezing Bean freezing

1.00

Milk UHT

0.00 0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

Annual production (kt/y)

Figure 7.7g Product price to annual production rate correlation. 4.50

Tomato paste 4.00

Carrot drying

Invested own capital (M$)

3.50

Orange juice

3.00

Potato drying 2.50

Milk UHT

Peach canning Pea freezing

2.00

Appricot canning Bean freezing

1.50 2.00

2.50

3.00

3.50

4.00

4.50

5.00

5.50

6.00

Annual turnover (M$/y)

Figure 7.7h Annual turnover to own capital invested correlation.

© 2008 by Taylor & Francis Group, LLC

6.50

7.00

262

Chapter 7

0.25

Carrot drying

0.20 Potato drying Pea freezing

Internal rate of return (IRR)

Bean freezing 0.15

Appricot canning Peach canning Orange juice

Milk UHT 0.10

Tomato paste

0.05

0.00 1.50

2.00

2.50

3.00

3.50

4.00

4.50

Own capital invested (M$)

Figure 7.7i Internal rate of return to own capital invested correlation. 6.00

Carrot drying

5.00

Net present value (M$)

4.00

Potato drying

3.00

Pea freezing 2.00

Bean freezing

Orange juice

Peach canning Appricot canning

Milk UHT Tomato paste

1.00

0.00 1.50

2.00

2.50

3.00

3.50

Own capital invested (M$)

Figure 7.7j Net present value to own capital invested correlation.

© 2008 by Taylor & Francis Group, LLC

4.00

4.50

Food Preservation Plants

263

0.25

Carrot drying

0.20 Potato drying Pea freezing

Internal rate of return (IRR)

Bean freezing 0.15

Peach canning Appricot canning Milk UHT

0.10

Orange juice

Tomato paste

0.05

0.00 0.00

1.00

2.00

3.00

Net present value (NPV)

4.00

5.00

6.00

.

Figure 7.7k Plant profitability comparison. Figure 7.7l is an interesting and useful cost summary. It represents in a graphical way the analysis of the cost production to its components. The main conclusions are: • The most significant component of the production cost is the raw material cost, followed by the labor cost. • Utility cost is also significant for some food preservation plants • Packaging and waste treatment costs are of minor importance in some plants. Packaging is important in fruit canning and sterilized milk plants. Finally, Figure 7.7m presents in a comparative manner the cumulated cash flow (CCF) and the net present value (NPV) for all the examined food preservation plants as a function of their lifetime. Carrot drying seems as the most promising with a depreciated payback period of about 5 years, while the tomato paste plant is the less promising with a depreciated payback period of more than 15 years. It must be noted that all the previous results in this chapter are very sensitive to techno-economic assumptions made and any change in them may modify significantly the results.

© 2008 by Taylor & Francis Group, LLC

264

Chapter 7 4.00

Capital Charge Overheads

1.50

Fixed Manufacturing

1.00

Capital Charge

3.00

Fixed Manufacturing

2.50 Labor Waste Treatment

Utilities

1.50 Waste Treatment

Utilities

0.50

Raw Materials

0.00

0.00 1 Cost Operating

Tomato paste

1 Cost Operating

Orange juice

UHT sterilized milk

1.00

Labor

Utilities

Fixed Manufacturing

0.50

Waste Treatment

Packaging

Overheads

Unit Cost ($/kg)

Overheads

2.50

Capital Charge

Unit Cost ($/kg)

1.50

1.00

Waste Treatment

Packaging

Raw Materials

1 Cost Operating

Capital Charge

Capital Charge Overheads Labor

1.00 0.50

0.00

Fixed Manufacturing

Fixed Manufacturing

Utilities

Packaging

Packaging Raw Materials

Unit Cost ($/kg)

Overheads

2.00

Labor

0.50

1.00

3.50

Unit Cost ($/kg)

2.00

Unit Cost ($/kg)

Unit Cost ($/kg)

2.50

2.00 Capital Charge

Fixed Manufacturing

Overheads

1.50 Labor

Labor Waste Treatment

Utilities

0.50

1.00

Waste Treatment

Utilities

Packaging Packaging

0.50

Raw Materials

Raw Materials

Raw Materials

0.00

0.00

0.00 1 Cost Operating

1 Cost Operating

Peach canning

1 Cost Operating

Pea freezing

Potato drying

5.00

1.00

1.50

Fixed Manufacturing

Overheads

Capital Charge Overheads

Fixed Manufacturing

0.50 Utilities

Waste Treatment

0.50

Waste Treatment Packaging

Packaging Raw Materials

Raw Materials

1 Cost Operating

Apricot canning

3.50

Capital Charge Fixed Manufacturing

Overheads

3.00

Labor

Packaging

1.50 1.00

Raw Materials

0.50

1 Cost Operating

Bean freezing

1 Cost Operating

Carrot drying

Figure 7.7l Production cost comparison of food processing plants.

© 2008 by Taylor & Francis Group, LLC

Waste Treatment

Utilities

2.00

0.00

0.00

0.00

4.00

2.50

Labor

Labor

Utilities

Unit Cost ($/kg)

1.00

Unit Cost ($/kg)

Unit Cost ($/kg)

4.50

Capital Charge

265

5

4

4

3

3

2 CCF 1 NPV 0 0

5

-1

10

15

ND

20 NL

25 NS

30

5

4

3 CCF

2

1

NPV

0 0

5

-1

NE

10

15

ND

20 NL

25 NS

30

Net present value / Own Capital

5

Net present value / Own Capital

Net present value / Own Capital

Food Preservation Plants

NE

1

NPV

0 0

5

-1

-2

-2

CCF 2

10 ND

4

NS

30 NE

Operating year

Orange juice

5

25

-2

Tomato paste

4

20 NL

Operating year

Operating year

5

15

UHT sterilized milk

5

4

CCF

CCF 3

2

1

NPV

0 0

5

-1

10

15

ND

20 NL

25 NS

30

3

2 NPV

1

0 0

5

-1

NE

10

25 NS

30 NE

4

2

1

NPV

0 20 NL

25 NS

30 NE

Net present value / Own Capital

CCF

15

10

Operating year

Apricot canning

25 NS

30 NE

CCF

4

CCF

3

2

NPV

1

0 0 -1

20 NL

5

5

10 ND

15

20 NL

25 NS

30 NE

2 NPV 1

0 0 -1

5

10 ND

15

20 NL

25 NS

30 NE

-2

-2

-2

15

ND

Potato drying

3

3

10

5

Operating year

Net present value / Own Capital

5

4

ND

0 -1

Pea freezing

5

5

NPV 1

0

Operating year

Peach canning

0

2

-2

Operating year

Net present value / Own Capital

20 NL

-2

-2

-1

15

ND

Net present value / Own Capital

CCF

Net present value / Own Capital

Net present value / Own Capital

3

Operating year

Bean freezing

Operating year

Carrot drying

Figure 7.7m Cumulated cash flow (CCF) and net present value (NPV) comparison between the examined food preservation plants.

© 2008 by Taylor & Francis Group, LLC

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VIII. SUPPLIERS OF MAJOR FOOD PROCESSING EQUIPMENT Alfa Laval (S) www.alfalaval.com – Plate heat exchangers (heaters, pasteurizers, coolers), 2–20 t/h – Centrifugal separators, 3 t/h milk; 500 kg/h water/orange peel oil APV (UK) www.apv.com – Scraped surface heat exchangers, 2 t/h fruit juice concentrate APV Baker (UK) www.apvbaker.com – Milk homogenizer, 3 t/h Babcock–BSH AG (D) www.babcock–bsh.com – Rotary dryer, 10 t/h orange peels from 15 to 90% total solids Babcock & Wilson www.babcock.com – Packaged steam boilers, food processing, 20 bar, 2–10 t/h Cabinplant International (DK) www.cabinplant.com – Steam blancher 2 t/h cut vegetables Cleaver–Brooks (USA) www.cleaver–brooks.com – Packaged steam boilers, food processing, 20 bar, 2–10 t/h Delaval (Tetrapak) (S) www.delaval.com – Aseptic packaging machine, 3 t/h UHT sterilized milk in 1 L cart Dixie Canner (USA) www.dixiecanner.com – Can filling and can seaming machines, 3000 cans/h No. 2½ FMC Food Tech (USA) www.intl.fmcti.com – Rotary cooker–cooler, 3000 cans/h No. 2½ – Peach lye peeler, 2 t/h – Potato steam peeler, 1 t/h – Peach pitting machine, 2 t/h – Fruit washing machines, 2 t/h, 10 t/h – Tomato pulper – hot break, 10–20 t/h – Juice finishers, 10–20 t/h – Orange juice extractors, 20 t/h oranges

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FranRica (USA) www.fmc.com – Aseptic bulk packing machines, lined drums (200 kg), 4 t/h fruit concentrate, 1 t/h frozen or 200 kg/h dehydrated vegetables Frigoscandia (USA) www.frigoparts.com – Belt freezer, 1 t/h vegetables – Fluidized bed freezer, 1 t/h peas GEA–Wiegand (D) www.gea–ag.com – 3–effect evaporator, orange juice 12 to 65 oBrix, 10 t/h water evaporated Lubeca–Scholz (D) (www.scholz-mb.de – Can filling and can seaming machines, 3000 cans/h No. 2½ Ocme (I) www.ocme.it – Labeling machine, 3000 cans/h No. 2½ – Casing machine 3000 cans/h No. 2½ Proctor & Schwartz (USA) www.proctor.com – Belt dryer, cut vegetables, 1 t/h water evaporated – Rotary dryer, 10 t/h orange peels from 15 to 90% total solids Rossi & Catelli (I) www.tin.it – Tomato juice evaporator 6 to 32 % total solids, 16 t/h water evaporated SIG Holding (CH) www.sig-group.com – Packaging machine for frozen vegetables, 1500 plastic packages 0.75kg/h Standard Kessel (D) www.standardkessel.com – Packaged steam boilers, food processing, 20 bar, 2–10 t/h Urschel (USA) www.urschel.com – Potato, carrot cutting (dicing) machine, 1 t/h – Green bean cutting machine, 1 t/h

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REFERENCES Chen CS, Hernandez E, 1997. Design and performance evaluation of evaporation. In “Food Engineering Practice”, KJ Valentas, E Rotstein, and RP Singh eds. CRC Press. Cleland DJ, Valentas J, 1997. Prediction of freezing time and design of food freezers. In “Food Engineering Practice”, KJ Valentas, E Rotstein, and RP Singh eds. CRC Press. Downing DL, 1996. A Complete Course in Canning III, 13th ed. CTI Publications. Gould WA, 1992. Tomato Production, Processing and Technology, 3rd ed. CTI Publications. Greensmith M. 1998. Practical Dehydration, 2nd ed. Woodhead Publications. Holland FA, Wilkinson JK, 1997. Process Economics. In: RH Perry, DW Green, JO Maloney eds. Perry’s Chemical Engineers’ Handbook, 7th Edition, McGraw-Hill. Kimball DA, 1999. Citrus Processing, 2nd ed. Aspen Publications. Lewis M, Heppell N, 2000. Continuous Thermal Processing of Foods. Aspen Publications. Luh BS, Woodroof JG eds, 1988. Commercial Vegetable Processing, 2nd ed. Van Nostrand Reinhold. Maroulis ZB, Saravacos GD. 2003. Food Process Design. Marcel Dekker. Moresi M, 1984. Economic study of concentrated citrus juice production. In “Engineering and Food”, Vol 2, B McKenna ed., Elsevier Applied Science. Nagy S, Chen SC, Shaw PE, 1993. Fruit Juice Processing Technology. Agscience Inc. NFPA, 1997. Tomato Products, 7th ed. National Food Processors Association. Salunkhe DK, Kadam SS, 1995. Handbook of Fruit Science and Technology. Marcel Dekker. Saravacos GD, Kostaropoulos AE, 2002. Handbook of Food Processing Equipment. Kluwer/Acadenic/ Plenum Publications. Singh RP ed, 1986. Energy in Food Processing. Elsevier. Woodroof JG, Luh BS, eds, 1986. Commercial Fruit Processing, 2nd ed. Van Nostrand Reinhold.

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8 Food Manufacturing Plants

INTRODUCTION Food manufacturing plants include several small, medium, and large food processing plants in which food products of desirable quality, nutritive value, and convenience are produced. Manufactured foods are produced commercially in large quantities at a relatively low cost, afforded by the consumers. Food manufacturing plants use one or more of the various physical, chemical, and biological processes, such as mixing, separating, heating/cooling, cooking, drying, baking, roasting, and fermentation to produce a specific product, distributed normally in consumer packages. They use as raw materials either original agricultural or animal products or intermediate food products, produced by food preservation or food ingredients plants. Food preservation plants are treated separately in Chapter 7, and food ingredients plants in Chapter 9. Manufactured foods require, in general, more labor and more packaging than preserved foods and food ingredients. Batch processes are used more often than continuous operations. Specialized equipment may be required in some food processes. Food manufacturing plants are preferably located near large consumer centers for quick distribution of the food products, some of which have short shelf lives. Food plants using sensitive raw materials, such as fruits should be located near agricultural production. Plants using large amounts of imported raw materials, such as coffee beans and soybeans, are preferably located near seaports. Most manufacturing plants operate throughout the year, and ample storage facilities should be available for raw materials and processed food products. 269

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Limited amounts of liquid and solid wastes are usually produced in these plants, which can be disposed in the municipal sewage system, if available at a close distance and at affordable charge (cost). Otherwise, wastewater treatment facilities must be built near the food processing plant. Solid wastes can be treated and disposed to agricultural soils. The manufacture of most consumer food products is characterized by strict hygienic and safety regulations and practices, due to their sensitivity to microbial, biochemical, and chemical spoilage. Quality control, and compliance with government and international regulations and standards (HACCP, ISO) increase significantly the operating cost of the food plant. Packaging of manufactured foods is a major cost item, since consumer products are usually marketed in small packages, which must protect the product, appeal to the consumer, and provide the needed nutritional information (Abvenainen, 2003). Table 8.2 lists various food manufacturing plants of commercial and economic importance. Table 8.1 Food Manufacturing Plants Food Product Category

Manufacturing Plant

Cereal Products

Bread baking Pasta Dough products Cakes, biscuits Cake mixes Rice products

Dairy products

Cheese Butter Yogurt Milk powder Ice cream Whey

Confectionery

Candy Chocolate Cookies

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Fruit and vegetable products Tomato sauces, ketchup Fruit jams, marmalades Potato products Animal products

Corned beef Ham, bacon Sausages Poultry meat Egg products Fish products

Fats and oils

Vegetable oils Margarine Mayonnaise

Soft drinks

Carbonated beverages Colas Bottled water

Fermented drinks

Beer Wine Distilled drinks

Fermented foods

Pickles, sauerkraut Olives Vinegar

Coffee and Tea Products

Ground coffee Instant coffee Decaffeinated coffee Instant tea

Ready meals / Snack foods

Salads Soups Pizzas Potato chips Precooked meals Mashed potato Nuts Intermediate moisture foods

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The cereal manufacturing plants are based mostly on mechanical processing and formulation of ingredients. The cost of raw materials, mainly wheat flour, and the packaging materials are relatively low. Baking and other heat treatments require substantial amounts of energy in the form of fuel gas. The small amounts of food wastes produced can be handled with low-cost operations. Labor requirements are relatively high. The dairy manufacturing plants have high raw materials (milk) and labor costs. Some dairy products (yogurt and ice cream) have high packaging costs. The energy costs are low and liquid waste treatment is costly in some dairy plants. Ageing of cheese during controlled storage adds to the manufacturing cost. The manufacture of ice cream involves mechanical and freezing operations (Marshall et al., 2003). Confectionery is a traditional labor-intensive industry, based on mechanical processing, formulation, and mixing operations (Becket, 1994). Packaging costs are high, while energy and waste treatment costs are relatively low. The old hand-manufacturing methods are being replaced by continuous (e.g., extrusion) processes. The manufacture of fruit and vegetable products involves various mechanical and thermal processes, which require substantial amounts of energy. Labor cost is moderate, while the cost of liquid (wastewater) treatment may be high. Manufactured animal products (meat, poultry, fish, and eggs) are characterized by high raw materials and energy (refrigeration) costs. The costs of labor, packaging, and waste treatment are moderate (Hall, 1997). Edible fats and oils have relatively low raw materials costs. However, the energy cost of oil extraction and refining is very high. The costs of labor, packaging, and waste treatment are moderate. Soft drinks require high capital investment in packaging equipment. The costs of raw materials and labor are moderate. Waste treatment costs are low. Fermented drinks, such as wine and beer, are based on controlled fermentation of juices or malt extracts. Raw material costs may be high for wine, especially when high-quality grapes are used. Storage and ageing of wine and distilled drinks in wooden barrels for long time is expensive. Energy requirements are low in wine and high in distilled drinks. Fermented vegetable products, such as pickles and olives, are relatively low-cost products, produced from low-cost raw materials. The costs of labor, packaging, and energy are low. The manufacture of coffee products, especially instant and decaffeinated coffee, requires high investments in processing equipment and packaging machinery. The operating cost is affected by the high costs of raw materials and energy. Ready meals and snack foods are manufactured in small to medium plants with high labor and packaging costs. The cost of raw materials is moder-

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ate. Food preservation methods, such as thermal processing, refrigeration/ freezing or dehydration may be used, increasing the energy cost. Three application examples of different food manufacturing plants are presented in this Chapter of the book. The hypothetical food plants are designed following normal engineering procedures, i.e. material and energy balances, unit operations, and capital and operating cost estimates (Chapters 3–6). Several simplifying assumptions, necessary in the engineering analysis, are made using engineering judgment, and literature data from actual food manufacturing plants. Example 8.1 analyzes the design and economics of a rather large bread baking plant. The plant is based on mixing, fermentation, and baking operations. Raw materials and energy are very important in plant economics, while packaging and waste disposal play minor roles. Example 8.2 deals with the design and economics of a large yogurt manufacturing plant. Heat treatment, fermentation, and packaging are the most important economic operations. The raw materials (fluid milk and milk powder) are very important, while packaging in consumer cups requires expensive equipment and materials. Example 8.3 discusses the design and economics of a medium-sized commercial white wine processing plant. The plant basic operations are fermentation of grape juice, and ageing and bottling of wine. The required large fermentation and ageing tanks and the bottling machinery represent significant capital investment costs. The major waste of the winery is solid pomace, which can be disposed in surrounding vineyards. Expensive special wines are produced in relatively small wineries, using special variety grapes, grown under favorable soil and weather conditions. These wines are usually red-colored and they are stored for long times (several years) in traditional wooden barrels to develop their characteristic flavor and aroma.

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I. BREAD MANUFACTURING PLANT 1. Process Technology a. Bread Ingredients Wheat flour is the basic ingredient of bread manufacturing. It is produced in large quantities by the milling industry, using mostly hard wheat as a raw material. The hard wheat flour contains about 12% protein (gluten), which is essential in the bread-making process (bread structure). Milling of hard wheat yields about 74% flour and 26% bran. Flours of most other cereal grains contain significantly less protein than wheat, and for this reason they are normally not used for bread making (Matz, 1992). For the purpose of this book, the manufacture of white pan bread is considered in detail, since it represents the major product of the bread processing industry. Bran-containing bread is manufactured similarly. The formulation of bread composition is based on the wheat flour, and all other ingredients are expressed as a percentage (%) of the flour (Doerry, 1995). The major bread ingredients, in addition to flour, are: 1. Water, about 57% (flour basis); 2. Sugar, about 6% (flour basis), usually in the form of high fructose corn syrup (HFCS) 71 oBrix, 9% (flour basis); 3. Vegetable oil, e.g., corn oil, 2.5% (flour basis); 4. milk protein, 2.5% (flour basis), in the form of nonfat milk (NFDM) powder or whey protein; 5. Salt (sodium chloride), 1.5% (flour basis); 6. Compressed yeast (Saccharomyces cerevisiae), 1.5% (flour basis). In some wheat breads, part of the flour (e.g., 5%) may be replaced by vital wheat gluten. Various minor ingredients are added in the dough mixture to improve bread processing and bread quality, such as mineral yeast food (ammonium salts), oxidizing agents (ascorbic acid and azodicarbonamide, enzymes (amylases), dough strengtheners (emulsifiers), crumb softeners (mono-glycerides), and food preservatives (propionates), 0.15% (flour basis). Sorbic acid may be added in small amounts to the surface of baked bread loaves to prevent mold growth during storage. Flour bins, 50 t capacity, are used for flour storage in the plant. For daily flour consumption (plant capacity) of 50 t flour, 2 truckloads of 25 t each are needed. For one week (6 days) operation, 6 storage bins of a total 300 t capacity are required. Liquid sugar (HFCS solution) requires a liquid storage tank, e.g., 50 t for two weeks. The other minor ingredients are stored in bags or in refrigerated containers.

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b. Dough Preparation A semi-continuous (batch) process is widely used in the USA and in many other countries. The flour is transported pneumatically to the 1 t dough preparation tanks. Each batch yields about 1200 loaves of 1 lb (0.45 kg). Dough for commercial bread is prepared mostly by the sponge dough technology, which uses about 60% of the flour and some ingredients (yeast, sugar, milk powder) in a pre-fermentation step and the rest of the flour and ingredients are added in the fermentation step. The dough ingredients (sugar syrup, NFDM, and salt) are mixed with the flour and the water, and the required amount of yeast is added. Instead of compressed (wet) yeast, active dry yeast (ADY) at the rate of 0.7% (flour basis) may be used for convenience. The dough mixture is blended and pre-fermented for about 30 min at 25oC, so that the flour is hydrated and a desired gluten structure is developed. A “plastic” dough is thereby developed, holding the fermentation gases in the dough mass. c. Fermentation The rest ingredients (complementary water, vegetable oil, etc.) are mixed in 1 ton fermentation tanks, which are normally housed in separate fermentation room. Dough fermentation is carried out at 25oC and 80% RH for about 4 h. Excessive rising (accumulation of fermentation gases) of the dough is prevented by “punching” with special needles. d. Dough Mixing The fermented dough, after adding some minor ingredients, is mixed (kneaded) thoroughly in special equipment. Mechanical kneading increases substantially the viscoelasticity and gas holding capacity of the bread dough. Most traditional dough mixers are batch operated at about 70 RPM mixing speed (Matz, 1992; Doerry, 1995; Levine and Boehmer, 1997; Saravacos and Kostaropoulos, 2002). Kneading involves repeated compressing and stretching of the elastic dough. Horizontal kneaders are used mostly in the USA, while vertical spiral mixers are used in Europe. Recently, continuous dough mixers-extruders are used in bread technology. The intense mixing of the dough may cause significant overheating, which can be controlled by water cooling of the mixer jacket. e. Dough Dividing/Rounding Reciprocating or rotary dividers are used at high speed to produce bread loaves of the accurate weight, e.g., 0.5 kg or 1 lb. After dividing, the dough pieces are rounded mechanically. The divided dough piece is rounded between a rotating cone and a stationary rounding bar.

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f. Pre-proofing Trays of rounded dough pieces are introduced into a cabinet where they are allowed to relax at ambient temperature and controlled relative humidity for about 5 min. The intermediate proofing cabinet is usually placed above the dough mixing equipment. g. Bread Molding/Panning Bread molders are used to shape the rounded dough into loaves. The dough pieces are first sheeted and degassed by a series of rollers. The flattened dough pieces are rolled up into a loaf by passing through a curling chain. The loaves are deposited into baking pans and proofing trays. h. Proofing Proofing allows the dough to ferment and produce the leavening gas which expands the loaves resulting into a soft texture of the finished baked bread. Proofing is carried out at about 40oC and 80–85% RH in batch proof boxes or automated proofers. In the commercial automated proofers, the product is transported slowly on tray racks, or conveyor belts at controlled temperature and high humidity. Proofing time is about 45 min. i. Baking Oven Various types of baking ovens are used, such as tunnel ovens, traveling tray ovens, multiple hearth ovens (Matz, 1989; Halstrom et al., 1988; Saravacos and Kostaropoulos, 2002). Refined natural gas or LPG (direct firing) are the preferred fuels, since they leave no combustion residues on the baked bread. Heating oil, fuel oil, or coal can be used in a heat exchange system. An oven temperature of 232oC and baking time 20 min are used for 0.5 kg (1 lb) loaves. Forced circulation ovens can be used with the advantage of lowering the baking temperature by 14–19oC. A moisture loss of about 10% of the dough weight is normally observed during baking. Low pressure (0.3 bar) steam may be needed in baking bread loaves without pans on a conveyor. j. Depanning/Cooling of Bread The hot baked bread loaves are removed from the pan containers automatically, using suction cups. The bread loaves are cooled to about 35oC in an overhead conveyor by natural convection, under sanitary conditions. The cooling time is about 60 min for the 0.5 kg loaves. A high relative humidity should be maintained during cooling, so that the bread surface does not dry out excessively.

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k. Slicing/Packaging US regulations specify that the moisture content of white bread should not exceed 38% and the minimum weight of a bread loaf should be ½ lb or 0.227 kg. A surface bread preservative such as sorbic acid may be used to prevent mold growth. Band, rotary, or wire slicers are used to slice the bread loaves before packaging. Wrapping machines are used to package the bread into plastic bags of polyethylene or polypropylene (Matz, 1989). The plastic bags are reclosable, using plastic clips. l. Storage The packaged bread is distributed to the markets and the consumers soon after production. The fresh bread should be consumed within a few days of its production. m. Frozen Dough Prepared dough of various shapes and sizes can be packaged in plastic film and frozen at –18oC for long-time storage. The frozen dough is distributed recently through Supermarkets, where it is thawed, baked, and sold as fresh bread. Other dough products, such as bread rolls and croissants, can also be prepared, stored, and distributed in the frozen state. Frozen dough products represent convenient new products, which are competing in the food market with the traditional baked products. 2. Process Flowsheet A material and energy balance diagram of the bread manufacturing plant is shown in Figure 8.1a. The balances are based 1000 kg raw material. In the same diagram the utilities requirements are presented in MJ. A process flowsheet based on the above technology is presented in Figure 8.1b.

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Flour

Flour storage 1000 kg o 25 C

Water 570 kg Wet yeast

HFCS 90 kg

Dough preparation

NFDM

15 kg

25 kg

Salt

Electricity 123 MJ

15 kg 1715 kg Vegetable oil 20 kg

Fermentation 1735 kg

Dough mixing

Electricity 123 MJ

Dough dividing

Electricity 68 MJ

Heating 50 MJ

Pre-proofing

Molding / panning

Electricity 68 MJ

Heating 108 MJ

Proofing

o 40 C

Heating 1260 MJ

Baking

Water vapor 170 kg 1565 kg o 220 C

Cooling 120 MJ

Depanning / cooling Water vapor 20 kg 1545 kg o 35 C Slicing / packaging

Electricity 80 MJ

o 25 C

Storage Bread

Figure 8.1a Material and energy balances of the bread manufacturing plant.

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Salt

279 NFDM

HFCS

Z z

yeast

Oil Dough preparation

Fermentation

Preproofing Mixing

Dividing

Proofing Molding Panning S s

G Baking Storage

A

Depanning Packaging

Figure 8.1b Process flowsheet of the bread manufacturing plant.

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3. Material and Energy Requirements Table 8.1a lists the material and energy requirements of the bread manufacturing plant, based on the material and energy diagram of Figure 8.1a. The annual data corresponds to 3840 h/y, according to the operating scheme described in the next paragraph. The Labor refers only to production workers which is obtained by the process counting method (See Chapter 6). The supervising, and technical support is taken into account using the factorial method (Chapter 6). The packaging material refers to plastic bags. 4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 8.1b are estimated and the results are summarized in Table 8.1b. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 8.1c. Table 8.1a Material and Energy Requirements of the Bread Manufacturing Plant Per Product

Hourly basis

Annual

Products Bread

1.00 kg/kg

5.00 t/h

19 200 t/y

Raw materials Raw Materials

Fr.

0.65 kg/kg

Packaging Material

Fg.

0.50 p/kg

3.2 t/h

12 430 t/y

10000 p/h

38 400 000 p/y

Process Water

Fw.

Electricity

Fe.

0.37 kg/kg

1.84 t/h

7 080 t/y

0.08 kWh/kg

0.42 MW

Steam

1 590 MWh/y

Fs.

0.25 kWh/kg

1.27 MW

4 890 MWh/y

Cooling Watre

Fc.

0.02 kWh/kg

0.11 MW

410 MWh/y

Refrigeration

Fz.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

0.00 kg/kg

M.

6.4 h/t

Utilities

Wastes Waste Water Treatment

0.0 t/h

0 t/y

Labor Manpower

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Table 8.1b Equipment Cost Estimation of the Bread Manufacturing Plant No Process

Qty Size Units Cost

1 Flour storage bins

6

50 t

300

2 Corn syrup storage tank

1

50 t

50

3 NFDM storage in bags

1

7 t

10

4 Salt storage in bags

1

5 t

5

5 Refrigerated storage of yeast

1

5 t

15

6 Mixing tanks

3

1 t

75

7 Fermentation tanks

5

1 t

125 150

8 Dough kneading tanks

3

1 t

9 Dough dividers and rounders

2

3 t/h

10 Pre-proofing cabinet

1

2 t

30

11 Molders/panners

2

3 t/h

50

12 Conveyor belt proofing

1

6 t/h

200

13 Tunnel conveyor belt oven

1

6 t/h

300

14 Depanner/coolers

1

6 t/h

50

15 Slicing machine

2

3 t/h

40

16 Bread wrappers

2

3 t/h

60

50 1510 k$

Table 8.1c Capital Cost Estimation of the Bread Manufacturing Plant Purchased Equipment Cost

Ceq

1.51 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost

CF

Working Capital Cost

CW

Total Capital Cost

CT

4.53 4.84 9.37 M$

5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 8.1d and the results are summarized in Table 8.1e and in Figure 8.1c. The cost of raw material and the labor are the major components of the product cost. A labor rate of 15 $/h was assumed, which is representative of unskilled production workers. The annual operating time refers to 48 week per year, 5 days per week, 2 shifts per day, and 8h per shift.

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Table 8.1d Assumptions for Operating Cost Estimation of the Bread Manufacturing Plant Bread Plant Product Rate

PR

Operating Season

wpy

5.00 t/h 48 w/y

Annual Operating Time

ty

3840 h/y

Operating Cost Factors Data Fixed Manufacturing Cost Factor

fMF

0.10 -

Overhead Cost Factor

fOver

0.05 -

Utilities Cost Crude Oil Cost

Cb.

67.0 $/bbl

Fuel Cost

Cf.

0.07 $/kWh

Electricity Cost

Ce.

0.11 $/kWh

Steam Cost

Cs.

0.08 $/kWh

Cooling Water Cost

Cc.

0.01 $/kWh

Freezing Cost

Cz.

Process Water Unit Cost

Cw.

0.50 $/m3

Waste Treatment Cost

Cj.

0.05 $/m3

0.11 $/kWh

Labor Cost Characteristics Labor Rate Cost

CL

15.0 $/h

Labor Cost Correction Factor

fL

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00 -

Material Unit Cost Product

Cp.

1.20 $/kg

Raw Materials

Cr.

0.60 $/kg

Packaging Material

Cg.

0.01 $/p

For the purposes of the application example, it is assumed that the raw material cost includes the cost of all additives, expressed in $/kg flour. Detailed cost calculations require data on the cost of each material.

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Table 8.1e Operating Cost Estimation of the Bread Manufacturing Plant Manufacturing Cost Raw Materials

Cmat

8.87

Packaging

Cpack

0.38

Utilities Waste Treatment

Cutil Cwst

0.55 0.00

Labor Variable Manufacturing

Clab Cmv

5.76 15.56

Fixed Manufacturing Overheads

Cmf Cover

0.45 0.97

Manufacturing Capital Charge

CM e CT

16.98 M$/y 0.78 -

Total Annualized

TAC

17.76 M$/y

1.00 …

Fixed

Capital Charge Overheads

Unit Cost ($/kg)

Manufacturing

Labor

0.50

Utilities

Waste Treatment Packaging

Raw Materials

0.00 1 Cost Operating

Figure 8.1c Operating cost estimation of the bread manufacturing plant.

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6. Plant Profitability Table 8.1f summarizes all the required economic assumptions in order to calculate the plant profitability, that is: A tax rate of 35% is considered. The Negative Tax Permission Index is 1 when the examined plant is a part of larger factory and the plant taxation is consolidated with the total factory, and 0 otherwise, which means that the tax reduction may be lost. The annual depreciation is estimated according to the MACRS method described in Chapter 4. According to this method, the equipment is depreciated in 7 years. It is assumed that 50% of the required capital is covered by loan with interest of 5% for 15 y. It is also assumed that the plant lifetime is 27 y, but after 20 y the equipment has no salvage value. A discounted interest rate of 7% is assumed in order to express the time value of money. In all application examples, the calculated capital recovery factor, for i=0.07 and N=27, was e=0.083. Based on these assumptions, the annual cash flow of the examined system during its lifetime is presented in Figure 8.1d. Figure 8.1.d also presents the Cumulated Cash Flow CCF and the Net Present Value NPV for the project life time (see Chapter 4). The characteristic time intervals are the depreciated period ND, the loan payment period NL, the positive salvage period NS, and the project life time NE. Moreover, CCF intercepts the time axis at the simple payback period SPB, while NPV intercepts the time axis at the depreciated payback period DPB. Table 8.1f Assumptions for Plant Profitability Estimation Tax Characteristics Depreciation Method

jd MACRS -

Depreciation Period Tax Rate

ND t

7 y 0.35 -

Negative Tax Permission Index

ntp

1 -

Debt Characteristics Leverage

L

0.50 -

Loan Interest Rate

iL

0.05 -

Loan Period

NL

15 y

Discounted Interest Rate

i

0.07 -

Plant Lifetime

N

27 y

Nonzero Salvage Value Period

NS

20 y

Other

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2.5

Cash flow (M$)

2.0

Tax Tax Reduction

1.5

1.0 Net Profit 0.5 Loan Payment 0.0 1

2

3

4 5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Operating year

8 7

CCF

Net present value / Own Capital

6 5 4 3

NPV

2 1 0 0

5

-1

10 ND

15

20 NL

25 NS

30 NE

-2 Operating year

Figure 8.1d Annual cash flow (upper) and cumulated cash flow (CCF) and net present value (NPV) of the bread manufacturing plant.

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Based on these data the resulting profitability indices are also summarized in Table 8.1g. Table 8.1g Plant Profitability of the Bread Manufacturing Plant Profitability Sales Income

S

19.37 M$/y

Manufacturing Cost

CM

16.98 M$/y

Gross Profit

Pg

2.39 M$/y

Net Present Value

NPV

Own Capital Cost

Co

Capital Return Ratio

CRR

2.48 -

Internal Rate of Return

IRR

0.30 -

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11.61 M$ 4.69 M$

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7. Sensitivity Analysis All the above results refer to a basic reference point. The sensitivity of these results to the variation of basic data consists a crucial concept in the design and analysis of the food plants. Several sensitivity analysis situations could be formulated depended on the factors and the response variables selected. In this section the effect of the following factors on the plant profitability will be examined: • The annual operating time (break-even analysis), and the product price • The resources prices (raw materials, labor, utilities, equipment) • The economic environment (e.g., tax and debt characteristics) a. Break-Even Analysis A typical break-even analysis is presented in Figure 8.1e. The three crucial operating magnitudes, that is, the annual sales income, the annual manufacturing cost, and the corresponding annual gross profit are plotted versus the annual operating time. The profit curve indicates three characteristic points: • The lower break-even point • The maximum profit point • The upper break-even point It is obvious that the plant operation in the range between the lower and the upper break-even points is profitable. The optimum operating point happens to an annual operating time of about 2000 h, which corresponds to operation of 1 shift daily for 5 days per week. The optimum is sharp and an operation of 2 shifts will significantly decrease the profit. These results are further analyzed in Figure 8.1f, which presents the profit versus the annual operating time for three different values of the product price. These curves show a significant effect of the product price on the profit. In conclusion, these graphs reveal the economical operation of the plant and suggest the required changes in order to match external changes in the economic environment of the plant. In a world of rapid changes, plant flexibility is a crucial matter towards profitability. b. Effect of Resource Prices and Tax and Debt Characteristics Figure 8.1g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL, and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

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30

Annual income/outcome (M$/y)

.

25

20 Sales 15 Manufacturing cost 10 1 shift

2 shifts

5

+ weekends

3 shifts

Profit

0 0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Annual operating time (h/y)

Figure 8.1e Break-even analysis of the bread manufacturing plant. 5.0

Annual profit (M$/y)

4.0

3.0

Product price ($/kg) =

2.0

1.0

1.08

1.20

1.32

0.0 0

1000

2000

3000

4000

5000

6000

7000

8000

Annual operating time (h/y)

Figure 8.1f Break-even analysis of the bread manufacturing plant.

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10000

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2.00

Capital Return Ratio

.

Cr 1.00

CL Ceq

0.00

Cb

Cb

Ceq CL

-1.00

Cr -2.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

Relative variation

Capital Return Ratio

.

1.00

0.50

0.00

i t

L

iL

iL

L

t i

-0.50

-1.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

Relative variation

Figure 8.1g Sensitivity analysis of the bread manufacturing plant.

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0.40

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II. YOGURT MANUFACTURING PLANT 1. Process Technology a. Raw Materials The main raw material of yogurt is fresh cow’s milk, usually collected from dairy farms close to the plant. The milk contains about 13% TS, including 3.5% fat. The milk is transported from the farm to the plant by refrigerated tank trucks of about 30 t capacity and stored in stainless steel tanks of about 80 t capacity. Nonfat dry milk (NFDM) or milk whey protein is used for fortification of the liquid milk. Yogurt culture in wet or dried form is used for inoculation (Tamine and Robinson, 1999). Yogurt stabilizers, such as gelatin, pectin, modified starch, or gelatin/plant gum mixtures are normally used to thicken the yogurt coagulum. Fruit pieces or fruit pulp is used to prepare the fruit yogurt. The raw material (milk) of this application example is similar to the milk used in the UHT sterilization plant of example 7.3. b. Standardization/Mixing In this application example, medium-fat yogurt is produced, containing 1.5% milk fat. Centrifugal separation is used to remove about 2% of fat from the initial liquid milk and clarify the raw milk. The milk is fortified with milk proteins to produce a thick-body yogurt product. Nonfat dry milk (NFDM) at the rate of 4% is usually added, but dried whey protein may be also used. Milk protein stabilizers, used to prevent whey separation (syneresis) of yogurt during storage, are added at the rate of about 0.3%. c. Homogenization The mixture of milk ingredients is homogenized in a high-pressure continuous homogenizer, operated at about 200 bar pressure and temperature 55oC. Homogenization retards fat separation (creaming) and improves the water-binding properties of milk proteins (casein). d. Heat Treatment The homogenized milk is heated in a plate heat exchanger to about 90oC for 5 min for increasing the water-binding capacity of milk proteins and denaturation of the whey proteins. At the same time the milk mixture is pasteurized, i.e. all pathogenic and most spoilage bacteria are inactivated (Ranken and Kill, 1993).

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e. Fermentation The heated milk mixture is cooled to about 45oC and pumped to fermentation tanks, where it is inoculated with a yogurt culture. The yogurt inoculum (wet culture starter) consists of a mixed culture of Lactobacillus bulgaricus and Streptococcus thermophilus in proportion of 2% of the milk mixture. Incubation time is about 3h at 45oC, after which a firm coagulum is formed, which is used in the manufacture of various stirred yogurts, e.g., yogurt with fruit pieces, strained yogurt, or drinking yogurt. Set yogurt is prepared by packaging the inoculated milk mixture into consumer cups and incubating the aseptically sealed packages at 45oC for 3–4h. Modern yogurt plants use freeze-dried culture starters, replacing the old wet culture method. The freeze-dried starter is provided by culture manufacturers in powder form. The starter is applied by direct vat injection (DVI) at the rate of 0.5% of the milk mixture. f. Mixing of Yogurt The bulk-set yogurt is cooled through a plate heat exchanger to 15oC, using gentle (low shear) mechanical transport (positive displacement pumps). Fruitcontaining yogurt is prepared by gentle mixing of bulk yogurt with about 5% fruit pieces or fruit pulp. The fruit product, containing about 15% total solids, is supplied as frozen, canned, or dried fruit, and it is comminuted into pieces of the desired size before use. Strained yogurt is prepared by separating part of the whey from the stirred yogurt either in cloth bags or in a centrifugal separator. g. Packaging Stirred yogurt or inoculated milk mixture is usually packaged in plastic cups and sealed with aluminum lids, using automatic packaging machines, which operate under aseptic conditions. Semi-rigid plastic materials used in yogurt packaging include polyethylene (PE), polypropylene (PP), polystyrene (PS), or polyvinylchloride (PVC). The plastic cups may be supplied by plastics manufacturers or preferably formed in place by the packaging machine. The form–fill–seal (FFS) system is used in automatic machinery. The entire packaging operation is carried out under aseptic conditions, using hydrogen peroxide and/or UV radiation for sterilization. h. Cooling/Storage The sealed yogurt cups are cooled and stored at about 5oC. Refrigerated storage life is 2–3 weeks, and the yogurt is displayed in retail shops at about 10oC. The yogurt cups must be handled gently to prevent mechanical damage (shearing) of the yogurt coagulum.

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2. Process Flowsheet A material and energy balance diagram of the yogurt manufacturing plant is shown in Figure 8.2a. The balances are based on 1000 kg raw material. In the same diagram the utilities requirements are presented in MJ. A process flowsheet based on the above technology is presented in Figure 8.2b. 3. Material and Energy Requirements Table 8.2a lists the material and energy requirements of the yogurt manufacturing plant, based on the material and energy diagram of Figure 8.2a. The annual data corresponds to 3840 h/y, according to the operating scheme described in the next paragraph. The Labor refers only to production workers which is obtained by the process counting method (see Chapter 6). The supervising and technical support is taken into account using the factorial method (Chapter 6). The packaging material refers to plastic cups.

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Milk

Milk storage 1000 kg NFDM Fat

40 kg Standardization

20 kg

Stabilizers

Electricity 40 MJ

1020 kg o 25 C Heating

Electricity

Homogenization

100 MJ

50 MJ

o 55 C

Heating

Heat treatment

180 MJ

Electricity 20 MJ o 92 C

Cooling

Cooling

125 MJ

o 45 C

Wet calture 20 kg

Inoculation 1040 kg

Cuos, lids

Packaging

Electricity 40 MJ o 30 C

Heating 50 MJ

Cup incubation

o 45 C

Refrigeration 180 MJ

Refrigeration storage

o 5 C

Figure 8.2a Material and energy balances of the yogurt manufacturing plant.

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Chapter 8 NFDM Stabilizers Standardization Fat Raw milk storage

S

Homogenization

s

S C

Heat treatment

s

c

Z

Wet calture

Inocubation

z

Packaging Cold storage

Figure 8.2b Process flowsheet of the yogurt manufacturing plant.

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Table 8.2a Material and Energy Requirements of the Yogurt Manufacturing Plant Per Product

Hourly basis

Annual

Products Yogurt

1.00 kg/kg

5.00 t/h

19 200 t/y

Raw materials Raw Materials

Fr.

0.96 kg/kg

Packaging Material

Fg.

0.20 p/kg

4.8 t/h

18 460 t/y

25000 p/h

96 000 000 p/y

19 200 t/y

Utilities Process Water

Fw.

1.00 kg/kg

5.00 t/h

Electricity

Fe.

0.04 kWh/kg

0.20 MW

770 MWh/y

Steam

Fs.

0.09 kWh/kg

0.44 MW

1 690 MWh/y

Cooling Watre

Fc.

0.03 kWh/kg

0.17 MW

640 MWh/y

Refrigeration

Fz.

0.05 kWh/kg

0.24 MW

920 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

1.00 kg/kg

Wastes Waste Water Treatment

5.0 t/h

19 200 t/y

Labor Manpower

M.

3.6 h/t

18.0 p

69 120 h/y

4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 8.2b are estimated and the results are summarized in Table 8.2b. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 8.2c. 5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 8.2d and the results are summarized in Table 8.2e and in Figure 8.2c. The cost of raw material and the labor are the major components of the product cost. A labor rate of 15 $/h was assumed, which is representative of unskilled production workers. The annual operating time refers to 48 week per year, 5 days per week, 2 shifts per day, and 8h per shift.

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Table 8.2b Equipment Cost Estimation of the Yogurt Manufacturing Plant No Process

Qty Size Units

Cost

1 Trucks

4

30 t

400

2 Milk storage tanks

3

80 t

240

3 Mixing tanks

3

1 t

50

4 Homogenizers

1

5 t

250

5 Plate heat exchanger

1

5 t/h

200

6 Cooler

1

5 t/h

100

7 Aseptic packaging

5

1 t

800

8 Incubation room

1

16 t

50

9 Refrigerated storage

1

50 t

200

1

2 t

10 CIP cleaning system

200 2490 k$

Table 8.2c Capital Cost Estimation of the Yogurt Manufacturing Plant Purchased Equipment Cost

Ceq

2.49 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost

CF

Working Capital Cost

CW

Total Capital Cost

CT

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Table 8.2d Assumptions for Operating Cost Estimation of the Yogurt Manufacturing Plant Yogurt Plant Product Rate

PR

Operating Season

wpy

5.00 t/h 48 w/y

Annual Operating Time

ty

3840 h/y

Operating Cost Factors Data Fixed Manufacturing Cost Factor

fMF

0.10 -

Overhead Cost Factor

fOver

0.05 -

Utilities Cost Crude Oil Cost

Cb.

67.0 $/bbl

Fuel Cost

Cf.

0.07 $/kWh

Electricity Cost

Ce.

0.11 $/kWh

Steam Cost

Cs.

0.08 $/kWh

Cooling Water Cost

Cc.

0.01 $/kWh

Freezing Cost

Cz.

Process Water Unit Cost

Cw.

0.50 $/m3

Waste Treatment Cost

Cj.

0.05 $/m3

0.11 $/kWh

Labor Cost Characteristics Labor Rate Cost

CL

15.0 $/h

Labor Cost Correction Factor

fL

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00 -

Material Unit Cost Product

Cp.

1.25 $/kg

Raw Materials

Cr.

0.35 $/kg

Packaging Material

Cg.

0.04 $/p

For the purposes of the application example, it is assumed that the raw material cost includes the cost of all additives, expressed in $/kg milk. Detailed cost calculations require data on the cost of each material.

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Table 8.2e Operating Cost Estimation of the Yogurt Manufacturing Plant Manufacturing Cost Raw Materials

Cmat

Packaging

Cpack

7.68 3.84

Utilities

Cutil

0.32

Waste Treatment

Cwst

0.00

Labor

Clab

3.24

Variable Manufacturing

Cmv

15.09

Fixed Manufacturing

Cmf

0.75

Overheads

Cover

Manufacturing

CM

Capital Charge

e CT

Total Annualized

TAC

1.01 16.84 M$/y 1.04 17.89 M$/y

1.00 Capital Charge

Unit Cost ($/kg) . …

Fixed

Overheads

Manufacturing

Labor Utilities

Waste Treatment Packaging

0.50

Raw Materials

0.00 1 Cost Operating

Figure 8.2c Operating cost estimation of the yogurt manufacturing plant.

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6. Plant Profitability A plant profitability analysis of the design and economics of the yogurt manufacturing plant was performed according to the procedure described for the bread manufacturing plant (see Section I.6 of this chapter). Similar results were obtained. The assumptions for the plant profitability estimation are summarized in Table 8.1f of this Chapter. Figure 8.2d presents the cumulated cash flow CCF and the net present value NPV of the yogurt manufacturing plant during its lifetime. The characteristic economic quantities are indicated in this Figure: Depreciated period ND, loan payment period NL, positive salvage period NS, and project life time NE. The simple payback period SPB and the depreciated payback period DPB are obtained as the intercepts with the time axis of the CCF and NPV curves, respectively. Based on these data, the resulting profitability indices are also summarized in Table 8.2f. Table 8.2f Plant Profitability of the Yogurt Manufacturing Plant Profitability Sales Income

S

20.18 M$/y

Manufacturing Cost

CM

16.84 M$/y

Gross Profit

Pg

3.34 M$/y

Net Present Value

NPV

16.99 M$

Own Capital Cost

Co

Capital Return Ratio

CRR

2.72 -

Internal Rate of Return

IRR

0.32 -

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Cash flow (M$)

4.0

Tax

3.0 Tax Reduction

2.0

Net Profit 1.0

Loan Payment 0.0 1

2

3

4 5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Operating year

8 CCF

7

Net present value / Own Capital

6 5 4 3

NPV

2 1 0 0

5

-1

10 ND

15

20 NL

25 NS

30 NE

-2 Operating year

Figure 8.2d Annual cash flow (upper) and cumulated cash flow (CCF) and net present value (NPV) of the yogurt manufacturing plant.

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7. Sensitivity Analysis A sensitivity analysis of the yogurt manufacturing plant was performed according to the procedure described for the bread manufacturing plant (see Section 1.7 of this chapter). Similar results were obtained. Figure 8.2e shows the three characteristic points of the break-even analysis with an optimum at an annual operating time of about 2000 h, corresponding to operation of 2 shifts daily for 5 days per week. Figure 8.2.f presents the annual profit for three different values of the product price. Figure 8.2g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL, and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

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30

Annual income/outcome (M$/y)

.

25

20 Sales 15 Manufacturing cost 10 1 shift

2 shifts

+ weekends

3 shifts

5

Profit

0 0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Annual operating time (h/y)

Figure 8.2e Break-even analysis of the yogurt manufacturing plant. 6.0

Annual profit (M$/y)

5.0

Product price ($/kg) =

4.0 3.0 2.0 1.13

1.0

1.25

1.38

0.0 0

1000

2000

3000

4000

5000

6000

7000

8000

Annual operating time (h/y)

Figure 8.2f Break-even analysis of the yogurt manufacturing plant.

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1.00

Capital Return Ratio

.

Cr

Ceq CL 0.00

Cb

Cb

Ceq CL

Cr

-1.00 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

Relative variation

0.50 L

Capital Return Ratio

.

i t 0.00

iL

iL

t

L

i

-0.50 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

Relative variation

Figure 8.2g Sensitivity analysis of the yogurt manufacturing plant.

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0.40

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III. WINE PROCESSING PLANT 1. Outline of Process Technology a. Raw Materials The main raw material in wine processing is grapes of a wine-making variety. Wine quality is affected strongly by grape variety, soil, cultivation method, and weather conditions (temperature, humidity, and sunlight). Some regions of the world are suitable for high quality grapes and wines, such as France, Mediterranean countries, California, South Africa, South America, and Australia. Traditional wines are produced in small to medium-sized wineries, applying batch processes. Modern wine processing plants apply scientific and engineering principles to produce large quantities of wines at competitive cost. The economics of such a modern wine plant is analyzed in this example. Grape harvesting lasts about one month in the fall (September in the Northern Hemisphere). The grapes are harvested by hand in most countries. Mechanical harvesting of grapes is used in California. Maturity of the grapes is judged from the sugar content, e.g., 22oBrix. Mechanical harvesting can be accompanied by field crushing of the grapes. An added advantage of mechanical harvesting is destemming of the grapes and rejection of the stems in the field (vineyard), with less solid waste (pomace) in the plant (Boulton et al., 1996). Sulfite treatment of crushed grapes may be needed too in the vineyard. b. Grape Crushing The stems of the grapes are removed and the grape berries are crushed in a combined destemming/crushing operation. A perforated rotating drum is used with 25 mm diameter holes. The grapes are caught, crushed, and passed through the holes, while the stems and leaves are separated and discharged from the cylinder (Boulton et al., 1996; Nagy et al., 1993). c. Juice Expression In white wine processing, the juice is separated from the crushed grapes quickly to prevent the extraction of undesirable components from the grape skins and seeds. However, in the production of red wines, the crushed grapes are heated to about 50oC and fermented with the skins in order to extract the pigments and other desirable components of the grapes. The grape juice for white wines is expressed using various machines, e.g., the screw or the Willmes (bladder) presses (Saravacos and Kostaropoulos,

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2002). The pressed low-moisture pomace (mixture of grape skins, seeds, and stems) is disposed by mixing with the soil in the vineyard. d. Fermentation The expressed juice is treated with some yeast nutrients (ammonium salts) and sulfites (about 50 ppm sulfur dioxide) to control the alcoholic fermentation. Stainless steel fermentation tanks of about 40 m3 capacity are used. Grape juice of 22oBrix when fermented completely with yeast will yield wine with 11.5% ethanol. at the approximate rate of 1 L wine / kg juice. The grape juice is inoculated with activated dry yeast (ADY) at the rate of 0.15 kg/t. Carbon dioxide is produced during fermentation, along with ethanol, at the rate of 0.1 kg CO2 /L juice of 22oBrix. Large concentrations of CO2 must be removed from the fermentation room using venting fans. Fermentation is an exothermic biochemical process, and the temperature in the fermenting tank must be kept below 30oC. Cooling may be required, such as circulating the fermenting liquor through an external heat exchanger. e. Ageing of Wine White wines are aged in bulk for short time, e.g., 6 months, before bottling. Red wines are usually aged in wooden barrels for long time (more than one year) in wine cellars, acquiring characteristic flavor and aroma (bouquet), resulting in expensive wines. Stainless steel tanks of about 150 t capacity (40,000 gallons) may be used for bulk storage of white wines at about 20oC. Concrete tanks, lined with epoxy paint, may be used in wine storage. Refrigeration of the storage tanks may be needed during the ageing period. Wine storage results in some desirable biochemical and physicochemical reactions, and clarification of the wine. Ageing in bulk tanks can be accelerated by introducing wood chips in the wine, a process used in the manufacture of lager beer. f. Wine Filtration Wine is filtered to remove all the suspended particles before bottling. Frame and plate filters, leaf filters, of pad filters may be used, employing some type of filter aid. Recent advances in Membrane Technology allow the use of microfiltration or ultrafiltration in the clarification of wine (Saravacos and Kostaropoulos, 2002). Microfiltration membranes of proper pore size can remove all spoilage microorganisms (bacteria, yeasts, and molds) from the wine, resulting in a sterile product.

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g. Bottling of Wine The clarified aged wine is usually packaged in glass bottles of 0.75 L capacity, using high speed bottling machines. The wine is filled automatically in the bottles which are corked and sealed at the rate of up to 5000 bottles/h. A separate bottling room, operated at positive pressure under sterile conditions, is required. Bottling is carried out off-season and after the wine has aged. The empty bottles are rinsed with water and sterilized with a permitted chemical (e.g., a peroxide). h. Bottle Storage The wine bottles are stored at room (cellar) temperature for several months or years before sale distribution. The price of wine depends strongly on the grape variety, the vineyard area, the wine manufacturing technology, and the storage time. i. Plant Wastes The solid wastes of wineries (pomace) is normally disposed in the vineyards by mixing with the soil. The sanitary waste of wineries can be discharged to a local sewage plant or to a plant sewer. The winery liquid wastes, if low in volume, can be used for irrigation of the vineyard soil (Storm, 1997). Large volumes of liquid wastes can be discharge to local sewage or in a special wastewater treatment installation in the winery. 2. Process Flowsheet A material and energy balance diagram of the wine manufacturing plant is shown in Figure 8.3a. The balances are based on 1000 kg raw material. In the same diagram the utilities requirements are presented in MJ. A process flowsheet based on the above technology is presented in Figure 8.3b. 3. Material and Energy Requirements Table 8.3a lists the material and energy requirements of the wine manufacturing plant, based on the material and energy diagram of Figure 8.3a. The annual data corresponds to 320 h/y, according to the operating scheme described in the next paragraph. The Labor refers only to production workers which is obtained by the process counting method (See Chapter 6). The supervising and technical support is taken into account using the factorial method (Chapter 6). The packaging material refers to glass bottles.

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Grapes

1000 kg Electricity

Destemming/crushing Pomace 320 kg Juice

40 MJ

680 kg Electricity

Juice clarification Residue 20 kg Juice 22o Brix

40 MJ

660 kg

Refrigeration

CO2

Fermentation

90 MJ

Wine 12

o

Refrigeration

Ageing

140 MJ

Electricity

Residue 10 kg

Filtration

20 MJ

650 kg Bottles, corks

Electricity

Bottling

15 MJ

Electricity

Labeling/casing

5 MJ

Refrigeration 80 MJ

Bottle storage

Figure 8.3a Material and energy balances of the wine manufacturing plant.

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Grapes

Pomace Destemming Crushing

Clarification

Fermentation Ageing

Filtration

Bottling Storage

Figure 8.3b Process flowsheet of the wine manufacturing plant.

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Table 8.3a Material and Energy Requirements of the Wine Manufacturing Plant Per Product

Hourly basis

Annual

Products Wine

1.00 kg/kg

5.00 t/h

1 600 t/y

Raw materials Raw Materials

Fr.

1.54 kg/kg

Packaging Material

Fg.

0.75 p/kg

7.7 t/h

2 460 t/y

6667 p/h

2 133 330 p/y

Utilities Process Water

Fw.

0.00 kg/kg

0.00 t/h

Electricity

Fe.

0.05 kWh/kg

0.26 MW

0 t/y 80 MWh/y

Steam

Fs.

0.00 kWh/kg

0.00 MW

0 MWh/y

Cooling Watre

Fc.

0.00 kWh/kg

0.00 MW

0 MWh/y

Refrigeration

Fz.

0.13 kWh/kg

0.66 MW

210 MWh/y

Fuel

Ff.

0.00 kWh/kg

0.00 MW

0 MWh/y

Fj.

0.00 kg/kg

M.

6.4 h/t

Wastes Waste Water Treatment

0.0 t/h

0 t/y

Labor Manpower

32.0 p

10 240 h/y

4. Capital Investment Based on the simplified shortcut methods of Chapter 5, the size and the cost of the equipment presented in the flowsheet of Figure 8.3a are estimated and the results are summarized in Table 8.3b. The required capital is estimated as described in Chapter 5, and the results are summarized along with the appropriate assumptions in Table 8.3c. 5. Operating Expenses The operating cost is calculated on the basis of the assumptions presented in Table 8.3d and the results are summarized in Table 8.3e and in Figure 8.3c. The cost of raw material, fixed manufacturing, and labor are the major components of the product cost. A labor rate of 15 $/h was assumed, which is representative of unskilled production workers. The annual operating time refer to 4 week per year, 5 days per week, 2 shifts per day, and 8h per shift.

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Table 8.3b Equipment Cost Estimation of the Wine Manufacturing Plant No Process

Qty Size Units

Cost

1 Fermentation tanks

20

40 t

1000

2 Storage tanks

10

150 t

1000

3 Crusher/destemmer

1

5 t/h

150

4 Screw press

1

5 t/h

150

5 Plate heat exchanger

1

5 t

150

6 Microfiltration

1

1 t/h

150

7 Bottling machine

1

5 t/h

400 3000 k$

Table 8.3c Capital Cost Estimation of the Wine Manufacturing Plant Purchased Equipment Cost

Ceq

3.00 M$

Lang Factor

fL

3.00 -

Working Capital Factor

fW

0.25 -

Fixed Capital Cost

CF

Working Capital Cost

CW

Total Capital Cost

CT

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9.00 1.35 10.35 M$

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Table 8.3d Assumptions for Operating Cost Estimation of the Wine Manufacturing Plant Wine Plant Product Rate

PR

Operating Season

wpy

5.00 t/h 4 w/y

Annual Operating Time

ty

320 h/y

Operating Cost Factors Data Fixed Manufacturing Cost Factor

fMF

0.10 -

Overhead Cost Factor

fOver

0.05 -

Utilities Cost Crude Oil Cost

Cb.

67.0 $/bbl

Fuel Cost

Cf.

0.07 $/kWh

Electricity Cost

Ce.

0.11 $/kWh

Steam Cost

Cs.

0.08 $/kWh

Cooling Water Cost

Cc.

0.01 $/kWh

Freezing Cost

Cz.

Process Water Unit Cost

Cw.

0.50 $/m3

Waste Treatment Cost

Cj.

0.05 $/m3

0.11 $/kWh

Labor Cost Characteristics Labor Rate Cost

CL

15.0 $/h

Labor Cost Correction Factor

fL

2.50 -

Overtime Correction Factor for Second Shift

fL2

1.50 -

Overtime Correction Factor for Third Shift

fL3

2.00 -

Material Unit Cost Product

Cp.

4.00 $/kg

Raw Materials

Cr.

0.50 $/kg

Packaging Material

Cg.

0.10 $/p

For the purposes of the application example, it is assumed that the cost of the raw material (grapes) includes the minor cost of the additional processing materials.

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Table 8.3e Operating Cost Estimation of the Wine Manufacturing Plant Manufacturing Cost Raw Materials

Cmat

Packaging

Cpack

1.46 0.21

Utilities

Cutil

0.03

Waste Treatment

Cwst

0.00

Labor

Clab

0.48

Variable Manufacturing

Cmv

2.19

Fixed Manufacturing

Cmf

0.90

Overheads

Cover

Manufacturing

CM

0.27

Capital Charge

e CT

0.86 -

Total Annualized

TAC

4.22 M$/y

3.36 M$/y

Unit Cost ($/kg) . …

3.00

2.50

Capital Charge Overheads

2.00 Fixed Manufacturing

1.50

1.00

0.50

Utilities

Labor Packaging

Waste Treatment

Raw Materials

0.00 1 Cost Operating

Figure 8.3c Operating cost estimation of the wine manufacturing plant.

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6. Plant Profitability A plant profitability analysis of the design and economics of the wine manufacturing plant was performed according to the procedure described for the bread manufacturing plant (see Section I.6 of this chapter). Similar results were obtained. The assumptions for the plant profitability estimation are summarized in Table 8.1f of this Chapter. Figure 8.3d presents the cumulated cash flow CCF and the net present value NPV of the yogurt manufacturing plant during its lifetime. The characteristic economic quantities are indicated in this Figure: Depreciated period ND, loan payment period NL, positive salvage period NS, and project life time NE. The simple payback period SPB and the depreciated payback period DPB are obtained as the intercepts with the time axis of the CCF and NPV curves, respectively. Based on these data, the resulting profitability indices are also summarized in Table 8.3f. Table 8.3f Plant Profitability of the Wine Manufacturing Plant Profitability Sales Income

S

5.38 M$/y

Manufacturing Cost

CM

3.36 M$/y

Gross Profit

Pg

2.02 M$/y

Net Present Value

NPV

9.11 M$

Own Capital Cost

Co

Capital Return Ratio

CRR

1.76 -

Internal Rate of Return

IRR

0.25 -

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Cash flow (M$)

3.0

2.0 Tax

Tax Reduction

1.0

Net Profit

Loan Payment 0.0 1

2

3

4 5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Operating year

6

CCF

Net present value / Own Capital

4

NPV

2

0 0

5

10 ND

15

20 NL

25 NS

30 NE

-2 Operating year

Figure 8.3d Annual cash flow (upper) and cumulated cash flow (CCF) and net present value (NPV) of the wine manufacturing plant.

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7. Sensitivity Analysis A sensitivity analysis of the wine manufacturing plant was performed according to the procedure described for the bread manufacturing plant (see Section 1.7 of this chapter). Similar results were obtained. Figure 8.3e shows the three characteristic points of the break-even analysis while Figure 8.3.f presents the annual profit for three different values of the product price. Figure 8.3g reveals the effect of the resource prices (equipment Ceq, raw materials Cr, labor CL, utilities Cb) and the economic environment (tax rate t, discount rate i, loan interest rate iL, and leverage L) on the Capital Return Ratio CRR (Net Present Value to the Own Capital invested Ratio), respectively.

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10

2 shifts

Annual income/outcome (M$/y)

.

1 shift

+ weekends

3 shifts

Sales

Manufacturing cost

5

Profit

0 0

100

200

300

400

500

600

700

800

Annual operating time (h/y)

Figure 8.3e Break-even analysis of the wine manufacturing plant. 4.0

Annual profit (M$/y)

Product price ($/kg) =

4.40

3.0

4.00 2.0 3.60 1.0

0.0 0

100

200

300

400

500

600

700

Annual operating time (h/y)

Figure 8.3f Break-even analysis of the wine manufacturing plant.

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Capital Return Ratio

.

0.50

0.25

Cr

CL 0.00

Cb

Cb

CL -0.25 Cr Ceq

-0.50 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0.40

Relative variation

0.50

Capital Return Ratio

.

L 0.25

i t

0.00

-0.25

iL

iL t

L

i

-0.50 -0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

Relative variation

Figure 8.3g Sensitivity analysis of the wine manufacturing plant.

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0.40

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IV. ECONOMIC COMPARISON The results presented in the previous sections of Chapter 8 are summarized and compared. in this section. Table 8.4a summarizes the energy requirements in the 3 food manufacturing plants, considered in Chapter 8. The theoretical energy requirement, in MJ/kg product, was calculated from material and energy balances of each plant. The estimated (actual) energy requirement was calculated from the theoretical, assuming a 25% energy loss. It is evident that the energy requirements of the food manufacturing plants, considered in this chapter, are generally lower than the energy requirements of the food preservation and food ingredients plants, considered in Chapters 7 and 9, respectively. However, food manufacturing plants, using energy intensive operations, such as evaporation and drying, may require much higher energy per unit product mass. Figure 8.4a compares the plant profitability between the examined food manufacturing plants in both terms of net present value (NPV) and internal rate of return (IRR). Figure 8.4b is an interesting and useful figure. It represents, in a graphical way, the analysis of the cost breakdown to its components. • The most significant component of the production cost is the raw material cost followed by the labor cost. • Utility cost is not significant for some food manufacturing plants. • Packaging cost is important in yogurt and wine manufacture, but less important in baked bread. • Waste treatment cost is of minor importance in the food manufacturing plants examined in this chapter. Finally, Figure 8.4c presents in a comparative manner the cumulated cash flow (CCF) and the net presents value (NPV) for all the examined food manufacturing plants as a function of their lifetime. It must be noted that all the previous results in this chapter are very sensitive to techno-economic assumptions made and any change in them may modify significantly the results. Table 8.4a Energy Requirements of Food Manufacturing Plants Food Plant Energy Requirements, MJ/kg product Theoretical Estimated 1. Bread 1.30 1.73 0.73 1.00 2. Yogurt 3. Wine 0.54 0.72 Note: To convert MJ/kg to kWh/kg divide by 3.6.

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0.40

Yogurt

Internal rate of return (IRR)

0.30

Bread

Wine

0.20

Food manufacturing plants

Food preservation plants 0.10

0.00 0.00

2.00

4.00

6.00

8.00

10.00

Net present value (NPV)

Figure 8.4a Plant profitability comparison.

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14.00

16.00

18.00

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Bread 1.00

Unit Cost ($/kg)

Fixed Manufacturing

Capital Charge Overheads

Labor

0.50

Utilities

Waste Treatment

Packaging

Raw Materials

0.00 1 Cost Operating

Yogurt 1.00 Capital Charge

Unit Cost ($/kg)

Fixed Manufacturing

Overheads

Labor Utilities

Waste Treatment Packaging

0.50

Raw Materials

0.00 1 Cost Operating

Wine

Unit Cost ($/kg)

3.00

2.50

Capital Charge Overheads

2.00 Fixed Manufacturing

1.50

1.00

0.50

Utilities

Labor Packaging

Waste Treatment

Raw Materials

0.00 1 Cost Operating

Figure 8.4b Production cost comparison.

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Bread 10

8

Net present value / Own Capital

CCF 6

4 NPV 2

0 0

5

ND

10

15

NL

20

NS

25

NE

30

-2 Operating year

Yogurt 10

8

Net present value / Own Capital

CCF 6

4 NPV 2

0 0

5

ND

10

15

NL

20

NS

25

NE

30

-2 Operating year

Wine 10

Net present value / Own Capital

8

6 CCF 4

NPV

2

0 0

5

ND

10

15

NL

20

NS

25

NE

30

-2 Operating year

Figure 8.4c Cumulated cash flow (CCF) and net present value (NPV) comparison between the examined food manufacturing plants.

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REFERENCES Ahvenainen R, 2003. Novel Packaging Techniques. CRC Press. Becket ST ed, 1994. Industrial Chocolate Manufacturing and Use. Blackie Academic and Professional. Boulton RB, Singleton VL. Bisson LF, Kunkee RE, 1996. Principles and Practices of Winemaking. Chapman Hall. Doerry WT, 1995. Breadmaking Technology. American Institute of Baking. Hall GM ed, 1997. Fish Processing Technology, 2nd ed. Blackie Academic and Professional. Hallstrom B, Skjoldebradt C, Tragardh C, 1988. Heat Transfer and Food Products. Elsevier Applied Science. Levine L, Boehmer E, 1997. Dough processing systems. In Valentas KJ, Rotstein E, Singh RP, eds: Food Engineering Practice. CRC Press. Marshall RT, Goff HD, Hartel RW, 2003. Ice Cream 6th edition. Kluwer Academic/ Plenum Publ. Matz SA, 1989. Bakery Technology. Packaging, Nutrition, Product Development, Quality Assurance. Elsevier Publ. Matz SA, 1989. Equipment for Bakers. Elsevier Science Publ. Matz SA, 1992. Bakery Technology and Engineering, Van Nostrand Reinhold. Nagy S, Chen CS, Shaw PE, 1993. Fruit Juice Processing Technology. Agscience Inc, Auburndale. Ranken MD, Kill RC, 1993. Food Industries Manual, 23rd ed. Blackie Academic and Professional. Saravacos GD, Kostaropoulos AE, 2002. Handbook of Food Processing Equipment. Kluwer Academic / Plenum. Storm D, 1997. Winery Utilities. Chapman & Hall. Tamine AY, Robinson RK, 1999. Yoghurt: Science and Technology, 2nd edition. Woodhead Publ.

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9 Food Ingredients Plants

INTRODUCTION Food ingredients plants utilize agricultural and natural raw materials to separate and recover valuable food components, such as wheat flour, sugar, edible oils, pectin, protein, and salt, which are used in the manufacture of several food products. Wheat flour and other cereal flours can be considered as food ingredients, which are used in large quantities in the baking and other food industries. Various other food ingredients, used in smaller quantities, are produced by the Chemical Process Industries, e.g., flavors and gums, coloring materials, sweeteners, antioxidants, preservatives, vitamins, nutritive minerals, and special food chemicals. The raw materials of the natural food ingredients are bulk agricultural products of relatively low cost, such as cereal grains (wheat, corn), sugar beets or sugar cane, and soybeans. Some food ingredients are produced from byproducts of food preservation or food manufacturing plants, e.g., pectin from citrus or apple peels, and protein from cheese whey. The design and economics of food ingredient plants is based on conventional Chemical Engineering technology. The plants are optimized, instrumented and controlled, and the plant effluents are treated to meet the environmental requirements. Microbial spoilage and chemical or biochemical deterioration of food ingredients during processing are very limited, and hygienic and food safety requirements in such plants are less severe than in conventional food preservation and food manufacturing plants. Food ingredients plants produce higher value-added products, compared to the food preservation and food manufacturing plants. The raw materials are subjected to extensive processing in order to separate and purify the desired 323

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ingredient. As a result, the cost of processing is increased and the cost of raw materials becomes less important. Table 9.1 lists various food ingredients plants of importance to food manufacturing. Food flours (mainly wheat) are produced in large milling plants, using mechanical reduction (mills) and separation (sieving) equipment, operated continuously. A number of flour fractions are produced, used in bakeries and other food manufacturing plants. Flour mills are located near ports and large population centers. Bulk storage and transportation of flours are used extensively. Starch and sugar plants are generally large chemical engineering installations producing large quantities of food ingredients from agricultural raw materials. The food ingredients are separated, recovered and, if needed, modified by a series of mechanical, physical, and chemical processes. The plants use large amounts of energy (steam, fuel, electricity) and process water, and they produce significant amounts of wastes, which should be treated. Food biopolymer plants utilize agricultural raw materials and food plant wastes to produce pectin, gelatin, whey protein, etc., which are used in the manufacture of several food products. Food proteins are especially important because they provide the required high nutritive value to various foods. Vegetable oil plants produce large quantities of edible oils from oil seeds, olives, and corn, using mechanical expression, mechanical separation, and solvent extraction. These plants produce large amounts of by-products, which can be utilized in the production of proteins and other useful food ingredients (Shahidi, 2005). The liquid, solid, and gaseous wastes of these plants must often be treated to comply with the environmental pollution laws. Plant extracts are produced by water or solvent extraction of useful ingredients from vegetable plant materials, such as flavor compounds, gums, or phytonutrients (flavonoids, carotenoids, etc.). These ingredients are produced in relatively small quantities in specialized chemical processing plants. A large number of food chemicals and biochemicals are produced in specialized chemical plants, e.g., vitamins, food preservatives, and food enzymes. These ingredients are produced in relatively small quantities, often batch operated, using complex processes and specialized equipment, and hence they are relatively expensive materials.

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Table 9.1 Food Ingredients Plants Food Ingredient Category

Processing Plant

Food flours

Wheat Other grain Soya

Sugars / starches

Beet sugar, cane sugar Starches, modified starches Corn syrups, HFCS

Food biopolymers

Pectin Cellulose Gelatin Whey protein Soy protein

Vegetable oils

Soybean oil Corn oil Rapeseed oil Olive oil

Plant extracts

Flavors, colors Hydrocolloids Gums Phytonutrients

Food chemicals and biochemicals

Vitamins Amino acids Antioxidants Acidulants Preservatives Enzymes

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I. BEET SUGAR PLANT The Economics of a large beet sugar plant is discussed briefly in this application example, following the procedure of the examples of food preservation and food manufacturing plants (Chapters 7 and 8). The detailed design and economic analysis of such plant would require more engineering and economic information and data, which are found in books and literature on Chemical Plant Design (Perry’s Chemical Engineers’ Handbook, 1997; Peters and Timmerhaus, 2003). Beet sugar plants are located in agricultural regions, growing large amounts of sugar beets. Sugar processing involves several chemical engineering operations and processes, such as sugar extraction, juice clarification, sugar crystallization, and sugar drying. The sugar plants consume large quantities of energy and process water, and generate considerable amounts of wastes. Sugar molasses and dried sugar pulp are byproducts of considerable economic value. Cane sugar is produced from sugarcane in similar sugar plants, except for the juice extraction process, which is based on the mechanical expression (pressing) of the raw material (Chen and Chou, 1993). Raw cane sugar is produced in sugar mills in cane growing regions (tropical or semi-tropical), and refined to pure crystalline sugar in sugar refining plants, located near large consumption centers (Chou, 2000). 1. Outline of Process Technology a. Raw Materials Sugar beets are grown in large quantities in several countries of the Northern Hemisphere and they are harvested mechanically during the fall, so that the sugar plants operate during the fall and winter of each year (“campaign”). Sugar beets contain approximately 23% TS (Total Solids) by weight, which include 16.6% sucrose and 6.4% nonsugars. Of the 16.6% sucrose, about 14% is recovered in the sugar plant as sugar, 2% goes to the byproduct molasses, and 0.6% is lost during processing. Molasses contain about 80% TS, half of which is sugar and the rest nonsugars (McGinnis, 1971; Schneider, 1968). The harvested beets are transported by truck to the sugar plant, where they are stored either in silos or in bulk until processed. b. Sugar Extraction The beets are transported from the storage area to the processing plant by fluming (hydraulic transport in a water canal). At the same time they are washed of external materials, such as soil, leaves, and weeds, while various stone materi-

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als are removed. Approximate water requirements for beet transport 6 m3/t, and for washing 2 m3/t. The washed beets are cut into long pieces (strips or “cosettes”) 5–7 cm long. Special horizontal rotating cutting machines (slicers) are used with sharp knives, which are replaced and sharpened periodically. The sugar is extracted (or leached) from the beet pieces by contacting with hot water for sufficient time. Under these conditions, the sucrose molecules will diffuse from the interior to the surface of the beet pieces, and then transfer to the surrounding solution. Modern sugar plants use continuous extraction equipment, such as the DDS (De Danske Sukkerfabriker) system. The DDS extractor is an inclined (10o) long trough, in which a slowly rotating screw transports the beet pieces from the bottom to the top, while the extraction hot water flows by gravity from the top. The extractors are about 20 m long and they are operated at temperatures 70–80oC and residence time about 1.5 h. Heating of the beet pieces inactivates the cell membranes of the beet, facilitating the diffusion of sucrose into the surrounding water. Clean steam condensates from the sugar evaporators may be used in the extraction process. The extracted beet pieces (or pulp) contain the water-insoluble solids (“marc”), which are dried to an animal feed byproduct. The yield of wet pulp (16% TS) is about 32% of the beets and, after drying, to 90% TS it corresponds to about 5.6% of the beets. The extracted juice is clarified from the colloidal and dissolved nonsugar substances, which may affect adversely the processing operations (concentration and crystallization) and the quality (color, impurities) of the sugar. The juice is treated repeatedly with lime (about 2.5 kg CaO / ton of beets) and carbon dioxide and filtered to bring about the required chemical reactions and separation processes of the juice clarification. A lime kiln is normally installed in the sugar plant, producing calcium oxide from limestone (calcium carbonate) and carbon dioxide in about equal amounts. The heat of reaction, 1.76 MJ/kg limestone, is provided by the burning of 60 kg coal/t. Addition of lime to the juice at 80–90oC raises the pH to about 11, causing coagulation of the colloids and destruction of most of the invert sugars and amides in the juice, which cause problems in the concentration and crystallization of the sugar. The lime-treated juice is saturated with carbon dioxide gas for the purpose of precipitating and removing the lime as calcium carbonate. Treatment of the sugar juice with lime, followed by carbonation with CO2 and filtration, is repeated one or more times until a satisfactory clarified juice is obtained. All juice is filtered before concentration, using some rotary and pressure filters. Modern membrane separation technology (microfiltration and ultrafiltration) may replace the lime clarification process.

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c. Juice Concentration The clarified sugar juice, containing normally 15% sucrose (15oBrix), is concentrated to a sugar solution of about 65oBrix, using an economic industrial concentration system. Since large amounts of water must be removed from the sugar solution, energy-efficient systems are necessary, such as multiple-effect evaporators or thermal/mechanical vapor recompression evaporators. A typical concentration system, used in the sugar industry, is the 5-effect feed-forward short-tube evaporator (Saravacos and Kostaropoulos, 2002). Clarified sugar solutions of low oBrix are relatively heat-stable and they can be evaporated at temperatures above 100oC. The temperature in the first effect (15oBrix) should not exceed 130oC, while in the last (5th) effect (65oBrix) it should be less than 100oC (e.g., 70oC), necessitating vacuum operation of the last effects. The boiling point elevation (BPE) of dilute sugar juices (lower than 30oBrix) is less than 1oC and it can be neglected in preliminary calculations. However, BPE becomes important at higher sugar concentrations, e.g., 4.4oC at 65oBrix. The steam used for heating the first effect of the evaporator is usually saturated at 3.6 bar pressure and temperature 140oC. In the large beet sugar plants, the process steam is usually provided by a power generation system, which uses superheated steam at e.g., 26 bar pressure and 370oC temperature. The superheated steam is produced by the steam boiler and it drives a power generating turbine (cogeneration system). Thus, power is generated for the electrical needs of the processing plant, while the exhausted low-pressure steam is used for heating (Section II of this chapter). The steam condensates from the evaporator units are used for preheating the sugar solutions in the clarification operation. Part of the condensates is returned to the feed water of the steam boiler d. Sugar Crystallization The juice concentrate (65oBrix) is filtered using filter aids and crystallized in evaporative crystallizers, removing part of the water and yielding a sugar mass (magma) containing 90% sucrose, and a thick solution of sugar and nonsugars (molasses). The batch crystallizers are operated in vacuum at about 90oC, using steam from the steam boiler or vapors from the evaporator. The thick sugar solution is seeded with ground sugar crystals (seed size 10 μm and concentration 8 g/m3) to initiate crystallization, and sufficient time is allowed for crystal growth. The sugar magma is separated in centrifuges into crystalline sugar and molasses. The separated raw sugar is washed with water and purified by recrystallization one or two times. Refined white sugar is produced by dissolving the raw (cane) sugar in hot water, vacuum evaporation, and re-crystallization.

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e. Centrifugation Vertical basket centrifuges are used to separate the sugar magma from the molasses. The capacity of each centrifuge is about 600 kg, and several centrifuges, operated in parallel, are required in a large sugar plant. The separated sugar magma is either dried or purified by re-crystallization. The separated sugar, containing about 97% TS, is washed in the centrifuge with water and the wash sugar solution is returned to the crystallization system. f. Drying of Sugar Sugar, separated from the molasses in the centrifuges, is dried from about 97% TS to 99.97% TS in a rotary air-dryer. Relatively high air temperature and short residence times are used to prevent heat damage to the dried sugar. The hot air in the dryer should not exceed 90oC and the discharged sugar should be at less than 45oC . g. Drying of Beet Pulp The pulp residue, produced in the sugar extraction of beets and the filtrates of the clarification process is first pressed mechanically to remove the excess water, e.g., from 14% to 18% TS, and the pressed pulp is dried from about 18% to 90% TS by air-drying. Since a large amount of water must be removed, high capacity rotary dryers are used. The dryers can be operated at relatively high temperatures, since the dried animal feed produced is a thermally stable product. h. Sugar Molasses Molasses, the liquid residue of sugar crystallization, and dried beet pulp are two important byproducts of sugar processing, which have a considerable economic value. Molasses contain about 80% TS, half of which is sugar and the rest various nonsugar substances of high nutritive value. Molasses is used as a raw material in several fermentation industries, as an animal feed, often mixed with dried beet pulp, and as a sugar additive in some food products. i. Plant Effluents Large amounts of water are used in the beet sugar plant, for example 11 t water/ton beets. Due to extensive water recycling (e.g., 10 times), the net use of water and the wastewater outflow (effluent) is about 1 ton water/ton beets. The waste water from the sugar plant contains small amounts sugars and organic substances (BOD) which can be easily oxidized in biological oxidation systems. The treatment of food wastes is discussed briefly in Chapter 3.

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j. Sugar Storage The dried crystalline sugar may be stored in large concrete silos of capacity about 5000 t each. Sugar is packaged in 40 kg multiwalled bags for commercial use. For retail distribution, consumer bags (paper or plastic) of 0.5 to 1.0 kg are used. Large quantities of sugar are used by the food industry in the form of sugar solutions of 77% TS (invert liquid sugar), which is transported in 30 t trucks. 2. Preliminary Sugar Plant Design A preliminary design of the beet sugar plant can be prepared following a procedure similar to that of the Application Examples of Chapters 7 and 8. The sizing and costing of the process equipment (Capital Cost estimation) can utilize the methods and data of Chapter 5. In addition, technical and cost data on special equipment, such as size reduction (slicing), sugar extraction, juice clarification, lime production, juice clarification and filtration, sugar crystallization, and sugar centrifugation can be found in known Chemical Engineering references (Perry et al., 1997; Peters and Timmerhaus, 2003; Walas, 1988; Couper, 2003) or from quotations of equipment manufacturers and suppliers (Saravacos and Kostaropoulos, 2002). For illustrative purposes, a medium-sized beet sugar plant of capacity 3000 t/d beets is considered. Figure 9.1 shows the simplified process block diagram of material and energy balances, while the main process flowsheet is shown in Figure 9.2. Table 9.1 outlines the material balances of the 3000 t/d beet sugar plant, while the major plant equipment is listed in Table 9.2. White sugar is produced by washing with water the separated sugar on the centrifuges and recrystallizing the solution one or more times. Thus, the yield of sugar is reduced and more molasses is produced.

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Water ppm SO2

Washing Beets 16.6oB

1000 kg

Cutting

Electricity 0.5 kW

Beets 16.6oB

1000 kg

Water 1000 kg Electricity 0.5 kW

Electricity

Lime 2.5 kg

Beet pulp Extraction

Steam

327 kg

93 kW

1 kW Pressing

Water

16% TS Juice 15oB

1060 kg

Beet pulp 16%TS

327 kg

CO2 2.5 kg

Fuel

ppm SO2 Clarification

Electricity 0.2 kW

Sludge

200 kW Drying

Fuel Juice 15 B

90 kW

1000 kg Dried pulp 90%TS

Steam Electricity

154 kW

Electricity Water

o

58 kg

Condensate Evaporation

0.3 kW Concentrate 65oB

230 kg Sludge

Filtration

Electricity 0.2 kW

Concentrate 65oB

230 kg

Steam Electricity

41 kW

Crystallization A

0.2 kW Sugar magma 90%TS

166 kg

Water Centrifugation A

Electricity 2 kW

Molasses

146 kg

Crystallization B

Electricity 0.2W Water

Centrifugation B

Electricity 1 kW

Steam 6 kW

Wet sugar 97%TS

156 kg

Fuel Electricity

3 kW

Drying

0.5 kW Raw sugar

Electricity

140 kg

Sieving

0.5 kW Raw sugar

140 kg

Figure 9.1 Material and energy balances of a beet sugar plant. Basis: 1 t/h beets.

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W

R

L

W

W

L s

L s

S

S

G

P A W

S

s

S

R

s

G

C

F

S c w S s

P

s

A

G c

S

S

s

G

G

C A

F

P

S A

s

K

P s

P

K

Figure 9.2 Simplified process flowsheet of a beet sugar plant.

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Table 9.1 Material balances of the 3000 t/d beet sugar plan Plant capacity, sugar beets: 3000 t/d = 125 t/h = 270,000 t/y Operating time: 90 d/y = 2160 h/y Beet composition: 23%TS = 16.6% sucrose + 6.4% nonsugars Sugar yield: 14% of beets + 2% molasses + 0.6% sugar losses = 37 800 t/y sugar + 5400 t/y molasses Beet pulp: Yield of 16% TS wet pulp 312 kg/t beets or 39 t/h Dried pulp 6.9 t/h = 14 978 t/y 90% TS Clarified beet juice of 15oBrix 1 t/t beets. Juice concentration 15 to 65oBrix Juice concentrate 230 kg/t beets = 28.7 t/h. Water evaporation 1000 – 230 = 770 kg/t beets = 96 t/h 5-effect evaporator: water evaporated per effect 96/5 = 19 t/h Sugar magma 90% TS in crystallizers 166 kg/t beets = 20.7 t/h Water evaporated in crystallizers 28.7 – 20.7 = 8 t/h The 20.7 t/h sugar magma is separated in batch vertical centrifuges to 19.2 t/h centrifuged sugar 97% TS and 1.5 t/h of molasses. The sugar is washed with water and the sugar washings are recrystallized, resulting in 18.0 t/h sugar 97% TS and 1.0 t/h molasses. Total molasses production 2.5x2160 = 5400 t/y The 97% TS sugar is dried in a rotary air dryer to 17.5 t/h sugar of 99.97% TS (0.03% moisture). Beet pulp 16% TS 39 t/h pressed to 34.7 t/h pulp. Water removed 4.3 t/h. Pressed pulp 34.7 t/h dehydrated by air drying to 6.9 t/h dried pulp 10% TS. Water removed 27.8 t/h. Liming of beet sugar for clarification requires 25 kg CaO (44.6 kg limestone)/t beets, or 5.6 t /h. limestone. Total limestone required 2160x5.6 = 12,096 t/y Fuel required 0.08x12096 = 968 t/y coke (coal product).

In the beet sugar plant, considered here, the theoretical energy requirements are about 15 MJ (4.2 kWh)/kg sugar, and practically about 18 MJ (5 kWh)/kg sugar. Most of the energy is consumed in heating processes, such as evaporation and drying. Significant energy economy can be achieved by utilizing the hot condensates from the evaporation effects to heat the beet juice or the crystallizers.

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In some sugar plants, cogeneration of heat and electrical power (Section II of this chapter) may reduce substantially the energy cost. The 3000 t/h sugar beet plant, producing 17.5 t/h sugar requires a total energy of 17.5x5 = 87.5 MW. Material and energy data from Figure 9.1 show that the energy requirements of 18 MJ/kg sugar are broken down to about 8 MJ/kg sugar for steam and electricity and 10 MJ/kg sugar for fuel heating (dryer and calciner). Thus, the power requirement of a cogeneration plant would be 8x17,500 MJ/h = 39 MW. Since the steam energy is about 2.5 MJ/kg, the steam requirement would be 56 t/h. The energy required for drying and calcining 48.5 MW can be supplied by fuels, e.g., natural gas of 40 MJ/kg heat value, 48.5x3600/40 = 4365 kg/h or 4.4 t/h. Table 9.2 Major processing equipment of the 3000 t/d beet sugar plant - Beet slicing machines (50 t/h), needed 3x50 =150 t/h - Continuous countercurrent sugar beet extractor, DDS type, 150 t/h - Lime kiln (calciner), 150 t limestone/d - Juice clarification tanks (50 t/h), needed 3x50 = 150 t/h - Rotary filters for beet sugar juice (50 t/h), needed 3x50 = 150 t/h - Rotary filters for second filtration of beet sugar juice (50 t/h), needed 3x50 = 150 t/h - Pressure leaf filers for beet sugar juice (50 t/h), needed 3x50 = 150 t/h - 5-effect short-tube evaporator for sugar juice concentration 15 to 65oBrix. Total water evaporation 96 t/h, water evaporation per effect 19.2 t/h. - Pressure leaf filter for the sugar juice concentrate, 30 t/h - Sugar evaporative crystallizers, 30 t/h juice concentrate - Sugar magma centrifuges (2 t/h), needed 10x2 = 20 t/h - Rotary air dryer for sugar drying 20 t/h sugar from 3% to 0.03% water. Water evaporation, 0.6 t/h - Rotary air dryer for drying 34.7 t/h pressed pulp 18% TS to 6.9 t/h dried pulp 90% TS. Water evaporation 27.8 t/h. - Steam boilers: 2 boilers of capacity 25 t/h steam at 25 bar. - Bulk storage of sugar: 8 large concrete (cement) bins of 5 kt capacity each. - Bulk storage of molasses: 5 steel tanks of 1 kt capacity each

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3. Outline of Sugar Economics Using the procedures described in Chapters 5 and 6, and cost data from the application examples of Chapters 7 and 8, the equipment cost was estimated to be about 25 M$. Using the Lang factors of Chapter 4, the estimated capital cost (investment) of a 3000 t/d sugar beet plant would be approximately from 75 M$ (main processing plant) to 100 M$ (grassroots plant). Thus, the capital cost of a medium-sized beet sugar plant is about 10 times higher than the cost of most food processing plants discussed in Chapters 7 and 8. Sugar plants are industrial installations much larger than typical food preservation and food manufacturing plants. Large capital investments are also required for some other major food ingredients plants, such as vegetable oils, grain flours, starches, and proteins. The profitability of the sugar beet plant can be estimated, following a procedure similar to the examples of food processing plants. The operating cost of the sugar plant is affected strongly by the price of the raw material (sugar beets) and the energy (mainly steam) cost. Sugar plants produce large quantities of wastewater containing considerable amounts of sugars and other organic compounds which could pollute the environment, if discharged untreated. Strict pollution regulations may require the installation of wastewater treatment facilities at the plant site, increasing significantly the plant cost. Primary treatment (mechanical separation) of suspended particles, followed by secondary treatment (bio-oxidation) is necessary in most sugar plants. During the recent years, beet sugar is facing a stiff competition from cane sugar, which is produced in larger quantities at lower cost in tropical and subtropical countries. Sugar consumption is decreasing worldwide, due to dieting and the substantial use of artificial sweeteners. The overcapacity of sugar plants and the low sugar prices of beet sugar have led to government subsidies to beet growers in Europe. The world sugar market is discussed by Spence (2005). The limited supplies and increasing prices of oil have created an expanding market of renewable fuels, especially bioethanol, i.e. ethanol produced by fermentation of sugar-containing agricultural products. Large quantities of bioethanol are produced from cane sugar in Brazil and from corn in the USA. Bioethenol is used mainly as an automobile fuel, mixed with gasoline. In the European Union, a number of sugar plants are converting partially or entirely to bioethanol plants, utilizing the excess capacity of sugar beet production. The bioethanol plant consists of a beet juice extraction and clarification section, similar to the beet sugar plant, a fermentation section, similar to the wine fermentation plant of Chapter 8, and an ethanol distillation section, discussed in Perry’s Chemical Engineers’ Handbook (1997) and special books on Distillation, and in Maroulis and Saravacos (2003). A simplified computer model has been proposed for the design of a mixed beet sugar – bioethanol plant (Henke et al., 2006).

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Bioethanol can be also produced from corn and other starch-containing agricultural products by enzymatic conversion to sugars, followed by fermentation and distillation. The capital cost of a 100 kt/y bioethanol plant from sugars is about 100 M$. Typical cost data for beet sugar and byproducts are presented in Table 9.3: Table 9.3 Typical Cost Data for Beet Sugar and Byproducts (2006) Sugar beets 50 $/t White sugar 700 $/t Molasses 200 $/t Dried pulp 100 $/t Bioethanol 400–800 $/t

II. OVERVIEW OF PROCESS PLANT OPTIMIZATION A straight forward design, like the concept applied in previous examples, rarely is profitable for complex plants. Thus, a severe attempt is needed toward plant optimization. The plant optimization is also called in economic terminology as economic balance (Couper, 2003). The basic theory of optimization, the problem definition, and the applied mathematical techniques are developed in chemical engineering text books (Peters and Timmerhaus, 2003; Edgar and Himmelblau, 1988; etc.). Applications in food process optimization are presented by Maroulis and Saravacos (2003). An information flow diagram for conceptual plant design, in which the optimization phases are introduced, is presented in Figure 9.3. The following stages are involved: (1) Selection of the proper flowsheet to realize the required production; (2) material and energy balances, which are specifying the process requirements of the plant; (3) sizing and rating of the required industrial process equipment; (4) cost estimation; (5) financial and profitability analysis; (6) parametric optimization; and (7) structural optimization of the process. Thus, two types of optimization is usual considered: 1. Parametric Optimization The parametric optimization, is a mathematical procedure towards the mathematical optimum of given economic functions. No flowsheet changes are examined and the corresponding information flow diagram is presented in Figure 9.4. © 2008 by Taylor & Francis Group, LLC

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Process Specifications 1

2

3

4

5

Process Flowsheet Synthesis

Material and Energy Balances

7

Equipment Sizing and Rating

Equipment and Utilities Costing

6

Structural Optimization

Parametric Optimization

Financial and Profitability Analysis

Process Design Results

Figure 9.3 Information flow diagram of process design (Maroulis and Saravacos, 2003).

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Process specifications

Design variables

Technical data

Economical data

Process mathematical model

Optimization technique

Economic objective function Optimum solution

Figure 9.4 Information flow diagram for process optimization (Maroulis and Saravacos, 2003).

2. Structural Optimization Structural optimization refers to flowsheet changes towards the optimum flowsheet structure. No pure mathematical techniques can be effective. Instead, expert systems of artificial intelligent tools may be used. Figure 9.5 summarizes some special techniques proposed for chemical and food engineering. Heat exchanger networks optimization is an efficient technique of energy integration (Linnhoff et al., 1982). Thermal energy and power cogeneration is a specific case of energy integration.

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Optimization

Parametric

Structural

(conceptual mathematics)

(expert systems, artificial intelligent)

Network optimization

Superstructure (leads to parametric)

Heat exchangers Distillation columns Chemical reactors

Figure 9.5 Structural optimization. 3. Cogeneration in Food Processing In large food processing plants, where very large amounts of energy are consumed, such as beet sugar and wet corn milling, considerable energy savings may be achieved by using the energy cogeneration system (Teixeira, 1986). The topping system is normally used, in which high-pressure steam, e.g., 120 bars, is used to generate electricity, while the exhaust low-pressure steam, e.g., 2 bars, is used in heating process applications. Figure 9.6 shows a simplified diagram of a cogeneration system, consisting of the high-pressure steam boiler, the steam turbine, the electrical generator, and the necessary piping. Cogeneration is usually applied to beet and cane sugar plants (Section I of this chapter). Another potential application of this energy-saving system could be in large citrus juice concentrate plants (application example 7.2). The capital investment for cogeneration is considerable (high-pressure steam boiler, steam turbine, electrical generator). Cogeneration is justified only when electricity cost is high and fuel cost is low.

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Chapter 9 Flue HPS High Pressure Steam

Electricity

Steam turbines

MPS Medium Pressure Steam

LPS Low Pressure Steam Boiler Condensate

Air

Fuel

Figure 9.6. Cogeneration system.

REFERENCES Chen JCP, Chou CC, 1993. Cane Sugar Handbook, 13th ed. J Wiley. Chou CC, 2000. Handbook of Sugar Refining. J Wiley. Couper JR, 2003. Process Engineering Economics. Marcel Dekker. Edgar TF, Himmelblau DM, 1988. Optimization of Chemical Processes. McGraw Hill. Henke S, Bubnik Z, Hinkova A, Pour V, 2006. Model of a sugar factory with bioethanol production in program “Sugars”. J Food Engineering, 77, 416. Linnhoff B et al., 1982. User Guide for Process Integration for the Efficient Use of Energy. The Institution of Chemical Engineers, UK. Maroulis ZB, Saravacos GD, 2003. Food Process Design, Marcel Dekker. McGinnis RA, ed, 1971. Beet Sugar Technology, 2nd edition. Beet Sugar Development Foundation. Perry RJ, Green DW, 1997. Perry’s Chemical Engineers’ Handbook, 7th edition. McGraw-Hill.

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Peters SM, Timmerhaus KD, 2003. Plant Design and Economics for Chemical Engineers, 5th edition. McGraw-Hill. Saravacos GD, Kostaropoulos AE, 2002. Handbook of Food Processing Equipment. Kluwer Academic / Plenum Publishers. Schneider F, 1968. Technologie des Zuckers. Schaper Verlag. Shahidi F, ed, 2005. Bailey’s Industrial Oil and Fat Products, 6th ed., J Wiley. Spence D, 2005. The World Sugar Market, CRC Press. Teixeira AA, 1986. Cogeneration in food processing plants. In: Energy in Food Processing, RP Singh, ed.. Elsevier. Walas SM, 1988. Chemical Process Equipment. Butterworth.

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Appendices

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I. GLOSSARY OF ECONOMIC TERMS Administrative cost: Administrative and offices salaries, rent, auditing, legal, engineering, etc. expenses. Amortization: Same as Depreciation, but the period of time (life) is definitely known. Annual net sales: Kilograms (tons) of product sold times the net selling price. Annual report: The report of management to the shareholders and other interested parties at the end of a year of operation showing the company status, its funds, profits, income, expenses, and other information. Assets: The book value of property owned by a firm. Balance sheet: A tabulation of the assets, liabilities, and stockholders’ equity for a company. The assets must be equal to the liabilities plus the stockholders’ equity. Battery limits: A boundary around the equipment units which constitute the process plant. Plant facilities outside the boundary limits are defined as “off-site” or “outside battery limits”. Book value: The original investment minus the accumulated depreciation. Break-even chart: An economic production chart showing the point at which the total revenue equals the total cost of production. Byproduct: A product made in the production of a main product, which may have a value in itself, or it may be used as a raw material for another product. Campaign: A lengthy production run, followed by plant shutdown for cleaning, maintenance, or modifications. Successive campaigns may be made either for a single or for different products. Capacity (plant): The maximum production capability of a process plant per unit time, expressed in tons/day or similar units, assessed by a production trial over of a period of one to three days. The annual capacity is the product of maximum daily capacity and the equivalent availability (days/year) of the plant to produce at maximum daily capacity. Capital cost: The sum of fixed capital (investment) and working capital. Capital ratio: The ratio of capital investment to sales; it is the reciprocal of the capital turnover. Capital turnover: The ratio of sales to capital investment; it is the reciprocal of the capital ratio. Cash: Money which must be on hand to pay for monthly operating expanses, such as raw materials, wages, salaries, etc. Cash flow: Net income after taxes and depreciation. CIF (Cost, insurance, freight): The exporter’s payment of the cost of shipping a product to the importing country’s destination. Commodity: An industrial product traded usually in large volume at the same specifications. Common stock: Money paid into a corporation for the purchase of common stock which becomes the permanent capital of the firm. The common stock can be transferred to individuals or firms. Consumer good: A product which requires no further processing prior to use by the ultimate consumer. Contingency: Unforeseen cost elements, likely to occur. They include costs occurring from minor design changes in the project, due to weather, currency exchange rate, or inflation. © 2008 by Taylor & Francis Group, LLC

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Cost of capital: The cost of borrowing money (interest rate) from all sources, i.e. loans, bonds, preferred and common stocks. Cost of sales: The sum of fixed and variable (direct and indirect) costs for producing a product and delivering it to the customer. Creditors: Companies or persons to whom money is owned by a Company, e.g. for purchase or raw materials or utilities. Depreciation: A reasonable time, allowed by Tax Authorities for wear and obsolescence of equipment used in industry. The period of time (life time) is estimated (not known definitely). Depreciation is deductible from income for tax purposes. Depreciation methods: Straight line (SL), double declining balance (DDB), and modified accelerated cost recovery system (MACRS). Direct cost (expenses): The cost directly associated with the production of a product, like utilities, labor, maintenance, etc. Direct labor cost (expenses): The cost of labor involved in the actual production of a product or service. Discounted cash flow rate of return (DCFR): The interest rate at which the net present value (NPV) is equal to zero. The DCFR must exceed the cost of capital (interest) for a project to be profitable. Discounted payback period (DPB): The time at which the Net Present Value (NPV) equals zero. Distribution cost: The cost of advertising, samples, travel, freight, warehousing, etc. to distribute a product. Dividend: A share of profit distribution to stockholders. Earnings: The difference between income and operating cost (expenses). EBITDA: Earnings before interests, taxes, depreciation. Economic Value Added (EVA): Profit above the cost of capital generated by a company. Equity: The funds owned by a company, including those of new share issues and retained earnings from profitable operation. Exchange rate: The rate at which one international currency can be exchanged for another. FIFO (first in, first out): The first material going into an operation is the first used or going out. Fixed assets: The real material facilities that represent part of the capital in an enterprise. Fixed operating cost: Cost of a product, in $ per unit time, which is unchanged with a change of production rate. FOB (Free on board) price: Price of equipment or product on board ship in country of origin. The importer pays the subsequent cost of shipping the product to its destination. Goods manufactured, cost of: The total cost, direct and indirect, including overhead charges. Grass roots plant: A complete plant including main processing and off-sites. Gross domestic product (GDP): The sum of the goods and services produced by a nation within its borders. © 2008 by Taylor & Francis Group, LLC

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Gross national product (GNP): The sum of the goods and services produced by a nation including domestic and foreign activities attributable to that nation. Indirect cost (expenses): Manufacturing cost that is not directly related to the amount of product processed, such as depreciation, local taxes, insurance, etc. Internal rate of return (IRR): Same meaning with the “discounted cash flow rate of return” (DCFR). Inventory: The quantity of raw materials and /or supplies held in a process or in storage. Leverage: The influence of debt on the earning rate of a company. Liabilities: The economic obligations (debts) of a company. Market value added: The present value of the EVA. Net present value (NPV): Cumulative cash flows incurred over the life of a project, including investment, operational and terminal phases. Net worth: Total assets minus total liabilities. Off-sites: Facilities outside the main processing plant (battery limits), such as storage of raw materials and products, utilities, and service facilities (offices, workshops, laboratories, cafeteria, and others). Operating cost: The sum of the cost (expenses) for the processing of a product plus general, administrative, and selling expenses. Operating profit (margin): The gross profit (margin) minus the general, administrative, and selling expenses. Payback time: The time required to recover investment costs in a project. More frequently, the time from the start of production to recover fixed capital costs. Present worth: The value at a given time of expenditures, costs, profits, etc. according to a predetermined method of computation. Processing cost (expenses): The sum of the direct and indirect processing costs. It includes the raw materials, utilities, labor, maintenance, depreciation, local taxes, etc. Production rate: The amount of product manufactured in a given time period. Productivity: Tons of product / ton of raw material; tons of product / MWh; tons of product / year.person; tons of product / year.dollar of fixed capital. Profit, gross: The total revenue minus the cost of products sold. Profitability: Economic feasibility of a proposed project or an ongoing operation. Revenues: The net income from the sale of a product to a customer. Return in investment (ROI): The interest rate at which the nondiscounted net present value equals zero. Royalty: Payment to a technology licensor as an initial lump or a periodic payment, based on sales. Royalty may include know-how for new plants and products and subsequent improvements of technology which can be incorporated into plant operations. SARE (Sales, administration, research, and engineering expenses): Overhead expenses for maintaining administration offices, sales offices, and the expense of © 2008 by Taylor & Francis Group, LLC

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maintaining research and engineering departments. It is expressed as a percentage of annual net sales. Simple payback period (SPB): The time at which the nondiscounted net present value equals zero. Selling expenses: Salaries and commissions paid to sales personnel. Surplus: The excess of earnings over expenses which is not distributed to stockholders. Time value of money: The expected interest rate that capital would earn. Total operating investment: The fixed capital, utilities and service capital, and working capital. Value added: The difference between the raw material cost and the selling price of a product. Variable operating cost: Cost expressed in ($ / unit time) which varies with production rate, such as raw materials and utilities costs. Working capital: The current assets minus the current liabilities. The total amount of money invested in raw materials, supplies, products in process or in inventory, accounts receivable, and cash minus the corresponding liabilities due within 1 year.

References Brennan D, 1998. Process Industry Economics. IChemE. Couper JR, 2003. Process Engineering Economics. Marcel Dekker.

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II. NOTATION AND CONVERSION TO SI UNITS

From acre Angstrom atm (760 Torr) bar barrel (bbl), fermented liquor barrel (bbl), oil box (oranges ) Btu Btu/cwt (long) Btu/h ft oF Btu/h ft2 Btu/h ft2oF Btu/h Btu/lb bushel cP cuft cuft/lb cuft/min (CFM) d (day) dyne erg ft lb ft of water ft ft/min (FPM) gallons (Imperial) gallons (US) gallons/min (GPM) grain h (hour) hectare HP (boiler) HP hundredweight (cwt), short hundredweight (cwt), long in (inches) in Hg inch of Hg inch of water kcal kg force (kp) kWh L (lit, lt, l) © 2008 by Taylor & Francis Group, LLC

To (SI) Units m3 m bar Pa m3 m3 kg kJ kJ/kg W/m K W/m2 W/m2 W kJ/kg m3 Pa s m3 m3/kg m3/s h N J J Pa m m/s m3 m3 m3/s kg s m2 kW kW kg kg m Pa Pa Pa kJ N MJ m3

Multiply by 4.046x103 10-10 1.013 1x105 0.117 0.159 41.0 1.055 0.02 1.729 3.154 5.678 0.293 2.326 0.035 0.001 0.0284 0.0624 0.5x10–3 24 1 x 10-5 1 x 10-7 1.355 2990 0.305 0.0051 4.543x10–3 3.785x10–3 0.063x10–3 6.48 x 10-5 3 600 10x103 9.80 0.745 45.4 50.8 0.0254 3386 3.38 kPa 0.25 kPa 4.18 9.81 3.6 0.001

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lb force lb mass lb/cuft lb/ft s lb/ft2 lb/inch2 (psi) miles mm water MWh ounce (oz) P (poise) pint (1/2 quart) quart RPM (rpm) sq ft (ft2) sq in (inch2) therm (100 kBtu) t (ton), metric ton (US), short ton-refrigeration Torr (mm Hg) y (year) y (year) yard K = oC + 273.15 o C = (oF – 32)/1.8

N kg kg/m3 Pa s Pa Pa km Pa GJ kg Pa s m3 m3 1/s m2 m2 MJ kg kg kW Pa d (days ) h (hours) m

$ (USD) = US Dollar Prefixes da (deca) h (hecto) k (kilo) M (mega) G (giga) d (deci) c (centi) m (milli) μ (micro) n (nano)

= 101 = 102 = 103 = 106 = 109 = 10–1 = 10–2 = 10–3 = 10–6 = 10–9

In the USA, the following prefixes are sometimes used: M (thousand) = 103 MM (million) = 106 Billion = 109

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4.45 0.454 16.02 1.488 47.9 6894 1.609 9.81 3.6 0.028 0.10 4.73 x 10-4 9.46 x 10-4 1/60 0.093 0.645x10–3 105.5 1000 907.2 3.51 133.3 365 8 760 0.914

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III. USEFUL THERMOPHYSICAL PROPERTIES OF WATER

Density of liquid water (ρ) Specific heat of liquid water (Cp) Heat of freezing of water (ΔHf) Heat of evaporation, 100oC (ΔHe) Typical enthalpy of steam (ΔHs)

1000 4.18 0.33 2.3 2.4

kg/m3 kJ/kgK MJ/kg MJ/kg MJ/kg

Data from Saravacos and Kostaropoulos (2002), Maroulis and Saravacos (2003).

IV. THERMOPHYSICAL PROPERTIES OF SOME FOOD MATERIALS (Examples of Chapters 7, 8, 9) Food material % Total Solids Apricots 15 Carrots 12 Flour, wheat 87 Bread 65 Grape juice 22oBrix 22 Green beans 11 Green peas 22 Milk 12 Milk powder 96.5 Oranges 13.6 Orange juice 12oBrix 12 Orange juice 65oBrix 65 Peaches 11 Potatoes 24 Sugar beets 23 Beet juice 15oBrix 15 Beet juice 65oBrix 65 Sugar, white 99.9 Tomatoes 7 Tomato juice 6% 6 Tomato paste 32% 32 Wine 12% (vol.)

ρ kg/m3 1000 1030 785 350 1090 900 1040 1020 610 1030 1040 1315 930 1050 1040 1050 1320 1600 1020 1020 1130 970

Data from Saravacos and Kostaropoulos (2002), Maroulis and Saravacos (2003).

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Cp kJ/kg K 3.6 3.8 1.8 2.0 3.5 3.8 3.5 3.8 1.3 3.8 3.8 2.5 3.8 3.5 3.5 3.4 2.5 1.26 3.9 3.9 3.3 3.8

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V. RHEOLOGICAL PROPERTIES Fluid (20oC) Water Tomato juice 6oBrix Orange juice 12oBrix Sugar solution 15oBrix Sugar solution 65oBrix Orange juice 65oBrix Tomato paste 32oBrix

n 1.00 1.00 1.00 1.00 1.00 0.76 0.30

K 0.001 0.002 0.002 0.003 0.045 0.400 120.0

Generalized rheological equation: ηa = K γn-1 ηa = apparent viscosity, Pa s; γ = shear rate, 1/s; n = flow behavior index, -; K = flow consistency coefficient, Pa sn; Ea = activation energy, kJ/mol

VI. OVERALL HEAT TRANSFER COEFFICIENTS (U) Heating / Cooling Air heating – cooling Water heating – cooling Steam heating Viscous liquid foods Evaporation of liquid foods Data from Saravacos and Maroulis, 2001.

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U, kW/m2K 0.05 – 0.10 0.5 – 2.5 1.0 – 3.0 0.2 – 1.0 0.5 – 2.0

Ea 15 16 16 18 40 40 15

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VII. ACCOMPANYING CD The book accompanying CD contains the following Excel files: 1. 2. 3.

EquipmentCost.xls UtilitiesModel.xls PlantEconomics.xls

The EquipmentCost.xls file calculates the cost of equipment versus its size. Using appropriate pull down menus a specific equipment or a group of equipment can be selected. Figures 5.3 of Chapter 5 can be reproduced or modified. The UtilitiesModel.xls file implements the proposed model of Chapter 6. The utilities cost is calculated versus the crude oil price. Crucial Figure 6.14 can be updated according to current crude oil price. The PlantEconomics.xls produces the results of Chapters 7 and 8. All the applications of this book can be updated and modified according the user specifications.

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