Six Sigma and Beyond: Design for Six Sigma

SIX SIGMA AND BEYOND Design for Six Sigma

SIX SIGMA AND BEYOND A series by D.H. Stamatis Volume I

Foundations of Excellent Performance

Volume II

Problem Solving and Basic Mathematics

Volume III

Statistics and Probability

Volume IV

Statistical Process Control

Volume V

Design of Experiments

Volume VI

Design for Six Sigma

Volume VII

The Implementation Process

D. H. Stamatis

SIX SIGMA AND BEYOND Design for Six Sigma

ST. LUCIE PRES S A CRC Press Company Boca Raton London New York Washington, D.C.

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Library of Congress Cataloging-in-Publication Data Stamatis, D. H., 1947Six sigma and beyond : design for six sigma, volume VI p. cm. -- (Six sigma and beyond series) Includes bibliographical references. ISBN 1-57444-315-1 (v. 1 : alk paper) 1. Quality control--Statistical methods. 2. Production management--Statistical methods. 3. Industrial management. I. Title. II. Series. TS156 .S73 2001 658.5′62--dc21

2001041635

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 consequences of their use. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage or retrieval system, without prior permission in writing from the publisher. The consent of CRC Press LLC does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from CRC Press LLC for such copying. Direct all inquiries to CRC Press LLC, 2000 N.W. Corporate Blvd., Boca Raton, Florida 33431. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe.

Visit the CRC Press Web site at www.crcpress.com © 2003 by CRC Press LLC St. Lucie Press is an imprint of CRC Press LLC No claim to original U.S. Government works International Standard Book Number 1-57444-315-1 Library of Congress Card Number 2001041635 Printed in the United States of America 1 2 3 4 5 6 7 8 9 0 Printed on acid-free paper

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To Christine

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Preface A collage of historical facts brings us to the realization that concerns about quality are present not only in the minds of top management when things go wrong but also in the minds of customers when they buy something and it does not work. We begin the collage 20 years ago, with Wayne’s (1982) proclamation in the New York Times of “management gospel gone wrong.” Wayne quoted two Harvard professors, Hays and Abernathy, as saying, “You may have your eye on the wrong ball.” In a discussion of the cost differential between American and Japanese companies, Wayne said that American business executives argue that the Japanese advantage is largely rooted in factors unique to Japan: lower labor costs, more automated and newer factories, strong government support, and a homogeneous culture. The professors, though, argue differently, Wayne said. They claim that Japanese businesses are better because they pay attention to such basics as a clean workplace, preventive maintenance for machinery, a desire to make their production process error free, and an attitude that “thinks quality.” Other authors writing in the early 1980s made similar points. Blotnick (1982) wrote, “If it’s American, it must be bad.” The headline of an anonymous article in The Sentinel Star (1982) referred to “retailers relearning lesson of customer’s always right.” Ohmae (1982) wrote an article titled “Quality control circles: They work and don’t work.” Imai (1982) wrote that unless organizations control (eliminate) their waste, they would have problems. He identified waste as: 1. 2. 3. 4. 5. 6. 7.

The The The The The The The

waste waste waste waste waste waste waste

of of of of of of of

making too many units waiting time at the machine transporting units processing itself inventory motion making defective units

Imai pointed out some of Toyota’s advantages, specifically its autonomation system. Autonomation means that the machine is equipped with human wisdom to stop automatically whenever something goes wrong with it. Wight (1982) urged management to “learn to live with the truth.” When Honda rolled out its first American-built car, Lewin (1982) wrote, “Japanese bosses ponder mysterious U.S. workers.” Among other things, the Japanese wondered why Americans have so many lawyers, Lewin pointed out. Lohr (1983) wrote that “it’s just wishful thinking to say that Japan cannot catch up software. That is what a lot of people were saying about semiconductor industry a few years ago and the auto industry a decade ago.”

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Holusha (1983) wrote of the “U.S. striving for efficiency.” Serrin (1983) described a study that showed that the work ethic is “alive but neglected.” Holloran (1983) wrote that an “army staff chief faults industry as producing defective materials.” Almost twenty years later, Zahary (2001) reported that Toyota strives to retain its benchmark status by continuing its focus on the Kaizen approach and genchi genbutso (go and see attitude). Winter (2001) wrote that GM is “now trying to show it understands importance of product.” McElroy (2001) wrote, “Customers don’t care how well your stock is performing. They do not care you are the lowest producer. They do not care you are the fastest to market. All they care about is the car they are buying. That is why it all comes down to product.” Morais (2001), quoting O’Connell (2000), claimed that over 100,000 focus groups were fielded in 1999, even though marketing and advertising professionals have mixed feelings about their value. Steel (1998 pp. 79 and 202–205) expressed industry’s ambivalence about focus groups. Among other things, he claimed that they are not very representative at all. The odd thing about focus groups is that we still use them to predict the sales potential of new products primarily because of their instant judgments, non-projectable conclusions, and comparatively low costs, even though we know better — that is, we know that we could do better by learning about consumers’ product needs and attitudes and understanding their lives. In the automotive industry, the evidence that something is wrong is abundantly clear, as Mayne et al. (2001) have reported. Here are some key points: 1. National Highway Traffic Safety Administration records showed more than 250 vehicle recalls as of mid-June 2001 — well on pace to exceed the previous year’s record 12-month total of 483. The 2000 total broke the previous high of 370 — set in 1999 — and shattered the next-highest mark of 328, set the year before. 2. Numbers of recalled vehicles have risen correspondingly — 23.4 million in 2000, 19.2 million the previous year, and 17.2 million in 1998. 3. The number of vehicles snared by non-compliance recalls — issued for failure to meet the Federal Motor Vehicle Safety Standards — increased to 4.5 million in 2000. This represents a 61% hike compared to 1999’s 2.8 million, and it is nearly three times the 1.6 million recorded in 1998. 4. A total of 18.9 million vehicles were recalled in 2000 because of safetyrelated defects. That is 81% of the overall recall total and a sharp increase compared to 1999 and 1998, when safety-related defects prompted recalls of 16.4 million and 15.6 million vehicles, respectively. Even more telling, perhaps, it is 9% more than the 17.3 million new light vehicles sold last year in the U.S. 5. A supplier executive, who wants to remain anonymous, bristles at the suggestion that quality problems fall at the feet of suppliers. He says quality has suffered because of the Big Three’s relentless pursuit of cost reduction. He also suggests that buyers at the Big Three are evaluated primarily on the basis of cost savings rather than on the quality of the parts they procure. In the final analysis, “Americans build to print and specification, whereas Japanese build to function.”

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Powerful statements indeed, yet I could go on with examples involving home appliances, food, electronics, health devices, and many other types of products. However, the point is that the problems we are having are not new. The actions necessary to fix these problems are not new. What we need is a new commitment to pursue customer satisfaction and mean it. We must put quality in the design of all our products and services in such a way that the customer sees value in them. We must become like a philologist who believes that there is truth and falsehood in a comma. The pleasures of philology are such that by merely changing the placement of a comma, you can make sense out of nonsense; you can claim a small victory over ignorance and error. So, we in quality must learn to persevere and learn as much as possible about the customer. We must make strides to identify what customers need, want, and expect and then provide them with that product or service. We must do what the French philosopher Etienne Souriau observed: pour inventer il faut penser a cote. To invent, you must think aside — that is, slightly askew. Or we must follow the lead of Emily Dickinson when she wrote, “My business is circumstances,” and her readers understood the serendipity of ideas and the rewards of looking aside to see those ideas’ unlikely, or at least less than obvious, connections. This is the essence of Design for Six Sigma (DFSS). The upfront analysis and investigation of the customer is of paramount importance. So is trying to identify what is really needed (trade-off analysis) to make the difference. The DFSS approach is based on a systems overhaul and a new mindset to cure the ailments of organizations (profitability) and provide satisfaction to the customer (functionality and value). It is a proactive approach rather than a reactive approach, unlike the regular six sigma methodology. DFSS is a methodology that works for the future, rather than the present or past. DFSS is a holistic system that is based on challenging the status quo and providing a product or a service that not only is accepted by the customer but is financially rewarding for the organization. To do this, of course, managers must take risks. They must allow their engineers to design robust designs — and that means that the traditional Y = F(x) is not good enough. Now we must look for Y = F(x,n). In these equations, x is the traditional customer characteristic (cascaded to smaller and precise characteristics), but now we add the n, which is the noise. In other words, we must design our products and services in the presence of noise for maximum satisfaction. The best way to predict the future is to invent it. This suggests that the best way to know what is coming is to put yourself in charge of creating the situation you want. Be purposeful. Look at what is needed now, and set about doing it. Action works like a powerful drug to relieve feelings of fear, helplessness, anger, uncertainty, or depression. Mobilize yourself as well as the organization because you will be the primary architect of your future. One of the keys to being successful in your efforts is to anticipate. Accept the past, focus on the future, and anticipate. Consider what is coming, what needs to happen, and how you can rise to the occasion. Stay loose. Remain flexible. Be light on your feet. Instead of changing with the times, make a habit of changing a little ahead of the times. This change can happen with Designing for Six Sigma and

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beyond. The only requirement is that we must take advantage of the future before we are ready for it. I am reminded of Flint’s (2001), Visnic’s (2001), and Mayne’s (2001) comments, respectively. American automotive companies, for example, have abandoned the car market because they do not make money on cars. They forget that the Japanese companies not only sell cars but make money from them. So what does Detroit do to sell? It focuses on price — rebates, discounts, 0% finance, lease subsidies, and so on. What does the competition do? Not only have they developed an engine/transmission with variable valve breathing, they are already using it. We are trying to perfect the five-speed, and the competition is installing six speeds; we talk about CVTs, and Audi is putting one in its new A4. We are focusing on 10 years and 150,000 miles reliability, and our competitors are pushing for 15 years and 200,000 miles reliability. In diesel technology, the Europeans and Americans are worlds apart. Even in this age of globalization, the light duty diesel markets in Europe have become more sophisticated and demanding to the point where policy makers have recognized the environmental advantages of diesel and have allowed new diesel vehicles to prove themselves as efficient, quiet, and powerful alternatives. What do we do? Our policy makers have created a regulatory structure that greatly impedes the widespread use of diesel vehicles. Consequently, Americans may be denied the performance, fuel economy, and environmental benefits of advanced diesel technology. A third example comes again from the automotive world in reference to fuel economy. One of the issues in fuel economy is the underbody design. Early on, American companies paid great attention to the design of the underbody. As time went on, the emphasis shifted to shapes that channel airflow over the bodywork, instead of what lies beneath. But while U.S. automakers were accustomed to being on top, BMW AG was redefining airflow from the ground up. Underbodies have been a priority with the Munich-based automaker since 1980. That is when BMW acquired its first wind tunnel and began development of the 1986 7-series — code named E32. Today, underbodies rank second behind rear ends, wheel housing and cooling airflow. As of right now, the initiative for BMW has gained them 2 miles per hour. When we talk about customer satisfaction we must do certain things that will help or improve the image of the organization in the perception of the customer. We are talking about prestige and reputation. Prestige and reputation differ from each other in three ways: 1. Reputation applies to individual products or services, while prestige is a characteristic of the organization as a whole. 2. Reputation can be measured on absolute scales, but prestige can only be judged in relative terms. 3. Prestige is judged relative to other organizations; reputation is not. It is prestige that we are interested from a Design for Six Sigma perspective. The reason for this is that prestige compels each organization to perform better than its competitors, thereby promoting excellence and continuously raising industry

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standards not only for the customer but also for the competitors. To achieve prestige, we must be cognizant of some basic yet inherent items, including the following: • Be ready to engage our customers in conversation every second of the day. In the digital age, this means having an interactive medium where people can tell you what they think about your brand and your product or service whenever they have an idea, a complaint, or a compliment, or when they just want to air some ideas with somebody who knows where you are going. Easy places to start are always-open discussion boards and focus groups. When you get more sophisticated, you can try regularly scheduled special events or special meetings. The best solution? Set up an Internet communication structure that lets you have a 24 × 7 open line of communication. • Make customer relations a two-way street. Today’s customers not only want to be heard, they want to respond. They want to engage you in conversation, brainstorming, and relationship building. To facilitate this, you may want to consider two-way communication into your Web site that provides means for real-time sharing of ideas, debate, and interaction. Another way to facilitate this is through moderated chat rooms or other more organized techniques. Online events and presentations allow you to show off new ideas or development to customers, then take questions in a moderated and controlled manner, across time zones and around the world. Online meetings allow you to have customers attend “by invitation only.” Keys to success: make sure your communication is honest and credible and that the “idea flow” is going both ways. In today’s world, an organization can design digital communication systems that can provide instant information. This system can be used to brainstorm, to test concepts and features, and more importantly, to consider trade-offs. • Get your customers to help design your products and services. Most organizations ignore the best product and service designers and consultants — people who know your product or service inside out and know intimately what the market needs, more often than not. They are your customers. They can tell you a lot more than just what is right and wrong with your current products. They can tell you what they really need in future products — in functional terms. • Let your customers get to know each other. Word of mouth is a concept that no one should ever underestimate in the Internet age. The power of conversation has the lightning-quick ability to create trends, fads, and brands. People talking to each other in a moderated environment and sharing unprompted, honest opinions about your brand of product or service remains the number one way for you to get new satisfied customers. • Make your customers feel special. When you get down to it, we have been talking about delighting the customer for at least 20 years, but that is where we have stopped. We have forgotten that relationships with customers should not be any different from relationships you have with

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close friends. You need to keep in touch. You need to be honest. You need to tell people they matter to you. To facilitate this “special attitude,” an organization may have special days for the customer, special product anniversaries and so on. However, in every special situation, representatives of the organization should be identifying new functionalities for new or pending products and shortcomings of the current products. • Never try to “understand” your customer. (This is not a contradiction of the above points. Rather, it emphasizes the notion of change in expectations.) Customers are fickle. They change. As a consequence, the organization must be vigilant in tracking the changes, the wants, and the expectations of customers. To make sure that customers are being satisfied and that they will continue to be loyal to your products and services, make sure you have a system that allows you to listen, listen, and then listen some more to what they have to say. • Shrink the globe. The world is shrinking. It has become commonplace to discuss the information revolution in terms of the creation of “global markets.” To “think global” is in vogue with the majority of large corporations. But global thinking presupposes that we also understand the “global customer.” Do we really understand? Or do we merely think we do? How do we treat all our customers as though they live right next door? One way, of course, is through a combination of modern communication technology and old-fashioned neighborliness. You need good, solid, two-way conversation with someone half a globe away that is as immediate, as powerful, and as intimate as a conversation with someone right in front of you. This obviously is difficult and demanding, and in the following chapters we are going to establish a flow of disciplines that perhaps can help us in formulating those “global customers” with their specific needs, wants, and expectations. • Design for customer satisfaction and loyalty. Some time ago I heard a saying that is quite appropriate here. The saying goes something like “everything is in a state of flux, including the status quo.” I happen to agree. Never in human history has so much change affected so many people in so many ways. The winds of change keep building, blowing harder than ever, hitting more people, reshaping all kinds of organizations. Incredible as it may sound, all these changes are happening even in organizations that think that they have understood the customer and the market. To their surprise, they have not. How else can we explain some of the latest statistics that tell us the following: 1. Business failures topped 400,00 in the first half of the 1990s and exceeded 500,000 by the end of the decade. That is double the number of the previous decade. The same trend is projected for the first decade of the new century.

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2. Eighty-five percent of all U.S. organizations now outsource services once performed in house. 3. More than three million layoffs have occurred in the last five years. What can be done to reverse this trend? Well, some will ride the wind based only on their size, some will not make it, and some will make it. The ones that will make it must learn to operate under different conditions — conditions that delight the customer with the service or the product that an organization is offering. The organization must learn to design services or products so that the customer will see value in them and cannot stand it until it has possession of either one. As the desire of the customer increases for the service or product, the demand for quality will increase. Designing for six sigma is not a small thing, nor should it be a lighthearted undertaking. It is a very difficult road to follow, but the results are worthwhile. The structure of this volume is straightforward and follows the pattern of the model of DFSS, which is Recognize, Define, Characterize, Optimize, and Verify (RDCOV). Specifically, with each stage of the model, we will explain some of the most important tools and methodologies. Our introduction is the stage where we address the basic and fundamental characteristics of any DFSS program. It is our version of the Recognize step. Specifically, we address: 1. 2. 3. 4.

Partnering Robust teams Systems engineering Advanced quality planning

We follow with the Define stage, where we discuss customer concerns by first explaining the notion of “function” and then continuing with three very important methodologies in the pursuit of satisfying the customer. Those methodologies are: 1. Kano model 2. Quality function deployment (QFD) 3. Conjoint analysis We move into a discussion of “Best in class” by discussing benchmarking. We continue the discussion with advanced topics relating to design, specifically: 1. 2. 3. 4. 5. 6. 7. 8.

Monte Carlo Finite element analysis Excel’s solver Failure mode and effect analysis (FMEA) Reliability and R&M DOE Parameter design Tolerance design

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We continue with relatively short discussions of manufacturing topics, specifically: 1. Design for manufacturing/assembly (DFM/DFA) 2. Mistake proofing Our discussion on miscellaneous topics is geared to enhance the overall design function and to sensitize readers to the fact that the pursuit of DFSS is a team orientation with many disciplines interwoven to produce the optimum design. Of course, we do not pretend to have exhaustively identified all methodologies and all tools, but we believe that we have identified the most critical ones. Specifically, we discuss: 1. 2. 3. 4. 5. 6. 7.

Theory of constraints Design review Trade-off analysis Cost of quality Reengineering GD&T Metrology

We follow with a chapter on innovative methodologies in pursuing DFSS such as signal process flow, axiomatic designs, and TRIZ, and then we return to classic discussions on value analysis, project management, an overview of mathematical concepts for reliability, and Taylor’s theorem and financial concepts. We conclude our discussion of Design for Six Sigma and Beyond with a formal summary in a matrix format of all the tools used, following the model of DCOV: 1. 2. 3. 4.

Define Characterize Optimize Verify

REFERENCES Anon., Retailers Relearning Lesson of Customer’s Always Right, The Sentinel Star, Jan. 17, 1982, p. 4. Blotnick, S., If It’s American, It Must Be Bad, Forbes, Feb. 1, 1982, p. 146. Flint, J., Where’s the Cars? You Can Make Money on Cars If You Really Want To, Ward’s AUTOWORLD, Sept. 2001, p .21. Halloran, R., Chief of Army Assails Industry on Arms Flaw, The New York Times, Aug. 9, 1983, p. 1. Holusha, J., Why G.M. Needs Toyota: U.S. Striving for Efficiency, The New York Times, Feb. 16, 1983, p. 1 (of business section). Imai, M., From Taylor to Ford to Toyota: Kanban System — Another Challenge from Japan, The Japan Economic Journal, Mar. 30, 1982, p. 12.

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Lewin, T., Japanese Bosses Ponder Mysterious U.S. Workers, The New York Times, Nov. 7, 1982, p. 2 (of business section). Lohr, S., Japan’s Hard Look at Software, The New York Times, Jan. 9, 1983, p. 3 (of business section). Mayne, E., Bottoms Up! Fuel Economy Pressure Underscores Underbody Debate. Ward’s AUTOWORLD, Sept. 2001, p. 58. Mayne, E. et al., Quality Crunch, Ward’s AUTOWORLD, July 2001, p. 14. McElroy, J., Rendezvous captures consumer interest, Wards AUTOWORLD, Jan. 2001, p. 12. Morais, R., The End of Focus Groups, Quirk’s Marketing Research Review, May 2001, p. 154. O’Connell, V., advertising column, Wall Street Journal, Nov. 27, 2000, p. B21. Ohmae, K., Quality Control Circles: They Work and Don’t Work, The Wall Street Journal, Mar. 29, 1982, p. 2. Serrin, W., Study Says Work Ethic Is Alive But Neglected, The New York Times, Sept. 5, 1983, p. 4. Steel, J., Truth, Lies and Advertising, Wiley, New York, 1998. Visnic, B., Super Diesel! Anyone in the Industry Will Tell You: Forget Hybrids; Diesels Are Our One Stop Cure All, Ward’s AUTOWORLD, Sept. 2001, p. 34. Wayne, L., Management Gospel Gone Wrong, The New York Times, May 30, 1982, p. 1 (of business section). Wight, O.W., Learning To Tell the Truth, Purchasing, May 13, 1982, p. 5. Winter, D., One last speed, Wards AUTOWORLD, July 2001, p. 9. Zachary, K., Toyota Strives To Retain Its Benchmark Status, Supplement to Ward’s AUTOWORLD, Aug. 6–10, 2001, p. 11.

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Acknowledgments I want to thank Dr. A. Stuart for granting me permission to use some of the material in Chapter 14. The summaries of the different distributions and reliability have added much to the volume. I am really indebted for his contribution. As with the other volumes in this series, many people have helped in many ways to make this book a reality. I am afraid that I will miss some, even though their help was invaluable. Dr. H. Hatzis, Dr. E. Panos, and Dr. E. Kelly have been indispensable in reviewing and commenting freely on previous drafts and throughout this project. I would like to thank Dr. L. Lamberson for his thoughtful comments and suggestions on reliability, G. Burke for his suggestions on R&M, and R. Kapur for his valuable comments about the flow and content of the material. I want to thank Ford Motor Company and especially Richard Rossier and David Kelley for their efforts to obtain permission for using the introductory material on “robust teams.” I want to thank Prentice Hall for granting me permission to use the material on conjoint and MANOVA analysis in Chapter 2. That material was taken from the 1998 book Multivariate Data Analysis, 5th ed., by J.F. Hair, R.E. Anderson, R.L. Tatham, and W.C. Block. I want to thank McGraw-Hill and D.R. Bothe for granting me permission to use some material on six sigma taken from the 1977 book Measuring Process Capability, by D.R. Bothe. I want to thank J. Wiley and the Buffa Foundation for granting me permission to use material on the Monte Carlo method from the 1973 book Modern Production Management, 4th ed., by E.S. Buffa. I want to thank the American Supplier Institute for granting me permission to use the L8 interaction table as well as some of their OA and linear graphs. I want to thank M.A. Anleitner, from Livonia Technical Services, for his contribution to the topic of “function” in Chapter 2, for helping me articulate some of the key points on APQP, and for serving as a sounding board on issues of value analysis. Thanks, Mike. I also want to thank J. Ondrus, from General Dynamics — Land System Division, for introducing me to Value Analysis and serving as a reviewer for earlier drafts on this topic. I want to thank T. Panson, P. Rageas, and J. Golematis, all of them certified public accountants, for their guidance and help in articulating the basics of accounting and financial concerns presented in Chapter 15. Of course, the ultimate responsibility for interpreting their guidance is solely mine. Special thanks go to the editors at CRC for putting up with me, as well as for transforming my notes and the manuscript into a user-friendly product.

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I want to thank the participants in my seminars for their comments and recommendations. They actually piloted the material in their own organizations and saw firsthand the results of some of the techniques and methodologies discussed in this particular volume. Their comments were incorporated with much appreciation. Finally, as always, this volume would not have been completed without the support of my family and especially my navigator, chief editor, and supporter — my wife, Carla.

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About the Author D. H. Stamatis, Ph.D., ASQC-Fellow, CQE, CMfgE, is president of Contemporary Consultants, in Southgate, Michigan. He received his B.S. and B.A. degrees in marketing from Wayne State University, his master’s degree from Central Michigan University, and his Ph.D. degree in instructional technology and business/statistics from Wayne State University. Dr. Stamatis is a certified quality engineer for the American Society of Quality Control, a certified manufacturing engineer for the Society of Manufacturing Engineers, and a graduate of BSI’s ISO 9000 lead assessor training program. He is a specialist in management consulting, organizational development, and quality science and has taught these subjects at Central Michigan University, the University of Michigan, and Florida Institute of Technology. With more than 30 years of experience in management, quality training, and consulting, Dr. Stamatis has served and consulted for numerous industries in the private and public sectors. His consulting extends across the United States, Southeast Asia, Japan, China, India, and Europe. Dr. Stamatis has written more than 60 articles and presented many speeches at national and international conferences on quality. He is a contributing author in several books and the sole author of 20 books. In addition, he has performed more than 100 automotive-related audits and 25 preassessment ISO 9000 audits, and has helped several companies attain certification. He is an active member of the Detroit Engineering Society, the American Society for Training and Development, the American Marketing Association, and the American Research Association, and a fellow of the American Society for Quality Control.

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List of Figures Figure 2.1 Figure 2.2 Figure 2.3 Figure 2.4 Figure 2.5 Figure 2.6 Figure 2.7 Figure 2.8 Figure 2.9 Figure 2.10 Figure 2.11 Figure 2.12 Figure 2.13 Figure 2.14 Figure 2.15 Figure 2.16 Figure 2.17 Figure 3.1 Figure 5.1 Figure 5.2 Figure 5.3 Figure 5.4 Figure 5.5 Figure 5.6 Figure 5.7 Figure 5.8 Figure 5.9 Figure 6.1 Figure 6.2 Figure 6.3 Figure 6.4 Figure 6.5 Figure 6.6 Figure 6.7 Figure 6.8 Figure 6.9 Figure 6.10 Figure 6.11

Paper pencil assembly. Function diagram for a mechanical pencil. Ten symbols for process flow charting. Process flow for complaint handling. Kano model framework. Basic quality depicted in the Kano model. Performance quality depicted in the Kano model. Excitement quality depicted in the Kano model. Excitement quality depicted over time in the Kano model. A typical House of Quality matrix. The initial “what” of the customer. The iterative process of “what” to “how.” The relationship matrix. The conversion of “how” to “how much.” The flow of information in the process of developing the final “House of Quality.” Alternative method of calculating importance. The development of QFD. The benchmarking continuum process. Trade-off relationships between program objectives (balance design). Sequential approach. Simultaneous approach. Tomorrow’s approach … if not today’s. The product development map/guide. Manufacturing system schematic. Approaches to mistake proofing. Major inspection techniques. Function of mistake-proofing devices. Types of FMEA. Payback effort. Kano model. A Pugh matrix — shaving with a razor. Scope for DFMEA — braking system. Scope for PFMEA — printed circuit board screen printing process. Typical FMEA header. Typical FMEA body. Function tree process. Example of ballpoint pen. FMEA body.

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Figure 6.12 Figure 6.13 Figure 6.14 Figure 6.15 Figure 6.16 Figure 6.17 Figure 6.18 Figure 6.19 Figure 6.20 Figure 6.21 Figure 6.22 Figure 7.1 Figure 7.2 Figure 7.3 Figure 7.4 Figure 7.5 Figure 7.6 Figure 7.7 Figure 9.1 Figure 9.2 Figure 9.3 Figure 9.4 Figure 9.5 Figure 9.6 Figure 9.7 Figure 9.8 Figure 9.9 Figure 9.10 Figure 9.11 Figure 9.12 Figure 9.13 Figure 9.14 Figure 9.15 Figure 9.16 Figure 9.17 Figure 9.18 Figure 9.19 Figure 9.20 Figure 9.21 Figure 9.22 Figure 10.1 Figure 10.2 Figure 11.1 Figure 11.2 Figure 11.3

Transferring the failure modes to the FMEA form. Transferring severity and classification to the FMEA form. Transferring causes and occurrences to the FMEA form. Transferring current controls and detection to the FMEA form. Area chart. Transferring the RPN to the FMEA form. Action plans and results analysis. Transferring action plans and action results on the FMEA form. FMEA linkages. The learning stages. Pen assembly process. Bathtub curve. A series block diagram. A parallel reliability block diagram. A complex reliability block diagram. The Weibull distribution for the example. Control factors and noise interactions. An example of a parameter design in reliability usage. An example of a partially completed fishbone diagram. An example of interaction. Example of cause-and-effect diagram. Plots of averages (higher responses are better). A linear example of a process with several factors. Contrasts shown in a graphical presentation. First round testing. Second round testing. Linear graph for L4. The orthogonal array (OA), linear graph (LG), and column interaction for L9. Three-level factors in a L8 array. Traditional approach. Nominal the best. Smaller the better Larger the better. A comparison of Cpk and loss function. Plots of averages (higher responses are better). ANOVA decomposition of multi-level factors. Factors not linear. Plots of the average standard deviation by factor level. Factor effects. Factor effects. Quality cost: The quality control system. Costs. A typical branching using signal flow graph. A simple example with signal flow graph. A hypothetical design process.

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Figure 11.4 Figure 11.5 Figure 11.6 Figure 11.7 Figure 11.8 Figure 11.9 Figure 12.1 Figure 12.2 Figure 12.3 Figure 12.4 Figure 12.5 Figure 12.6 Figure 12.7 Figure 15.1 Figure 15.2 Figure 15.3 Figure 16.1

The graph transmission. First few terms of the probability. The effect of a self loop. Node absorption. Order of design matrix showing functional coupling between FRs and DPs. Relationship of axiomatic design framework and other tools. Relationship of savings potential to time. Project identification sheet. Cost visibility sheet. Cost function worksheet. A form that may be used to direct effort. Second step in the FAST diagram block process. A partial cost function FAST diagram. Life cycle of a typical company or product. A pictorial approach of duPont’s formula. Breakeven analysis. The DFSS model.

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List of Tables Table I.1 Table 1.1 Table 1.2 Table 1.3 Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 2.5 Table 2.6 Table 4.1 Table 4.2 Table 4.3 Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 6.1 Table 6.2 Table 6.3 Table 6.4 Table 6.5 Table 6.6 Table 6.7 Table 6.8 Table 6.9 Table 7.1 Table 7.2 Table 7.3 Table 7.4 Table 7.5 Table 8.1 Table 8.2 Table 8.3

Probability of a completely conforming product. Customer/supplier expanded partnering interface meetings. A typical questionnaire. A general questionnaire. Characteristic matrix for a machining process. Benefits of improved total development process. Stimuli descriptions and respondent rankings for conjoint analysis of industrial cleanser. Average ranks and deviations for respondents 1 and 2. Estimated part-worths and factor importance for respondents 1 and 2. Predicted part-worth totals and comparison of actual and estimated preference rankings. Simulated samples of 20 performance time values for operations A and B. Simulated operation of the two-station assembly line when operation A precedes operation B. Simulated operation of the two-station assembly line when operation B precedes operation A. Customer attributes for a car door. Relative importance of weights. Customer’s evaluation of competitive products. Examples of mistakes and defects. DFMEA — severity rating. PFMEA — severity rating. DFMEA — occurrence rating. PFMEA — occurrence rating. DFMEA detection table. PFMEA detection table. Special characteristics for both design and process. Manufacturing process control matrix. Machinery guidelines for severity, occurrence, and detection. Failure rates with median ranks. Median ranks. Five percent rank table. Ninety-five percent rank table. Department of Defense reliability and maintainability — standards and data items. Activities in the first three phases of the R&M process. Cost comparison of two machines. Thermal calculation values.

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Table 8.4 Table 9.1 Table 9.2 Table 9.3 Table 9.4 Table 9.5 Table 9.6 Table 9.7 Table 9.8 Table 9.9 Table 9.10 Table 9.11 Table 9.12 Table 9.13 Table 9.14 Table 9.15 Table 9.16 Table 9.17 Table 9.18 Table 9.19 Table 9.20 Table 9.21 Table 9.22 Table 9.23 Table 9.24 Table 9.25 Table 9.26 Table 9.27 Table 9.28 Table 9.29 Table 9.30 Table 9.31 Table 9.32 Table 9.33 Table 9.34 Table 9.35 Table 9.36 Table 9.37 Table 9.38 Table 9.39 Table 9.40 Table 9.41 Table 9.42 Table 9.43 Table 9.44 Table 9.45

Guidelines for the Duane model. One factor at a time. Test numbers for comparison. The group runs using DOE configurations. Comparisons using DOE. Comparisons of the two means. The test matrix for the seven factors. Test results. An example of contrasts. L4 setup. The L8 interaction table. An L9 with a two-level column. Combination method. Modified L8 array. An L8 with an L4 outer array. Recommended factor assignment by column. Formulas for calculating S/N. Concerns with NTB S/N ratio. L8 with test results. ANOVA table. Higher order relationships. Inner OA (L8) with outer OA (L4) and test results. The STB ANOVA table. The LTB ANOVA table. The NTB ANOVA table. Raw data ANOVA table. Combination design. L9 OA with test results. ANOVA table. Second run of ANOVA. L8 with test results and S/N values. ANOVA table for data from Table 9.30. Significant figures from Table 9.31. Observed versus cumulative frequency. Attribute test setup and results. ANOVA table (for cumulative frequency). The effect of the significant factors. Rate of occurrence at the optimum settings. Door closing effort: test set up and results. ANOVA table for door closing effort. The effects of the door closing effort. Rate of occurrence at the optimum settings. OA and test setup and results. ANOVA for the raw data. ANOVA table for the NTB S/N ratios. Typical ANOVA table setup.

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Table 9.46 Table 9.47 Table 9.48 Table 9.49 Table 9.50 Table 9.51 Table 9.52 Table 9.53 Table 9.54 Table 9.55 Table 9.56 Table 9.57 Table 9.58 Table 9.59 Table 9.60 Table 9.61 Table 9.62 Table 9.63 Table 9.64

L4 OA with test results. ANOVA table raw data. ANOVA table (S/N ratio used as raw data). Level averages — raw data. OA setup and test results for Example 2. ANOVA table (S/N ratio used as raw data). Transformed data. ANOVA table for the transformed data. Components and their levels. L8 inner OA with L8 outer OA and test results. ANOVA table (NTB) and level averages for the most significant factors. Variation runs using recommended factor target values. Calculated response variance. Cost of reducing tolerances. The impact of tightening the tolerance. Reduction of 20% in the tolerance limits of component A. Reduction of tolerance limits for component D. Reduction of tolerance limits for component C. L8 OA used for the confirmation runs with the levels set, test setup, ANOVA table and level averages. Table 9.65 Response variance. Table 10.1 Design review objectives. Table 10.2 Design review checklist. Table 10.3 Comparison between traditional and concurrent engineering. Table 10.4 Typical monthly quality cost report (values in thousands of dollars). Table 10.5 Prevention costs. Table 10.6 Appraisal costs. Table 10.7 Internal failure costs. Table 10.8 External failure costs. Table 10.9 Seven-step process redesign model. Table 10.10 GD&T characteristics and symbols. Table 12.1 Project identification checklist. Table 12.2 Idea needlers or thought stimulators. Table 12.3 The worksheet for setting the list. Table 12.4 Evolution summary. Table 12.5 Ranking and weighting. Table 12.6 Criteria affecting car purchase XXXX — pair comparison. Table 12.7 Criteria weighing. Table 12.8 Criteria comparison. Table 12.9 Criteria weight comparison — completed matrix. Table 13.1 Key integrative processes. Table 13.2 The characteristics of the DFSS implementation model using project management. Table 13.3 The process of six sigma and DFSS implementation using project management. Table 14.1 Possibilities of selecting a DFSS problem.

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Table 15.1 Table 15.2 Table 15.3

A summary of debits and credits. Summary of normal debit/credit balances. The Z score.

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Contents Introduction Understanding the Six Sigma Philosophy.......................................1 A Static versus a Dynamic Process ..........................................................................1 Products with Multiple Characteristics .....................................................................2 Short- and Long-Term Six Sigma Capability ...........................................................4 Design for Six Sigma and the Six Sigma Philosophy..............................................5 Design Phase.........................................................................................................5 Internal Manufacturing .........................................................................................5 External Manufacturing ........................................................................................6 References..................................................................................................................7 Chapter 1 Prerequisites to Design for Six Sigma (DFSS) ...................................9 Partnering ...................................................................................................................9 The Principles of Partnering...............................................................................11 View of Buyer/Supplier Relationship: A Paradigm Shift ..................................11 Characteristics of Expanded Partnering .............................................................12 Evaluating Suppliers and Selecting Supplier Partners.......................................14 Implementing Partnering ....................................................................................14 1. Establish Top Management Enrollment (Role of Top Management — Leadership)....................................................14 2. Establish Internal Organization.................................................................14 Option 1: Supplier Partnering Manager....................................................14 Option 2: Supplier Council/Team .............................................................15 Option 3: Commodity Management Organization ...................................15 3. Establish Supplier Involvement ................................................................15 4. Establish Responsibility for Implementation ...........................................15 5. Reevaluate the Partnering Process............................................................17 Ratings.......................................................................................................17 Terms Used in Specific Questions ............................................................19 Major Issues with Supplier Partnering Relationships........................................19 How Can We Improve?.......................................................................................20 Basic Partnering Checklist..................................................................................21 1. Leadership .................................................................................................21 2. Information and Analysis..........................................................................22 3. Strategic Quality Planning ........................................................................22 4. Human Resource Development and Management ...................................22 5. Management of Process Quality...............................................................23 6. Quality and Operational Results...............................................................23 7. Customer Focus and Satisfaction .............................................................23 Expanded Partnering Checklist ..........................................................................23 1. Leadership .................................................................................................23 2. Information and Analysis..........................................................................24

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3. Strategic Quality Planning ........................................................................24 4. Human Resource Development and Management ...................................24 5. Management of Process Quality...............................................................25 6. Quality and Operational Results...............................................................25 7. Customer Focus and Satisfaction .............................................................25 The Robust Team: A Quality Engineering Approach .............................................25 Team Systems .....................................................................................................26 Input ...............................................................................................................27 Signal..............................................................................................................27 The System.....................................................................................................27 Output/Response ............................................................................................28 The Environment............................................................................................28 External Variation...........................................................................................28 Internal Variation............................................................................................29 The Boundary.................................................................................................29 Controlling a Team Process: Conformance in Teams........................................29 Strategies for Dealing with Variation .................................................................30 Controlling or Eliminating Variation .............................................................30 Compensating for Variation ...........................................................................30 System Feedback............................................................................................31 Minimizing the Effect of Variation................................................................31 Monitoring Team Performance...........................................................................33 System Interrelationships...............................................................................33 Systems Engineering ...............................................................................................34 “Systems“ Defined ..............................................................................................34 Implications of the Systems Concept for the Manager .....................................35 Defining Systems Engineering ...........................................................................37 Pre-Feasibility Analysis ......................................................................................38 Requirement Analysis .........................................................................................38 Design Synthesis.................................................................................................38 Verification ..........................................................................................................39 Advanced Quality Planning.....................................................................................40 When Do We Use AQP?.....................................................................................42 What Is the Difference between AQP and APQP? ............................................43 How Do We Make AQP Work?..........................................................................43 Are There Pitfalls in Planning? ..........................................................................43 Do We Really Need Another Qualitative Tool to Gauge Quality?....................44 How Do We Use the Qualitative Methodology in an AQP Setting?.................44 APQP Initiative and Relationship to DFSS .......................................................45 References................................................................................................................47 Selected Bibliography..............................................................................................47 Chapter 2 Customer Understanding....................................................................49 The Concept of Function.........................................................................................52 Understanding Customer Wants and Needs .......................................................54

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Creating a Function Diagram .............................................................................55 The Product Flow Diagram and the Concept of Functives ...............................56 The Process Flow Diagram ................................................................................61 Using Function Concepts with Productivity and Quality Methodologies.........64 Kano Model .............................................................................................................68 Basic Quality.......................................................................................................69 Performance Quality ...........................................................................................69 Excitement Quality .............................................................................................69 Quality Function Deployment (QFD) .....................................................................71 Terms Associated with QFD...............................................................................73 Benefits of QFD..................................................................................................73 Issues with Traditional QFD...............................................................................75 Process Overview................................................................................................76 Developing a “QFD” Project Plan .....................................................................76 The Customer Axis ........................................................................................77 Technical Axis................................................................................................79 Internal Standards and Tests ..........................................................................79 The QFD Approach ............................................................................................79 QFD Methodology..............................................................................................80 QFD and Planning ..............................................................................................84 Product Development Process ............................................................................86 Conjoint Analysis ....................................................................................................88 What Is Conjoint Analysis?................................................................................88 A Hypothetical Example of Conjoint Analysis..................................................89 An Empirical Example .......................................................................................90 The Managerial Uses of Conjoint Analysis .......................................................95 References................................................................................................................95 Selected Bibliography..............................................................................................95 Chapter 3 Benchmarking ....................................................................................97 General Introduction to Benchmarking...................................................................97 A Brief History of Benchmarking......................................................................97 Potential Areas of Application of Benchmarking ..............................................97 Benchmarking and Business Strategy Development ..............................................99 Least Cost and Differentiation............................................................................99 Characteristics of a Least Cost Strategy ..........................................................100 Characteristics of a Differentiated Strategy .....................................................101 Benchmarking and Strategic Quality Management ..............................................102 Benchmarking and Six Sigma ..........................................................................105 National Quality Award Winners and Benchmarking......................................107 Example — Cadillac ....................................................................................107 A Second Example — Xerox ......................................................................108 Third Example — IBM Rochester...............................................................109 Fourth Example — Motorola.......................................................................110 Benchmarking and the Deming Management Method ....................................110

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Benchmarking and the Shewhart Cycle or Deming Wheel.............................111 Plan...............................................................................................................111 Do .................................................................................................................111 Study — Observe the Effects ......................................................................111 Act ................................................................................................................111 Why Do People Buy? .......................................................................................111 Alternative Definitions of Quality ....................................................................112 Determining the Customer’s Perception of Quality.........................................117 Quality, Pricing and Return on Investment (ROI) — The PIMS Results .......119 Benchmarking as a Management Tool..................................................................119 What Benchmarking Is and Is Not...................................................................120 The Benchmarking Process ..............................................................................121 Types of Benchmarking....................................................................................122 Organization for Benchmarking .......................................................................123 Requirements for Success.................................................................................124 Benchmarking and Change Management .............................................................126 Structural Pressure ............................................................................................128 Aspiration for Excellence .................................................................................128 Force Field Analysis .........................................................................................128 Identification of Benchmarking Alternatives ........................................................129 Externally Identified Benchmarking Candidates..............................................129 Industry Analysis and Critical Success Factors ..........................................129 PIMS Par Report ..........................................................................................130 Financial Comparison ..................................................................................130 Competitive Evaluations ..............................................................................131 Focus Groups ...............................................................................................131 Importance/Performance Analysis ...............................................................131 Internally Identified Benchmarking Candidates — Internal Assessment Surveys..........................................................................................132 Nominal Group Process: General Areas in Greatest Need of Improvement............................................................................................132 Pareto Analysis.............................................................................................132 Statistical Process Control ...........................................................................133 Trend Charting .............................................................................................133 Product and Company Life Cycle Position.................................................133 Failure Mode and Effect Analysis ...............................................................134 Cost/Time Analysis ......................................................................................134 Need to Identify Underlying Causes ................................................................134 Problem, Causes, Solutions .........................................................................134 The Five Whys .............................................................................................134 Cause and Effect Diagram ...........................................................................134 Business Assessment — Strengths and Weaknesses.............................................135 Prioritization of Benchmarking Alternatives — Prioritization Process................139 Prioritization Matrix .........................................................................................139 Quality Function Deployment (House of Quality) ..........................................140 Importance/Feasibility Matrix ..........................................................................141

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Paired Comparisons .....................................................................................141 Improvement Potential .................................................................................141 Prioritization Factors....................................................................................141 Are There Any Other Problems? What Is the Relative Importance of Each of These? .............................................................................................142 Identification of Benchmarking Sources...............................................................142 Types of Benchmark Sources ...........................................................................142 Internal Best Performers ..............................................................................143 Competitive Best Performers .......................................................................143 Best of Class ................................................................................................143 Selection Criteria ..............................................................................................144 Sources of Competitive Information ................................................................144 Gaining the Cooperation of the Benchmark Partner........................................148 Making the Contact ..........................................................................................149 Benchmarking — Performance and Process Analysis..........................................149 Preparation of the Benchmarking Proposal......................................................149 Activity before the Visit....................................................................................149 Understanding Your Own Operations..........................................................149 Activity Analysis..........................................................................................150 1. Define the Activity .............................................................................150 2. Determine the Triggering Event ........................................................150 3. Define the Activity .............................................................................150 4. Determine the Resource Requirements .............................................151 5. Determine the Activity Drivers ..........................................................151 6. Determine the Output of the Activity ................................................151 7. Determine the Activity Performance Measure ..................................151 Model the Activity .......................................................................................152 Examples of Modeling.................................................................................152 Flow Chart the Process ................................................................................153 Activities during the Visit.................................................................................155 Understand the Benchmark Partner’s Activities..........................................155 Identification of All of the Factors Required for Success ..........................155 Activities after the Visit ....................................................................................156 1. Functional Analysis.................................................................................156 2. Cost Analysis...........................................................................................156 3. Technology Forecasting ..........................................................................156 4. Financial Benchmarking .........................................................................157 5. Sales Promotion and Advertising ...........................................................157 6. Warehouse Operations ............................................................................157 7. PIMS Analysis.........................................................................................157 8. Purchasing Performance Benchmarks ....................................................157 Motorola Example........................................................................................158 Gap Analysis..........................................................................................................158 Definition of Gap Analysis ...............................................................................158 Current versus Future Gap ...............................................................................158

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Goal Setting ...........................................................................................................159 Goal Definition .................................................................................................159 Goal Characteristics ..........................................................................................159 Result versus Effort Goals................................................................................159 Goal Setting Philosophy ...................................................................................159 Best of the Best versus Optimization ..........................................................159 Kaizen versus Breakthrough Strategies .......................................................160 Guiding Principle Implications.........................................................................160 Goal Structure ...................................................................................................160 Cascading Goal Structure ............................................................................160 Interdepartmental Goals...............................................................................161 Action Plan Identification and Implementation ....................................................161 A Creative Planning Process ............................................................................162 Action Plan Prioritization .................................................................................162 Action Plan Documentation..............................................................................162 Monitoring and Control ....................................................................................162 Financial Analysis of Benchmarking Alternatives................................................163 Managing Benchmarking for Performance...........................................................164 References..............................................................................................................166 Selected Bibliography............................................................................................167 Chapter 4 Simulation ........................................................................................169 What Is Simulation? ..............................................................................................169 Simulated Sampling...............................................................................................170 Finite Element Analysis (FEA) .............................................................................175 Types of Finite Elements ..................................................................................175 Types of Analyses .............................................................................................176 Procedures Involved in FEA.............................................................................178 Steps in Analysis Procedure .............................................................................178 Overview of Finite Element Analysis — Solution Procedure .........................179 Input to the Finite Element Model ...................................................................180 Outputs from the Finite Element Analysis.......................................................180 Analysis of Redesigns of Refined Model ........................................................181 Summary — Finite Element Technique: A Design Tool .................................182 Excel’s Solver ........................................................................................................182 Design Optimization..............................................................................................182 How To Do Design Optimization.....................................................................184 Understanding the Optimization Algorithm .....................................................184 Conversion to an Unconstrained Problem........................................................185 Simulation and DFSS ............................................................................................185 References..............................................................................................................186 Selected Bibliography............................................................................................186 Chapter 5 Design for Manufacturability/Assembly (DFM/DFA or DFMA) ..........................................................................................187

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Business Expectations and the Impact from a Successful DFM/DFA.................189 The Essential Elements for Successful DFM/DFA ..............................................192 The Product Plan ..............................................................................................194 Product Design.............................................................................................194 Criteria for Decision between Crash Program and Perfect Product...........195 Case #1 — Crash Program .....................................................................195 Case #2 — Perfect Product Design ........................................................196 The Product Plan — Product Design Itself.................................................196 Define Product Performance Requirement ..................................................198 Available Tools and Methods for DFMA .............................................................198 Cookbooks for DFM/DFA................................................................................199 Use of the Human Body ..............................................................................199 Arrangement of the Work Place ..................................................................200 Design of Tools and Equipment ..................................................................200 Mitsubishi Method............................................................................................200 U-MASS Method..............................................................................................202 MIL-HDBK-727 ...............................................................................................203 Fundamental Design Guidance .............................................................................204 The Manufacturing Process...................................................................................206 Mistake Proofing....................................................................................................208 Definition ..........................................................................................................208 The Strategy ......................................................................................................208 Defects ..............................................................................................................209 Mistake Proof System Is a Technique for Avoiding Errors in the Workplace ...............................................................................................210 Types of Human Mistakes ................................................................................210 Forgetfulness ................................................................................................210 Mistakes of Misunderstanding.....................................................................210 Identification Mistakes .................................................................................210 Amateur Errors.............................................................................................211 Willful Mistakes...........................................................................................211 Inadvertent Mistakes ....................................................................................211 Slowness Mistakes .......................................................................................211 Lack of Standards Mistakes.........................................................................211 Surprise Mistakes .........................................................................................211 Intentional Mistakes .....................................................................................212 Defects and Errors ............................................................................................212 Mistake Types and Accompanying Causes ......................................................213 Signals that Alert ..............................................................................................215 Approaches to Mistake Proofing ......................................................................215 Major Inspection Techniques.......................................................................216 Mistake Proof System Devices....................................................................216 Devices Used as “Detectors of Mistakes” ..............................................217 Devices Used as “Preventers of Mistakes”.............................................217 Equation for Success ........................................................................................218 Typical Error Proofing Devices ...................................................................219

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References..............................................................................................................219 Selected Bibliography............................................................................................219 Chapter 6 Failure Mode and Effect Analysis (FMEA) ....................................223 Definition of FMEA ..............................................................................................224 Types of FMEAs....................................................................................................224 Is FMEA Needed? .................................................................................................225 Benefits of FMEA .................................................................................................226 FMEA History .......................................................................................................226 Initiation of the FMEA..........................................................................................227 Getting Started .......................................................................................................228 1. Understand Your Customers and Their Needs ............................................228 2. Know the Function ......................................................................................230 3. Understand the Concept of Priority ............................................................230 4. Develop and Evaluate Conceptual Designs/Processes Based on Customer Needs and Business Strategy......................................................230 5. Be Committed to Continual Improvement ..................................................231 6. Create an Effective FMEA Team ................................................................231 7. Define the FMEA Project and Scope ..........................................................234 The FMEA Form ...................................................................................................235 Developing the Function...................................................................................238 Organizing Product Functions ..........................................................................239 Failure Mode Analysis......................................................................................240 Understanding Failure Mode .......................................................................240 Failure Mode Questions...............................................................................240 Determining Potential Failure Modes..........................................................242 Failure Mode Effects ........................................................................................243 Effects and Severity Rating .........................................................................244 Severity Rating (Seriousness of the Effect) ................................................245 Failure Cause and Occurrence..........................................................................246 Popular Ways (Techniques) to Determine Causes ......................................247 Occurrence Rating........................................................................................249 Current Controls and Detection Ratings .....................................................249 Detection Rating ..........................................................................................250 Understanding and Calculating Risk................................................................251 Action Plans and Results.......................................................................................253 Classification and Characteristics.....................................................................254 Product Characteristics/“Root Causes” .......................................................255 Process Parameters/“Root Causes”..............................................................255 Driving the Action Plan ....................................................................................255 Linkages among Design and Process FMEAs and Control Plan.........................258 Getting the Most from FMEA...............................................................................260 System or Concept FMEA ....................................................................................262 Design Failure Mode and Effects Analysis (DFMEA).........................................262 Objective ...........................................................................................................263 Timing ...............................................................................................................263

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Requirements ....................................................................................................263 Discussion .........................................................................................................263 Forming the Appropriate Team....................................................................263 Describing the Function of the Design/Product..........................................264 Describing the Failure Mode Anticipated ...................................................264 Describing the Effect of the Failure ............................................................264 Describing the Cause of the Failure ............................................................264 Estimating the Frequency of Occurrence of Failure ...................................265 Estimating the Severity of the Failure.........................................................265 Identifying System and Design Controls ....................................................265 Estimating the Detection of the Failure ......................................................266 Calculating the Risk Priority Number .........................................................267 Recommending Corrective Action...............................................................267 Strategies for Lowering Risk: (System/Design) — High Severity or Occurrence ..........................................................................................267 Strategies for Lowering Risk: (System/Design) — High Detection Rating ......................................................................................................267 Process Failure Mode and Effects Analysis (FMEA)...........................................268 Objective ...........................................................................................................268 Timing ...............................................................................................................268 Requirements ....................................................................................................268 Discussion .........................................................................................................269 Forming the Team ........................................................................................269 Describing the Process Function .................................................................269 Manufacturing Process Functions...........................................................269 The PFMEA Function Questions............................................................270 Describing the Failure Mode Anticipated ...................................................270 Describing the Effect(s) of the Failure........................................................271 Describing the Cause(s) of the Failure........................................................272 Estimating the Frequency of Occurrence of Failure ...................................273 Estimating the Severity of the Failure.........................................................273 Identifying Manufacturing Process Controls...............................................273 Estimating the Detection of the Failure ......................................................274 Calculating the Risk Priority Number .........................................................275 Recommending Corrective Action...............................................................275 Strategies for Lowering Risk: (Manufacturing) — High Severity or Occurrence ..........................................................................................275 Strategies for Lowering Risk: (Manufacturing) — High Detection Rating ......................................................................................................276 Machinery FMEA (MFMEA) ...............................................................................277 Identify the Scope of the MFMEA ..................................................................277 Identify the Function ........................................................................................277 Failure Mode.....................................................................................................277 Potential Effects ................................................................................................278 Severity Rating..................................................................................................279 Classification .....................................................................................................279

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Potential Causes................................................................................................279 Occurrence Ratings...........................................................................................282 Surrogate MFMEAs..........................................................................................282 Current Controls...........................................................................................282 Detection Rating ..........................................................................................282 Risk Priority Number (RPN)............................................................................282 Recommended Actions .....................................................................................283 Date, Responsible Party....................................................................................283 Actions Taken/Revised RPN.............................................................................283 Revised RPN.....................................................................................................284 Summary ................................................................................................................284 Selected Bibliography............................................................................................284 Chapter 7 Reliability .........................................................................................287 Probabilistic Nature of Reliability ........................................................................287 Performing the Intended Function Satisfactorily..................................................288 Specified Time Period.......................................................................................288 Specified Conditions .........................................................................................289 Environmental Conditions Profile ....................................................................289 Reliability Numbers ..........................................................................................290 Indicators Used to Quantify Product Reliability..............................................290 Reliability and Quality ..........................................................................................291 Product Defects.................................................................................................291 Customer Satisfaction .......................................................................................292 Product Life and Failure Rate ..........................................................................293 Product Design and Development Cycle ..............................................................295 Reliability in Design.........................................................................................296 Cost of Engineering Changes and Product Life Cycle....................................297 Reliability in the Technology Deployment Process.........................................298 1. Pre-Deployment Process .........................................................................298 2. Core Engineering Process.......................................................................299 3. Quality Support .......................................................................................300 Reliability Measures — Testing ............................................................................300 What Is a Reliability Test? ...............................................................................300 When Does Reliability Testing Occur?............................................................301 Reliability Testing Objectives...........................................................................301 Sudden-Death Testing ..................................................................................302 Accelerated Testing ......................................................................................305 Accelerated Test Methods .....................................................................................305 Constant-Stress Testing.....................................................................................305 Step-Stress Testing............................................................................................306 Progressive-Stress Testing ................................................................................306 Accelerated-Test Models ..................................................................................306 Inverse Power Law Model ...........................................................................307 Arrhenius Model ..........................................................................................308

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AST/PASS..............................................................................................................310 Purpose of AST.................................................................................................310 AST Pre-Test Requirements .............................................................................311 Objective and Benefits of AST.........................................................................311 Purpose of PASS...............................................................................................311 Objective and Benefits of PASS .......................................................................312 Characteristics of a Reliability Demonstration Test .............................................312 The Operating Characteristic Curve.................................................................313 Attributes Tests .................................................................................................313 Variables Tests ..................................................................................................314 Fixed-Sample Tests ...........................................................................................314 Sequential Tests ................................................................................................314 Reliability Demonstration Test Methods...............................................................314 Small Populations — Fixed-Sample Test Using the Hypergeometric Distribution ...........................................................315 Large Population — Fixed-Sample Test Using the Binomial Distribution ......................................................................315 Large Population — Fixed-Sample Test Using the Poisson Distribution.........................................................................316 Success Testing ......................................................................................................316 Sequential Test Plan for the Binomial Distribution .........................................317 Graphical Solution ............................................................................................318 Variables Demonstration Tests ..............................................................................318 Failure-Truncated Test Plans — Fixed-Sample Test Using the Exponential Distribution ..................................................................318 Time-Truncated Test Plans — Fixed-Sample Test Using the Exponential Distribution ..................................................................319 Weibull and Normal Distributions....................................................................320 Sequential Test Plans .............................................................................................321 Exponential Distribution Sequential Test Plan.................................................321 Weibull and Normal Distributions....................................................................323 Interference (Tail) Testing ................................................................................323 Reliability Vision ..............................................................................................323 Reliability Block Diagrams ..............................................................................323 Weibull Distribution — Instructions for Plotting and Analyzing Failure Data on a Weibull Probability Chart ................................................................325 Instructions for Plotting Failure and Suspended Items Data on a Weibull Probability Chart.........................................................................331 Additional Notes on the Use of the Weibull....................................................334 Design of Experiments in Reliability Applications ..............................................335 Reliability Improvement through Parameter Design ............................................336 Department of Defense Reliability and Maintainability — Standards and Data Items.......................................................................................................337 References..............................................................................................................342 Selected Bibliography............................................................................................343

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Chapter 8 Reliability and Maintainability ........................................................345 Why Do Reliability and Maintainability?.............................................................345 Objectives...............................................................................................................346 Making Reliability and Maintainability Work ......................................................346 Who’s Responsible? ..............................................................................................347 Tools.......................................................................................................................347 Sequence and Timing ............................................................................................348 Concept ..................................................................................................................349 Bookshelf Data .................................................................................................349 Manufacturing Process Selection .....................................................................350 R&M and Preventive Maintenance (PM) Needs Analysis ..............................350 Development and Design.......................................................................................350 R&M Planning..................................................................................................350 Process Design for R&M .................................................................................351 Machinery FMEA Development ......................................................................351 Design Review ..................................................................................................352 Build and Install ....................................................................................................352 Equipment Run-Off ..........................................................................................352 Operation of Machinery....................................................................................352 Operations and Support .........................................................................................353 Conversion/Decommission ....................................................................................353 Typical R&M Measures ........................................................................................353 R&M Matrix .....................................................................................................353 Reliability Point Measurement .........................................................................354 MTBE................................................................................................................354 MTBF................................................................................................................355 Failure Rate.......................................................................................................355 MTTR................................................................................................................355 Availability ........................................................................................................356 Overall Equipment Effectiveness (OEE)..........................................................356 Life Cycle Costing (LCC) ................................................................................356 Top 10 Problems and Resolutions....................................................................357 Thermal Analysis ..............................................................................................357 Electrical Design Margins ................................................................................359 Safety Margins (SM) ........................................................................................359 Interference .......................................................................................................360 Conversion of MTBF to Failure Rate and Vice Versa .....................................361 Reliability Growth Plots ...................................................................................361 Machinery FMEA .............................................................................................361 Key Definitions in R&M .......................................................................................362 DFSS and R&M ....................................................................................................364 References..............................................................................................................365 Selected Bibliography............................................................................................365

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Chapter 9 Design of Experiments.....................................................................367 Setting the Stage for DOE.....................................................................................367 Why DOE (Design of Experiments) Is a Valuable Tool..................................367 Taguchi’s Approach ..........................................................................................370 Miscellaneous Thoughts ...................................................................................371 Planning the Experiment .......................................................................................372 Brainstorming....................................................................................................372 Choice of Response ..........................................................................................373 Miscellaneous Thoughts ...................................................................................379 Setting Up the Experiment ....................................................................................380 Choice of the Number of Factor Levels...........................................................380 Linear Graphs ...................................................................................................382 Degrees of Freedom..........................................................................................383 Using Orthogonal Arrays and Linear Graphs ..................................................383 Column Interaction (Triangular) Table.............................................................384 Factors with Three Levels ................................................................................385 Interactions and Hardware Test Setup..............................................................385 Choice of the Test Array...................................................................................387 Factors with Four Levels ..................................................................................389 Factors with Eight Levels .................................................................................389 Factors with Nine Levels..................................................................................390 Using Factors with Two Levels in a Three-Level Array .................................390 Dummy Treatment .......................................................................................390 Combination Method ...................................................................................390 Using Factors with Three Levels in a Two-Level Array .................................391 Other Techniques ..............................................................................................391 Nesting of Factors ........................................................................................392 Setting Up Experiments with Factors with Large Numbers of Levels.......392 Inner Arrays and Outer Arrays .........................................................................393 Randomization of the Experimental Tests .......................................................394 Miscellaneous Thoughts ...................................................................................394 Loss Function and Signal-to-Noise.......................................................................397 Loss Function and the Traditional Approach ...................................................397 Calculation of the Loss Function .....................................................................398 Comparison of the Loss Function and Cpk .....................................................402 Signal-to-Noise (S/N) .......................................................................................403 Miscellaneous Thoughts ...................................................................................404 Analysis..................................................................................................................405 Graphical Analysis ............................................................................................405 Analysis of Variance (ANOVA) .......................................................................407 Estimation at the Optimum Level ....................................................................408 Confidence Interval around the Estimation......................................................409 Interpretation and Use ......................................................................................410 ANOVA Decomposition of Multi-Level Factors .............................................410

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S/N Calculations and Interpretations................................................................411 Smaller-the-Better (STB) .............................................................................412 Larger-the-Better (LTB) ...............................................................................413 Nominal the Best (NTB) .............................................................................413 Combination Design .........................................................................................415 Miscellaneous Thoughts ...................................................................................418 Analysis of Classified Data ...................................................................................421 Classified Responses.........................................................................................422 Classified Attribute Analysis.............................................................................422 Class 1 ..........................................................................................................425 Class 2 ..........................................................................................................426 Classified Variable Analysis..............................................................................426 Discussion of the Degrees of Freedom ............................................................428 Miscellaneous Thoughts ...................................................................................429 Dynamic Situations................................................................................................430 Definition ..........................................................................................................430 Discussion .........................................................................................................431 Conditions ....................................................................................................431 Analysis ........................................................................................................432 Miscellaneous Thoughts ...................................................................................439 For Example 1..............................................................................................440 For Example 2..............................................................................................440 Parameter Design...................................................................................................441 Discussion .........................................................................................................441 Example........................................................................................................441 Tolerance Design ...................................................................................................447 Discussion .........................................................................................................447 Example........................................................................................................448 Humidity..................................................................................................454 Testing .....................................................................................................454 DOE Checklist .......................................................................................................454 Selected Bibliography............................................................................................455 Chapter 10 Miscellaneous Topics — Methodologies .......................................457 Theory of Constraints (TOC) ................................................................................457 The Goal ...........................................................................................................457 Strategic Measures ............................................................................................458 Net Profit, Return on Investment, and Productivity.........................................459 Measurement Focus ..........................................................................................460 Throughput versus Cost World.........................................................................461 Obstacles to Moving into the Throughput World ............................................461 The Foundation Elements of TOC ...................................................................463 The Theory of Non-Constraints .......................................................................463 The Five-Step Framework of TOC...................................................................464 Selected Bibliography............................................................................................465

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Design Review .......................................................................................................465 Failure Mode and Effect Analysis (FMEA).....................................................467 References..............................................................................................................470 Selected Bibliography............................................................................................470 Trade-Off Studies...................................................................................................470 How to Conduct a Trade-Off Study: The Process ...........................................471 1. Construct the Preliminary Matrix ...........................................................471 2. Select and Assemble the Cross-Functional Team ..................................472 3. Assign Team Members’ Roles and Responsibilities ..............................472 4. Assign Ranking Teams To Evaluate the Alternatives ............................473 Identification of Ranking Methods .........................................................473 Development of Standardized Documentation .......................................474 Timing for Report out of Selection Process...........................................474 5. Weight the Various Categories................................................................474 6. Compile the Evidence Book ...................................................................475 7. Present the Results ..................................................................................475 Glossary of Terms.............................................................................................476 Selected Bibliography............................................................................................477 Cost of Quality ......................................................................................................477 Cost Monitoring System...................................................................................478 Standard Cost ...............................................................................................478 Actual Costs .................................................................................................478 Variance ........................................................................................................480 Cost Reduction Efforts.................................................................................480 Concepts of Quality Costs................................................................................480 J. Juran .........................................................................................................480 W.E. Deming ................................................................................................480 P. Crosby ......................................................................................................481 G. Taguchi ....................................................................................................481 Definition of Quality Components ...................................................................481 Methods of Measuring Quality.........................................................................483 Complaint Indices .............................................................................................484 Processing and Resolution of Customer Complaints.......................................484 Techniques for Analyzing Data ........................................................................484 Format for Presentation of Costs......................................................................485 Laws of Cost of Quality ...................................................................................485 Data Sources .....................................................................................................487 Inspection Decisions .........................................................................................487 Prevention Costs (See Table 10.5) ...................................................................487 Appraisal Costs (See Table 10.6) .....................................................................487 Internal Failure Costs (See Table 10.7)............................................................487 External Failure Costs (See Table 10.8)...........................................................487 Diagnostic Guidelines to Identify Manufacturing Process Improvement Opportunities ..............................................................................489 Diagnostic Guidelines to Identify Administrative Process Improvement Opportunities ..............................................................................490

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Steps for Quality Improvement — Using Cost of Quality ..............................492 Procedure......................................................................................................492 Examples ......................................................................................................492 Guideline Cost of Quality Elements by Discipline .........................................502 Cost of Quality and DFSS Relationship ..........................................................509 References..............................................................................................................511 Selected Bibliography............................................................................................511 Reengineering ........................................................................................................511 Process Redesign ..............................................................................................511 The Restructuring Approach.............................................................................512 The Conference Method ...................................................................................513 The OOAD Method ..........................................................................................515 Reengineering and DFSS..................................................................................516 References..............................................................................................................517 Selected Bibliography............................................................................................518 Geometric Dimensioning and Tolerancing (GD&T) ............................................518 References..............................................................................................................523 Selected Bibliography............................................................................................523 Metrology...............................................................................................................524 Understanding the Problem ..............................................................................524 Metrology’s Role in Industry and Quality .......................................................525 Measurement Techniques and Equipment........................................................527 Purpose of Inspection .......................................................................................528 How Do We Use Inspection and Why? ...........................................................529 Methods of Testing ...........................................................................................529 Interpreting Results of Inspection and Testing ................................................530 Technique for Wringing Gage Blocks..............................................................531 Length Combinations........................................................................................532 References..............................................................................................................533 Chapter 11 Innovation Techniques Used in Design for Six Sigma (DFSS)....535 Modeling Design Iteration Using Signal Flow Graphs as Introduced by Eppinger, Nukala and Whitney (1997) ............................................................535 Rules and Definitions of Signal Flow Graphs as Introduced by Howard (1971) and Truxal (1955) ..............................................................538 Basic Operations on Signal Flow Graphs ........................................................538 The Effect of a Self Loop.................................................................................538 Solution by Node Absorption ...........................................................................539 References..............................................................................................................539 Selected Bibliography............................................................................................540 Axiomatic Designs ................................................................................................541 So, What Is an Axiomatic Design? ..................................................................542 Axiomatic and Other Design Methodologies...................................................542 Applying Axiomatic Design to Cars ................................................................543 New Designs ................................................................................................544

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Diagnosis of Existing Design ......................................................................544 Extensions and Engineering Changes to Existing Designs ........................544 Efficient Project Work-Flow ........................................................................545 Effective Change Management ....................................................................545 Efficient Design Function ............................................................................545 References..............................................................................................................547 Selected Bibliography............................................................................................547 TRIZ — The Theory of Inventive Problem Solving ............................................548 References..............................................................................................................551 Selected Bibliography............................................................................................551 Chapter 12 Value Analysis/Engineering ...........................................................553 Introduction to Value Control — The Environment .............................................553 History of Value Control .......................................................................................555 Value Concept........................................................................................................556 Definition ..........................................................................................................556 Planned Approach .............................................................................................556 Function ............................................................................................................557 Value..................................................................................................................557 Develop Alternatives.........................................................................................558 Evaluation, Planning, Reporting, and Implementation ....................................559 The Job Plan .....................................................................................................559 Application.............................................................................................................560 Value Control — The Job Plan .............................................................................561 Value Control — Techniques versus Job Plan ......................................................562 Techniques.........................................................................................................562 Information Phase..................................................................................................563 Define the Problem ...........................................................................................563 Information Development ............................................................................564 Information Collection ............................................................................564 Cost Visibility..........................................................................................564 Project Scope...........................................................................................565 Function Determination ...............................................................................567 Function Analysis and Evaluation ...............................................................567 Cost Visibility ...................................................................................................568 Definitions ....................................................................................................568 Sources of Cost Information........................................................................570 Cost Visibility Techniques ...........................................................................570 Technique 1 — Determine Manufacturing Cost.....................................571 Technique 2 — Determine Cost Element ...............................................571 Technique 3 — Determine Component or Process Costs ......................571 Technique 4 — Determine Quantitative Costs .......................................572 Technique 5 — Determine Functional Area Costs.................................573 Function Determination ....................................................................................573 What Is Function?........................................................................................574

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Basic and Secondary Functions...................................................................574 Basic Functions .......................................................................................574 Secondary Functions ...............................................................................575 Function Analysis and Evaluation ....................................................................575 Technique 1 — Identify and Evaluate Function..........................................575 Technique 2 — Evaluate Principle of Operation ........................................576 Technique 3 — Evaluate Basic Function ....................................................576 Technique 4 — Theoretical Evaluation of Function ...................................576 Technique 5 — Input Output Method .........................................................577 Technique 6 — Function Analysis System Technique................................577 Cost Function Relationship..........................................................................580 Evaluate the Function ..................................................................................580 Creative Phase........................................................................................................582 Phase 1. Blast....................................................................................................584 Phase 2. Create .................................................................................................584 Phase 3. Refine .................................................................................................584 Evaluation Phase....................................................................................................585 Selection and Screening Techniques ................................................................585 Pareto Voting ................................................................................................585 Paired Comparisons .....................................................................................586 Evaluation Summary....................................................................................587 Matrix Analysis ............................................................................................587 Example...................................................................................................589 Rank and Weigh Criteria....................................................................589 Evaluate Each Alternative ..................................................................590 Analyze Results ..................................................................................591 Implementation Phase............................................................................................591 Goal for Achievement.......................................................................................592 Developing a Plan.............................................................................................592 Evaluation of the System..................................................................................593 Understanding the Principles............................................................................593 Organization ......................................................................................................594 Attitude..............................................................................................................596 Value Council....................................................................................................596 Audit Results.....................................................................................................597 Project Selection ....................................................................................................597 Concluding Comments ..........................................................................................598 References..............................................................................................................598 Selected Bibliography............................................................................................598 Chapter 13 Project Management (PM).............................................................599 What Is a Project? .................................................................................................599 The Process of Project Management.....................................................................601 Key Integrative Processes......................................................................................602 Project Management and Quality..........................................................................603

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A Generic Seven-Step Approach to Project Management....................................603 Phase 1. Define the Project ..............................................................................603 Step 1. Describe the Project ........................................................................603 Step 2. Appoint the Planning Team.............................................................604 Step 3. Define the Work...............................................................................604 Phase 2. Plan the Project ..................................................................................604 Step 4. Estimate Tasks .................................................................................604 Step 5. Calculate the Schedule and Budgets...............................................604 Phase 3. Implement the Plan ............................................................................605 Step 6. Start the Project ...............................................................................605 Phase 4. Complete the Project..........................................................................605 Step 7. Track Progress and Finish the Project ............................................605 A Generic Application of Project Management in Implementing Six Sigma and DFSS ...............................................................................................................605 The Value of Project Management in the Implementation Process ................607 Planning the Process ....................................................................................607 Goal Setting..................................................................................................608 PM and Six Sigma/DFSS .................................................................................608 Project Justification and Prioritization Techniques .....................................610 Benefit-Cost Analysis..............................................................................610 Return on Assets (ROA).....................................................................610 Return on Investment (ROI)...............................................................610 Net Present Value (NPV) Method......................................................611 Internal Rate of Return (IRR) Method ..............................................611 Payback Period Method .....................................................................612 Project Decision Analysis .......................................................................612 Why Project Management Succeeds .....................................................................613 References..............................................................................................................615 Selected Bibliography............................................................................................615 Chapter 14 Limited Mathematical Background for Design for Six Sigma (DFSS) ...........................................................................................617 Exponential Distribution and Reliability...............................................................617 Exponential Distribution...................................................................................617 Probability Density Function and Cumulative Distribution Function ........618 Probability Density Function (Decay Time)...........................................618 Cumulative Distribution Function (Rise Time) ......................................618 Reliability Problems.....................................................................................618 Constant Rate Failure .......................................................................................619 Example........................................................................................................619 Probability of Reliability ..................................................................................621 Control Charts...................................................................................................621 Continuous Time Waveform ........................................................................621 Discrete Time Samples ................................................................................621 Digital Signal Processing ........................................................................622

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Sample Space ....................................................................................................622 Assigning Probability to Sets ...........................................................................624 Gamma Distribution ..............................................................................................625 Gamma Distribution (pdf) ................................................................................625 Gamma Function...............................................................................................626 Properties of Gamma Functions ..................................................................626 Gamma Distribution and Reliability............................................................627 Example 1: Time to Total System Failure.......................................................627 Gamma Distribution and Reliability............................................................628 Reliability Relationships ..............................................................................632 Reliability Function......................................................................................632 Data Failure Distribution ..................................................................................633 Failure Rate or Density Function .....................................................................633 Hazard Rate Function .......................................................................................634 Relations between Reliability and Hazard Functions ......................................634 Poisson Process.................................................................................................635 Characteristics of Poisson Process ..............................................................636 Poisson Distribution .....................................................................................636 Example........................................................................................................639 Weibull Distribution...............................................................................................640 Three-Parameter Weibull Distribution..............................................................643 Taylor Series Expansion ........................................................................................644 Taylor Series Expansion ...................................................................................645 Partial Derivatives ........................................................................................649 Taylor Series in Two-Dimensions................................................................649 Taylor Series of Random Variable (RV) Functions.....................................650 Variance and Covariance..............................................................................650 Functions of Random Variables...................................................................651 Division of Random Variables .....................................................................651 Powers of a Random Variable .....................................................................652 Exponential of a Random Variable..............................................................652 Constant Raised to RV Power .....................................................................653 Logarithm of Random Variable ...................................................................653 Example: Horizontal Beam Deflection........................................................654 Example: Difference between Two Means..................................................655 Miscellaneous ........................................................................................................656 Closing Remarks....................................................................................................658 Selected Bibliography............................................................................................658 Chapter 15 Fundamentals of Finance and Accounting for Champions, Master Blacks, and Black Belts ............................................................................661 The Theory of the Firm.........................................................................................661 Budgets ..................................................................................................................662 Our Romance with Growth ...................................................................................663 The New Industrial State.......................................................................................663

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Behavioral Theory .................................................................................................663 Accounting Fundamentals .....................................................................................664 Accounting’s Role in Business.........................................................................664 Financial Reports ..............................................................................................664 The Balance Sheet .......................................................................................664 Current Assets and Liabilities .................................................................665 Fixed Assets.............................................................................................665 Other Slow Assets ...................................................................................666 Current Liabilities ...................................................................................666 Working Capital Format..........................................................................666 Noncurrent Assets ...................................................................................667 Noncurrent Liabilities .............................................................................667 Shareholders’ Equity ...............................................................................667 The Income Statement ............................................................................667 Gross Profit..............................................................................................668 A Gaggle of Profits .................................................................................668 Earnings per Share ..................................................................................669 The Statement of Changes ......................................................................669 Sources of Funds or Cash .......................................................................669 Use of Funds ...........................................................................................670 Changes in Working Capital Items .........................................................670 The Footnotes ..........................................................................................670 Accountants’ Report.....................................................................................671 How to Look at an Annual Report ..............................................................671 Recording Business Transactions .....................................................................672 Debits and Credits........................................................................................673 Sources and Uses of Cash.......................................................................673 How Debits and Credits Are Used .........................................................673 The Balance Sheet Equations ......................................................................673 Classification of Accounts ................................................................................674 Recording Transactions................................................................................675 The Two Books of Account.........................................................................675 The Trial Balance ....................................................................................676 The Mirror Image....................................................................................676 Accrual Basis of Accounting............................................................................676 Accrual Basis versus Cash Basis.................................................................677 Details, Details .............................................................................................677 Birth of the Balance Sheet...........................................................................678 Profits versus Cash.......................................................................................678 Things Are Measured in Money..................................................................678 Values Are Based on Historical Costs.........................................................678 Understanding Financial Statements .....................................................................679 Assets ................................................................................................................679 The Inflation Effect...........................................................................................679 Summary of Valuation Methods .......................................................................679 Historical Cost..............................................................................................679

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Liquidation Value .........................................................................................679 Investment or Intrinsic Value .......................................................................680 Psychic Value ...............................................................................................680 Current Value or Replacement Cost ............................................................680 Assets versus Expenses................................................................................680 Types of Assets .................................................................................................681 Financial Assets............................................................................................681 Physical Assets.............................................................................................681 Operating Leverage .................................................................................682 Determining the Value of Inventory .......................................................682 FIFO....................................................................................................682 LIFO ...................................................................................................682 Weighted Average...............................................................................683 Depreciation ............................................................................................683 Useful Life Concept ................................................................................683 Depreciation as an Expense ...............................................................684 Depreciation as a Valuation Reserve..................................................684 Depreciation as a Tax Strategy ..........................................................684 Depreciation as Part of Cash Flow ....................................................685 Straight Line .......................................................................................685 Sum-of-the-Years’ Digits (SYD)........................................................686 Double Declining Balance (DDB) .....................................................686 Unit of Production..............................................................................687 Replacement Cost...............................................................................687 Advantages of Accelerated Depreciation ...........................................687 Financial Statement Analysis ................................................................................688 Ratio Analysis ...................................................................................................688 Liquidity Ratios............................................................................................691 Financial Leverage .......................................................................................692 Coverage Ratios ...........................................................................................692 Earnings........................................................................................................692 Earnings Ratios ............................................................................................693 Le ROI .....................................................................................................693 ROE: Return on Equity ......................................................................694 ROA: Return on Assets ......................................................................694 ROS: Return on Sales ........................................................................694 Other Return Ratios............................................................................694 Financial Rating Systems ......................................................................................695 Bond Rating Companies...................................................................................695 Moody’s et al. ..............................................................................................695 Moody’s...................................................................................................696 Standard and Poor’s ................................................................................696 Ratings on Common Stocks .............................................................................696 The S&P Rating Method .............................................................................697 The Value Line Method ...............................................................................697 Good Ole Ben Graham ................................................................................697

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Commercial Credit Ratings ..............................................................................698 Dun & Bradstreet .........................................................................................698 Other Systems ..............................................................................................699 Company and Product Life Cycle.........................................................................699 Cash Flow .........................................................................................................700 A Final Thought about Cash Flow...................................................................701 A Handy Guide to Cost Terms.........................................................................703 Useful Concepts for Financial Decisions..............................................................704 The Modified duPont Formula .........................................................................704 Breakeven Analysis...........................................................................................705 Contribution Margin Analysis ..........................................................................706 Price–Volume Variance Analysis ......................................................................707 Inventory’s EOQ Model....................................................................................707 Return on Investment Analysis.........................................................................708 Net Present Value (NPV) .............................................................................709 Internal Rate of Return (IRR)......................................................................709 Profit Planning .......................................................................................................710 The Nature of Sales Forecasting ......................................................................710 The Plans Up Form......................................................................................710 Statistical Analysis .......................................................................................711 Compound Growth Rates........................................................................711 Regression Analysis ................................................................................711 Revenues and Costs.................................................................................711 Departmental Budgets .............................................................................711 How to Budget ........................................................................................712 Zero-Growth Budgeting ..........................................................................712 Selected Bibliography............................................................................................712 Chapter 16 Closing Thoughts about Design for Six Sigma (DFSS) ...............715 Appendix The Four Stages of Quality Function Deployment ..........................725 Stage 1: Establish Targets......................................................................................725 Stage 2: Finalize Design Timetables and Prototype Plans ...................................725 Stage 3: Establish Conditions of Production ........................................................725 Stage 4: Begin Mass Production Startup ..............................................................726 Tangible Benefits ...................................................................................................726 Intangible Benefits .................................................................................................727 Summary Value......................................................................................................727 The QFD Process...................................................................................................727 Managing the Process............................................................................................728 Selected Bibliography ..........................................................................................731 Index ......................................................................................................................737

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Introduction — Understanding the Six Sigma Philosophy Much discussion in recent years has been devoted to the concept of “six sigma” quality. The company most often associated with this philosophy is Motorola, Inc., whose definition of this principle is stated by Harry (1997, p. 3) as follows: A product is said to have six sigma quality when it exhibits no more than 3.4 npmo at the part and process step levels.

Confusion often exists about the relationship between six sigma and this definition of producing no more than 3.4 nonconformities per million opportunities. From a typical normal distribution table, one may find that the area underneath the normal curve beyond six sigma from the average is 1.248 × 10–9 or .001248 ppm, which is about 1 part per billion. Considering both tails of the process distribution, this would be a total of .002 ppm. This process has the potential capability of fitting two six sigma spreads within the tolerance, or equivalently, having 12 σ equal the tolerance. However, the 3.4 ppm value corresponds to the area under the curve at a distance of only 4.5 sigma from the process average. Why this apparent discrepancy? It is due to the difference between a static and a dynamic process. (The reader is encouraged to review Volume I of this series.)

A STATIC VERSUS A DYNAMIC PROCESS If a process is static, meaning the process average remains centered at the middle of the tolerance, then approximately .002 ppm will be produced. But under the six sigma concept, the process is considered to be dynamic, implying that over time, the process average will move both higher and lower because of many small changes in material, operators, environmental factors, tools, etc. Most small shifts in the process average will go undetected by the control chart. For an n of 4, there is only a 50 percent chance a 1.5-sigma shift in µ is detected by the next subgroup after this change. By the time this next subgroup is collected, it may have returned to its original position. Thus, this process change will never be noticed on the chart, which means that no corrective action will be implemented. However, this movement has caused the actual long-term process variation to increase somewhat because betweensubgroup variation is greater than within-subgroup variation. Note that estimates of short-term process variation are not impacted because they are determined only from within-subgroup variation. 1

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2

Six Sigma and Beyond

Based on studies analyzing the effect of these changes on process variation (Bender, 1962, 1968; Evans, 1970, 1974, 1975a and b; Gilson, 1951), the six sigma principle acknowledges the likelihood of undetected shifts in the process average of up to ±1.5 sigma. Because shifts in the average greater than 1.5 sigma are expected to be caught, and six is assumed not to change, the worst case for the production of nonconforming parts happens when the process average has shifted either the full 1.5 sigma above the middle of the tolerance or the full 1.5 sigma below it. For this worst case, there would be only 4.5 sigma (6 sigma minus 1.5 sigma) remaining between the process average and the nearest specification limit. This reduced Z value of 4.5 for the dynamic model corresponds to 3.4 ppm. When this size of shift occurs, the Z value for the other specification limit becomes 7.5, which means essentially 0 ppm are outside this limit. Because the process average can shift in only one direction at a time, the maximum number of nonconforming parts produced is 3.4 ppm. Notice that most of the time the average should be closer to the middle of the tolerance, resulting in far fewer than 3.4 ppm actually being manufactured. To achieve a goal of 3.4 ppm, the process average must be no closer than 4.5 sigma to a specification limit. Assuming the average could drift by as much as 1.5 sigma, potential capability must be at least 6.06 (4.56 plus 1.5 sigma) to compensate for shifts in the process average of up to 1.56, yet still be able to produce the desired quality level. The required 4.56 plus this added buffer of 1.5 sigma create the 6 σ requirement, and thereby generate the label “six sigma.” (Here it must be noted that the 4.5 shift is allegedly an empirical value for the electronic industry. In the automotive industry, for years the shift has been identified as only 1 sigma — a shift from a Ppk of 1.33 to a Cpk of 1.67 i.e., from 4 sigma to 5 sigma. The point is that every industry should identify its own shift and use it accordingly. It is unfortunate that the 4.5 shift has become the default value for everything. For a detailed explanation on the difference between Ppk and Cpk, the reader is encouraged to review Volumes I and IV of this series.) To counter the effect of shifts in µ, a buffer of 1.5 standard deviations can be added to other capability goals as well. If no more than 32 ppm are desired outside either specification, the goal would be to have ±4.06 fit within the tolerance, assuming no change in the process average. This target equates to a Cp of 1.33 (4.0/3). Under the static model, this potential capability goal translates into 32 ppm outside each specification when the average is centered at M. But with the inevitable 1.56 drifts in µ occurring with the dynamic process model, the average could move as close as 2.56 (4.5 sigma minus 1.5 sigma) to a specification limit before triggering any type of corrective action. This change in centering would cause as many as 6210 ppm to be produced, quite a bit more than the desired maximum of 32 ppm.

PRODUCTS WITH MULTIPLE CHARACTERISTICS Extremely low ppm levels are imperative for producing high quality products possessing many characteristics (or components). Table I.1 compares the probability of manufacturing a product with all characteristics inside their respective specifications when each is produced with ±4 sigma (Cp = 1.33) versus ±6 sigma (Cp = 2.00)

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Introduction — Understanding the Six Sigma Philosophy

3

TABLE I.1 Probability of a Completely Conforming Product With 1.56 Shift Number of Characteristics

C, = 1.33 (±46)

C,. = 2.00 (±6a)

1 2 5 10 25 50 100 150 250 500

99.3790 98.7618 96.9333 93.9607 85.5787 73.2371 53.6367 39.2820 21.0696 4.4393

99.99966 99.99932 99.9983 99.9966 99.9915 99.9830 99.9660 99.9490 99.9150 99.8301

capability. The processes producing the features are assumed to be dynamic, with up to a 1.5-sigma shift in average possible. Suppose a product has only one feature, which is produced on a process having ±4 sigma potential capability. We can then calculate that a maximum of .6210 percent of these parts will be non-conforming under the dynamic model. Conversely, at least 99.3790 percent will be conforming, as is listed in the first line of Table I.1. If this single characteristic is instead produced on a process with ±6 sigma potential capability, at most .00034 percent of the finished product will be out of specification, with at least 99.99966 percent within specification. If a product has two characteristics, the probability that both are within specification (assuming independence) is .993790 times .993790, or 98.7618 percent when each is produced on a ±4 sigma process. If they are produced on a ±6 sigma process, this probability increases to 99.99932 percent (.9999966 times .9999966). The remainder of the table is computed in a similar manner. When each characteristic is produced with ±4 sigma capability (and assuming a maximum drift of 1.5 sigma), a product with 10 characteristics will average about 939 conforming parts out of every 1000 made, with the 61 nonconforming ones having at least one characteristic out of specification. If all characteristics are manufactured with ±6 sigma capability, it would be very unlikely to see even one nonconforming part out of these 1000. For a product having 50 characteristics, 268 out of 1000 parts will have at least one nonconforming characteristic when each is produced with ±4 sigma capability. If these 50 characteristics were manufactured with ±6 sigma capability, it would still be improbable to see one nonconforming part. In fact, with ±6 sigma capability, a product must have 150 characteristics before you would expect to find even one nonconforming part out of 1000. Contrast this to the ±4 sigma capability level, where 60.7 percent of these parts would be rejected, and the rationale for adopting the six sigma philosophy becomes quite evident.

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Six Sigma and Beyond

SHORT- AND LONG-TERM SIX SIGMA CAPABILITY The six sigma approach also differentiates between short- and long-term process variation. Just as in the past, the short-term standard deviation has been estimated from within-subgroup variation, usually from R, and the long-term standard deviation incorporates both the short-term variation and any additional variation in the process introduced by the small, undetected shifts in the process average that occur over time. Although no exact relationship between these two types of variation applies to every kind of process, the six sigma philosophy ties them together with this general equation (Harry and Lawson, 1992, pp. 6–8). σ LT = cσ ST

As c is affected by shifts in the process average, it is related to the k factor, which quantifies how far the process average is from the middle of the tolerance.

c=

µ−M 1 k= (USL − LSL ) / 2 1− k

If a process has a Cp of 2.00 and is centered at the middle of the tolerance, then there is a distance of 6σST from the average to the USL. When the process average shifts up by 1.5σST, it has moved off target by 25 percent of one-half the tolerance (1.5/6.0 = .25). For this k factor of .25, c is calculated as 1.33. C = 1/(1 – .25) = 1/.75 = 1.33 The long-term standard deviation for this process would then be estimated from σST, as: ˆ LT = cσ ST = 1.33σ ST σ

The value 1.33 is quite commonly adopted as the relationship between shortand long-term process variation (Koons, 1992). This factor implies that long-term variation is approximately 33 percent greater than short-term variation. Other authors are more conservative and assume a c factor between 1.40 and 1.60, which translates to a k factor ranging from .286 to .375 (Harry and Lawson, 1992, pp. 6–12, 7–6). For a c factor of 1.50, k is .333. 1.50 = 1/(1 – k) 1 – k = 1/1.50 k = 1 – (1/1.50) = .333

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5

This assumption expects up to a 33.3 percent shift in the process average. With six sigma capability, there is 6σST from M to the specification limit, a distance that equals one-half the tolerance. A k factor of .333 represents a maximum shift in the process average of 2.0σST, a number derived by multiplying one-half the tolerance, or 6σST, by .333.

DESIGN FOR SIX SIGMA AND THE SIX SIGMA PHILOSOPHY The six sigma philosophy is becoming more and more popular in the quality field, especially with companies in the electronics industry (de Treville et al., 1995). Organizations striving to attain the quality levels required with the six sigma system usually adopt the following three recommended strategies for accomplishing this goal (Tomas (1991) offers a six-step approach). Improving an existing process to the six sigma level of quality would be very difficult, if not impossible. That is why Fan (1990) insists this type of thinking must already be incorporated into the original design of new products and the processes that will manufacture them if there is to be any chance of achieving six sigma quality. The three recommended strategies are as follows:

DESIGN PHASE 1. Design in ±6σ tolerances for all critical product and process parameters. For additional information on this topic, read Six Sigma Mechanical Design Tolerancing by Harry and Stewart (1988). 2. Develop designs robust to unexpected changes in both manufacturing and customer environments (see Harry and Lawson, 1992). 3. Minimize part count and number of processing steps. 4. Standardize parts and processes. Knowing the process capability of current manufacturing operations will greatly aid designers in accomplishing this first step. And of course, good designs will positively influence the capability of future processes. Once a new product is released for production, the designed-in quality levels must be maintained, and even improved upon, by working to reduce (or eliminate) both assignable and common causes of process variation. McFadden (1993) lists several additional key components of a six sigma quality program specifically targeted at manufacturing.

INTERNAL MANUFACTURING 1. Standardize manufacturing practices. 2. Audit the manufacturing system. Pena (1990) provides a detailed audit checklist for this purpose.

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3. Use SPC to control, identify, and eliminate causes of variation in the manufacturing process. Mader et al. (1993) have written a book entitled Process Control Methods to help with this step. The reader may also review Volume IV of this series. 4. Measure process capability and compare to goals. Koons’ (1992) and Bothe’s (1997) books on capability indices are useful here. 5. Consider the effects of random sampling variation on all six sigma estimates and apply the proper confidence bounds. The reference by Tavormina and Buckley (1992) would be helpful here. 6. Kelly and Seymour (1993), Bothe (1993), and Delott and Gupta (1990) reveal how the application of statistical techniques helped achieve six sigma quality levels for copper plating ceramic substrates. Harry (1994) provides several examples of applying design of experiments to improve quality in the electronics industry. A special warning here is appropriate. Even if the first two strategies are adopted, a company will never achieve six sigma quality unless it has the full cooperation and participation of all its suppliers.

EXTERNAL MANUFACTURING 1. 2. 3. 4. 5.

Qualify suppliers. Minimize the number of suppliers. Develop long-term partnerships with remaining suppliers. Require documented process control plans. Insist on continuous process improvement.

Craig (1993) shows how Dupont Connector Systems utilized this set of strategies to introduce new products into the data processing and telecommunications industries. Noguera (1992) discusses how the six sigma doctrine applies to chip connection technology in electronics manufacturing, while Fontenot et al. (1994) explain how these six sigma principles pertain to improving customer service. Daskalantonakis et al. (1990–1991) describe how software measurement technology can identify areas of improvement and help track progress toward attaining six sigma quality in software development. As all these authors conclude, the rewards for achieving the six sigma quality goals are shorter cycle times, shorter lead times, reduced costs, higher yields, improved product reliability, increased profitability, and most important of all, highly satisfied customers. We have reviewed the principles of six sigma here to make sure the reader understands the ramifications of poor quality and the significance of implementing the six sigma philosophy. In Volume I of this series, we discussed this philosophy in much more detail. However, it is imperative to summarize some of the inherent advantages, as follows:

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7

1. As quality improves to the six sigma level, profits will follow with a margin of about 8% higher prices. 2. The difference between a six sigma company and a non–six sigma company is that the six sigma company is three times more profitable. Most of that profitability is through elimination of variability — waste. 3. Companies with improved quality gain market share continuously at the expense of companies that do not improve. The focus of all these great results is in the manufacturing. However, most of the cost reduction is not in manufacturing. We know from many studies and the experience of management consultants that about 80% of quality problems are actually designed into the product without any conscious attempt to do so. We also know that about 70% of a product’s cost is determined by its design. Yet, most of the “hoopla” about six sigma in the last several years has been about the DMAIC model. To be sure, in the absence of anything else, the DMAIC model is great. But it still focuses on after-the-fact problems, issues, and concerns. As we keep on fixing problems, we continually generate problems to be fixed. That is why Stamatis (2000) and Tavormina and Buckley (1994) and the first volume of this series proclaimed that six sigma is not any different from any other tool already in the tool box of the practitioner. We still believe that, but with a major caveat. The benefit of the six sigma philosophy and its application is in the design phase of the product or service. It is unconscionable to think that in this day and age there are organizations that allow their people to chase their tails and give accolades to so many for fixing problems. Never mind that the problems they are fixing are repeatable problems. It is an abomination to think that the more we talk about quality, the more it seems that we regress. We believe that a certification program will do its magic when in fact nothing will lead to real improvement unless we focus on the design. This volume is dedicated to the Design for Six Sigma, and we are going to talk about some of the most essential tools for improvement in “real” terms. Specifically, we are going to focus on resource efficiency, robust designs, and production of products and services that are directly correlated with customer needs, wants, and expectations.

REFERENCES Bender, A, Bendarizing Tolerances — A Simple Practical Probability Method of Handling Tolerances for Limit-Stack-Ups. Graphic Science, Dec. 1962, pp. 17–21. Bender, A., Statistical Tolerancing as It Relates to Quality Control and the Designer, SAE Paper No. 680490, Society of Automotive Engineers, Southfield, MI, 1968. Bothe, D.R., Reducing Process Variation, International Quality Institute., Inc., Sacramento, CA, 1993. Bothe, D.R., Measuring Process Capability, McGraw-Hill. New York, 1997. Craig, R.J., Six-Sigma Quality, the Key to Customer Satisfaction, 47th ASQC Annual Quality Congress Transactions, Boston, 1993, pp. 206–212.

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Daskalantonakis, M.K., Yacobellis, R.H., and Basili, V.R., A method for assessing software measurement technology, Quality Engineering 3, 27–40, 1990–1991. Delott, C. and Gupta, P., Characterization of copperplating process for ceramic substrates, Quality Engineering, 2, 269–284, 1990. de Treville, S., Edelson, N.M., and Watson, R., Getting six sigma back to basics, Quality Digest, 15, 42–47, 1995. Evans, D.H., Statistical tolerancing formulation, Journal of Quality Technology, 2, 188–195, 1970. Evans, D.H., Statistical tolerancing: the state of the art, Part I: Background, Journal of Quality Technology, 6, 188–195, 1974. Evans, D.H., Statistical tolerancing: the state of the art, Part II: Methods for estimating moments, Journal of Quality Technology, 7, 1–12. 1975 (a). Evans, D.H., Statistical tolerancing: the state of the art, Part III: Shifts and drifts, Journal of Quality Technology, 7, 72–76, 1975 (b). Fan, John Y. (May 1990). Achieving Six Sigma in Design, 44th ASQC Annual Quality Congress Transactions, San Francisco, May 1990, pp. 851–856. Fontenot, G., Behara, R., and Gresham, A., Six sigma in customer satisfaction, Quality Progress, 27, 73–76, 1994. Gilson, J., A New Approach to Engineering Tolerances, Machinery Publishing Co., London, 1951. Harry, M., The Nature of Six Sigma Quality, Motorola Univ. Press, Schaumburg, IL, 1997. Harry, M. and Stewart, R., Six Sigma Mechanical Design Tolerancing, Motorola University Press, Schaumburg, IL, 1988. Harry, M., The Vision of Six Sigma: Case Studies and Applications, 2nd ed., Sigma Publishing Co., Phoenix, 1994. Harry, M. and Lawson, J.R., Six Sigma Producibility Analysis and Process Characterization, Addison-Wesley Publishing Co., Reading, MA, 1992. Kelly, H.W. and Seymour, L.A., Data Display. Addison-Wesley Publishing Co., Reading, MA, 1993. Koons, J., Indices of Capability: Classical and Six Sigma Tools, Addison-Wesley Publishing Co., Reading, MA, 1992. Mader, D.P., Seymour, L.A., Brauer, D.C., and Gallemore, M.L., Process Control Methods, Addison-Wesley Publishing Co., Reading, MA, 1993. McFadden, F.R., Six-sigma quality programs, Quality Progress, 26, 37–42, 1993. Noguera, J., Implementing Six Sigma for Interconnect Technology, 46th ASQC Annual Quality Congress Transactions, Nashville, TN, May 1992, pp. 538–544. Pena, E., Motorola’s secret to total quality control, Quality Progress, 23, 43–45, 1990. Stamatis, D.H., Six sigma: point/counterpoint: who needs six sigma anyway, Quality Digest, 33–38, May, 2000. Tadikamalla, P.R., The confusion over six-sigma quality, Quality Progress, 21, 83–85, 1994. Tavormina, J.J., and Buckley, S., SPC and six-sigma, Quality, 31, 47, 1992. Tomas, S., Motorola’s Six Steps to Six Sigma, 34th International Conference Proceedings, APICS, Seattle, WA, 1991. pp. 166–169.

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1

Prerequisites to Design for Six Sigma (DFSS)

So far in this series we have presented an overview of the six sigma methodology (DMAIC) and some of the tools and specific methodologies for addressing problems in manufacturing. Although this is a commendable endeavor for anyone to pursue — as mentioned in Volume I of this series — it is not an efficient way to use resources to pursue improvement. The reason for this is the same as the reason you do not apply an atomic bomb to demolish a two-story building. It can be done, but it is a very expensive way to go. As we proposed in Volume I, if an organization really means business and wants quality improvement to go beyond six sigma constraints, it must focus on the design phase of its products or services. It is the design that produces results. It is the design that allows the organization to have flexibility. It is the design that convinces the customer of the existence of quality in a product. Of course, in order for this design to be appropriate and applicable for customer use, it must be perceived by the customer as functional, not by the organization’s definition but by the customer’s personal perceived understanding and application of that product or service. Design for Six Sigma (DFSS) is an approach in which engineers interpret and design the functionality of the customer need, want, and expectation into requirements that are based on a win-win proposition between customer and organization. Why is this important? It is important because only through improved quality and perceived value will the customer be satisfied. In turn, only if the customer is satisfied will the competitive advantage of a given organization increase. There are four prerequisites to DFSS and beyond. The first is the recognition that improvement must be a collaboration between organization and supplier (partnering). The second is the recognition that true DFSS and beyond will only be achieved if in a given organization there are “real” teams and those teams are really “robust.” The third prerequisite is that improvement on such a large scale can only be achieved by recognizing that systems engineering must be in place. Its function has to be to make sure that the customer’s needs, wants, and expectations are cascaded all the way to the component level. The fourth prerequisite is the implementation of at least a rudimentary system of Advanced Quality Planning (AQP). In this chapter we will address each of these prerequisites in a cursory format. (Here we must note that these prerequisites have also been called the “recognize” phase of the six sigma methodology.) In the follow-up chapters, we will discuss specific tools that we need in the pursuit of DFSS and beyond.

PARTNERING Partnering and cooperation must be our watchwords. In any industry, better communication up and down the supply chain is mandatory. In the past — in few 9

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instances even today — U.S. companies have bought almost solely on the basis of price through competitive bidding. We need to change our attitude. Price is important, but it is not the only consideration. Partnering with both customers and suppliers is just as important. The Japanese have created a competitive edge through vertical integration. We can learn from them by establishing “virtual” vertical integration through partnering with customers and suppliers. Just as in a marriage, we need to give more than we get and believe that it will all work out better in the end. We need to give preferential treatment to local suppliers. We should take a long-term view, understanding their need for profitability and looking beyond this year’s buy. To begin our thinking in that direction we must change our current paradigm. The first paradigm shift must be in the following definitions: 1. Vendors must be viewed as suppliers. 2. Procurement must be viewed as business strategy. These are small changes indeed but they mean totally different things. For example: “supplier” implies working together in a win-win situation, while “vendor” implies a one-time benefit — usually price. “Procurement” implies price orientation based on bidding of some sort, while “business strategy” takes into account the concern(s) of the entire organization. We all know that price alone is not the sole reason we buy. If we do buy on the basis of price alone, we pay the consequences later on. So, what is partnering? Partnering is a business culture that fosters open communication and mutually beneficial relationships in a supportive environment built on trust. Partnering relationships stimulate continuous quality improvement and a reduction in the total cost of ownership. Partnering starts with: 1. An attitude and behavioral change at the top of the organization 2. Recognition of long-term mutual dependencies internal and external to the organization 3. A commitment to this change being understood and valued at all levels within the organization At the core or basic level, partnering: 1. Fosters excellence throughout the organization 2. Encourages open communication in a beneficial, supportive, and nonadversarial environment of mutual trust and respect 3. Carries this positive environment outward from the organization to its customers and suppliers At an expanded level, partnering involves:

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1. 2. 3. 4.

11

Teaming Sharing resources Melding of customer and supplier Eliminating the we/they approach to conducting business

By the same token, partnering is not: 1. A negotiation or purchasing tool to be used as leverage against the supplier 2. A business guarantee However, in all cases, partnering promotes: 1. 2. 3. 4.

Customer satisfaction Mutual profitability Improved product, service, and operational quality A desire for and a commitment to excellence through continuous improvements in communication skills, quality, delivery, administration, and service performance 5. The factors that contribute to customer satisfaction and the lowest total cost of ownership 6. A situation in which each partner enhances its own competitive position through the knowledge and resources shared by the other

THE PRINCIPLES

OF

PARTNERING

Effective partnering has its foundation in the basic principles of economics, marketing, business, humanities, and sociology. The customer develops a set of business and technical desires, needs, requirements, and expectations in a competitive global market. The supplier most closely meeting those business and technical needs will be successful. The supplier asks the customer what is wanted rather than telling the customer what is available. The customer recognizes and understands the supplier’s business and technical requirements, allowing the supplier to be a viable and successful source to the industry. All transactions are honorable and fair. The parties are not trying to take advantage of each other. Functioning interchangeably each day as customer and supplier, internally within the organization and externally with customers and suppliers, every person in a strong supply chain recognizes mutual dependencies. All transactions must be mutually beneficial, with each person encouraging open communication and operating with integrity, mutual trust, cooperation, and respect.

VIEW

OF

BUYER/SUPPLIER RELATIONSHIP: A PARADIGM SHIFT

Partnering involves an expanded view of the buyer/supplier relationship, as shown here:

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Traditional

Expanded

Lowest price Specification-driven Short-term, reacts to market Trouble avoidance Purchasing’s responsibility Tactical Little sharing of information on both sides

Total cost of ownership End customer–driven Long-term Opportunity maximization Cross-functional teams and top management involvement Strategic Both supplier and buyer share short- and long-term plans Share risk and opportunity Standardization Joint venture Share data

How can this partnership develop? There are prerequisites. Some are listed here. The prerequisites for basic partnering include: 1. 2. 3. 4. 5.

Mutual respect Honesty Trust Open and frequent communication Understanding of each other’s needs

Additional prerequisites for expanded partnering include: 6. 7. 8. 9. 10. 11. 12.

Long-term commitment Recognition of continuing improvement — objective and factual Passion to help each other succeed High priority on relationship Shared risk and opportunity Shared strategies/technology road maps Management commitment

CHARACTERISTICS

OF

EXPANDED PARTNERING

Expanded partnering promotes dedication, desire, and commitment to product and service excellence through improvements in technology, skills, quality, delivery, administration, responsiveness, and total cost of ownership. All these are imperative requirements for DFSS. In other words, expanded partnering: 1. 2. 3. 4.

Builds on basic partnering Is a long-term relationship process Provides focus on mutual strategic and tactical goals Includes customer/supplier team support to promote mutual success and profitability.

Of course, there are different levels of partnering just as there are different levels of results. For example:

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Prerequisites to Design for Six Sigma (DFSS) Results

Partnering Focus

Sale only Loyalty/trust Secured volumes Mutual improvements Mutual breakthrough

Short term Product Product and service Process or system Continual improvement

13 Stage 1 2 3 4 5

Why is partnering so important in the DFSS even though it may mean different things to different people? It is because the purposes or goal of most customers who advocate “partnerships” are to reduce the time to get a new product to market by eliminating the bid cycle and to extend the customer’s capability without adding personnel. Partnering is joining together to accomplish an objective that can best be met by two individuals or corporations rather than one. For a partnership to work well, it requires that both partners understand the objective, each partner complements the other in skills necessary to meet the objective, and each recognizes the value of the other in the relationship. A true partnership occurs when both partners make a conscious decision to enter into a unique relationship. As the partnership develops, trust and respect build to a degree that both share the joy and rewards of success and, when things do not go so well, both work hard together to resolve the issues to mutual satisfaction. In a customer/supplier partnership, the customer must define the objective (or the scope of the project) and identify the needs. The supplier must have the capability to meet the customer’s needs and become an extension of the customer’s resources. To be more specific, the customer must be able to quantify and share the desired needs in terms of the quantity of services required, the timeline or critical path desired, and targeted costs — including up-front engineering as well as unit cost and capital investment. The supplier must determine whether it can commit the resources required to meet those needs and whether it is capable of reaching the targets. A mutual commitment must be made early in the program, and it must be for the life of the program. In a more practical sense, the customer in a customer/supplier partnership must be the leader and be in a position to guide the partners to the objective — no different than a project leader or a team leader of a program that is 100 percent internal to the customer. The leader also must monitor the progress in terms of cost and time with input from the supplier. Our experience would indicate that longer projects should be broken into “phases” so that there are milestones that are mutually agreed to in advance by the partners and that mark the points at which the supplier is paid for its services. For a partnership to work well, customer/supplier communications must be open and frequent. With the availability of CAD, e-mail, Internet, Web sites, fax, and voice mail, there should be no reason not to communicate within minutes of recognition of an issue critical to the program, but there is also a need for regular meetings at predetermined intervals at either the customer’s or supplier’s location (probably with some meetings at each location to expose both partners to as many of the team players as possible).

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I am sure there is more to be said as to why partnership and DFSS work in tandem and why both strive for mutual benefits, but I hope these thoughts gave some idea of the significance that both have for each other.

EVALUATING SUPPLIERS

AND

SELECTING SUPPLIER PARTNERS

There are many schemes to evaluate suppliers, and each of them has advantages and disadvantages. We believe, however, that each organization should take the time to generate its own criteria in at least two dimensions. The first should be the supplier’s situation and the second the purchaser’s situation. Within each category, levels of satisfaction may be assessed as total dissatisfaction, partial satisfaction, or total satisfaction, or numerical values may be used. The higher the number, the more qualified the supplier is. This may be done with either a questionnaire or a matrix. In either case, this task should be performed by a team of people from various functional areas, such as purchasing, engineering, finance, quality, and legal. The important point is to evaluate key suppliers for a fit with your company’s needs.

IMPLEMENTING PARTNERING There are five steps to partnering. They are: 1. Establish Top Management Enrollment (Role of Top Management — Leadership) The senior management, in the role of an executive customer partner or executive supplier partner (champion): 1. 2. 3. 4. 5. 6. 7. 8. 9.

Serves in a long-term assignment for each expanded partnering relationship Is available to support prompt issue resolution Establishes strong counterpart relationships with key customers and suppliers Provides for and supports decision-making authority at the lowest practical levels Provides partnering progress updates for executive management review Encourages and supports prompt responsiveness to communications affecting customer/supplier relationships Maintains a rapid management approval cycle, providing an ombudsman when required Commits adequate time to the partnering process Ensures that cohesive internal, cross-functional teams are in place to support the partnering process

2. Establish Internal Organization There are several options in this phase. However, the most common are: Option 1: Supplier Partnering Manager A staff supplier partnering manager is appointed to a full-time position (for a minimum of two years). This manager will be responsible for:

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1. Working with purchasing/commodity team management 2. Instilling the partnering principles into the company culture 3. Implementing the partnering process with company management and suppliers 4. Reviewing progress during customer/supplier review sessions 5. Working the issues specific to the partnering process Option 2: Supplier Council/Team A supplier partnering council or team is established within the organizational and operational structure that “owns” the resources required to support the partnering process. The functions are the same as for the supplier partnering manager but are assigned to several individuals. Typically, the council or team is made up of purchasing, quality, product engineering, and manufacturing management with additional resources available from finance, law, training, and other departments as required. Option 3: Commodity Management Organization A line organization consisting of a commodity manager and staff is created to manage the commodity and the partnering activities described in Option 1. Support is received from the operational groups as required. 3. Establish Supplier Involvement To have an effective partnering involvement is of paramount importance. This involvement may be encouraged and helped to grow by having open communication. Communication may be conducted in a variety of forums or as scheduled periodic meetings — see Table 1.1. 4. Establish Responsibility for Implementation Identify roles and responsibilities of the partnering process manager: 1. 2. 3. 4. 5.

Serve as customer representative. Serve as supplier advocate. (Avoid conflict of interest.) Focus participants on long-term success. Accelerate and route communications (good news, bad news). Perform meeting planning (with supplier) and facilitation function.

Perhaps one of the most important functions in this step is to establish credibility with each other as well as confidentiality requirements. The process of this exchange must be truthful and full of integrity. Some characteristics of this exchange are: 1. Each party provides the other with the information needed to be successful. 2. The supplier needs to know the customer’s requirements and expectations in order to meet them on a long-term basis.

Establish/update mutual key results, goals, objectives, action plans Discuss issues Review performance Review/discuss on-time deliveries Required actions of both parties Quality indicators Quality action plan Business issues

Purchasing Technical Quality/reliability (Other team members)

Monthly Team Meeting

Major issues Performance review “Health check” Objectives Expectations Actual performance Technology trends Business trends Program direction

Purchasing Technical Quality/reliability (Other team members) Executive partnersb

Quarterly/Semiannual Management Meeting

At supplier location and tour Maintain key contacts Major performance review

Purchasing Technical Quality/reliability (Other team members) Executive partners

Annual Management Review

Team includes personnel from Purchasing, Quality, Material Control, Engineering. When needed, also can include personnel from Sales, Safety, Manufacturing, Process Area Management, Planning, Training, Legal, Risk Management, Finance, Project Management. b Optional as part of quarterly and semiannual meetings.

Introduce program Obtain mutual agreement and commitment Identify teams Introduce/suggest executive partners Present/discuss customer objectives Supplier objectives Proposed objectives Business objectives Definition of responsibilities Expectations

Customer team Supplier team Executive partners (if appointed)

Kick-off Meeting

Meetings

16

a

Meeting Topics Partner meeting Meeting purpose Objectives Issues Participant responsibilities

Participants Customer teama Supplier teama

Internal Preparation Meeting

TABLE 1.1 Customer/Supplier Expanded Partnering Interface Meetings

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To be successful in this exchange requires time. The reason for this is that building trust is a function of time. The longer you work with someone the more you get to know that person. To expedite the process of gaining trust, suppliers and customers may want to share in: 1. 2. 3. 4. 5. 6. 7. 8.

Non-disclosure agreements Quality improvement process Technology development roadmaps Specification development Should-cost/Total-cost model Forecasts/Frozen schedules Executive partners Job rotation with suppliers

Be aware of, adhere to, and respect the sensitive/confidential nature of proprietary information, both yours and your partner’s. Always remember: recognize the differences in company cultures. Find ways to do things without imposing your value system. Compromise... Find the common ground... Work out the differences... Move forward… Negotiate... COOPERATE! 5. Reevaluate the Partnering Process People cannot improve unless they know where they are. Evaluation of the partnering process is a way to benchmark the progress of the relationship and to set priorities for future improvement. Questionnaires with five-point rating criteria provide a means for this evaluation in which both customers and suppliers take an active role. A typical questionnaire may look like Table 1.2. Sometimes the questionnaires provide detailed definitions of certain words or criteria that are being used in the instrument. The following is a brief supplement to explain/define the rating categories and some of the terms used in Table 1.2: Ratings 1. Does not meet — Failing to satisfy requirements, unacceptable performance 2. Marginally meets — Performance is not fully acceptable, needs improvement 3. Meets — Fulfills basic requirements, satisfactory 4. Exceeds — Surpasses normal requirements 5. Superior — Consistently excels above and beyond expectations, “worldclass” performance

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Six Sigma and Beyond

TABLE 1.2 A Typical Questionnaire Please select one of the following ratings for each question: Ratings: (1) Does not meet (2) Marginally meets (3) Meets (4) Exceeds (5) Superior 1. Rate the relationship’s impact in focusing both parties on strategic and tactical goals to foster mutual success. Strategic Tactical

1 1

2 2

3 3

4 4

5 5

Comments: 2. Have all established communication channels within Intel, from executive sponsor down, enabled the partners to improve their effectiveness/competitiveness as a company? Technical Issues Business Issues

1 1

2 2

3 3

4 4

5 5

1 1 1

2 2 2

3 3 3

4 4 4

5 5 5

1

2

3

4

5

Comments: 3. Rate the effectiveness of the team structure. Management Team Working Team Performance Reviews (Both Parties) Follow-Up on Action Items Comments: 4. Rate the effectiveness of the Key Supplier Program team in generating high quality solutions. Time of Solutions Quality of Solutions Cost-Effective Solutions Comments:

1 1 1

2 2 2

3 3 3

4 4 4

5 5 5

1 1

2 2

3 3

4 4

5 5

4 4 4 4 4 4

5 5 5 5 5 5

5. Does the Executive Partner provide meaningful support? Customer Supplier Comments: 6. Is the Key Supplier Program process formally managed in an effective manner? Customer Resource Commitment Supplier Resource Commitment Formal Communication Tools Information Sharing Total Cost Focus Dealing with “Me Best“ Comments:

1 1 1 1 1 1

2 2 2 2 2 2

3 3. 3 3 3 3

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Terms Used in Specific Questions Question 1 Strategic Goals — Long-range objectives (i.e., next-generation technology) Tactical Goals — Operational, day-to-day problem solving, etc. Question 3 Management Team — Executive sponsors plus upper/middle managers Working Team — Commodity/product teams, task forces, user groups Performance Reviews — Grading joint MBOs, other indicators (e.g., quality, customer satisfaction survey) Question 4 Time of Solution — Meets or exceeds time requirements/expectations Quality of Solution — Meets or exceeds quality requirements/expectations Cost-Effective Solution — Improves total cost effectiveness/fosters mutual profitability Question 5 Meaningful Support — Active participation and involvement during and between business meetings Question 6 Resource Commitment — Adequate support (people, tools, space...) to allow successful results Formal Communication Tools — Meetings, reports, MBO’s technology exchange; correct topics, timely, worthwhile Information Sharing — Plans, technology, data; useful, timely, fosters profitability Total Cost Focus — Model in place and used to support decisions to apply resources Dealing with “The Best” — Process contributes to world-class performance Another general questionnaire evaluating the partnering process is shown in Table 1.3.

MAJOR ISSUES

WITH

SUPPLIER PARTNERING RELATIONSHIPS

In any relationship that one may think of, issues and concerns exist. Partnering is no different. Some of the areas that might be of general concern include the following: 1. 2. 3. 4. 5. 6.

Issues Issues Issues Issues Issues Other

or or or or or

concerns concerns concerns concerns concerns

within the customer’s company within the supplier’s company of a competitive nature of a political or legal nature of a technological nature

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TABLE 1.3 A General Questionnaire Evaluate the following categories based on a rating of 1 to 5, with 1 being low and 5 being excellent. (Yet another variation of the criteria may be 1 = Much improvement needed, 5 = Little or no improvement needed.) Executive commitment to the process Recognition of mutual dependencies Mutually defined and shared expectations/objectives Executive partners/sponsors Quick issue resolution (break down roadblocks) Understanding and sharing of risks Sharing of technical roadmaps/competitive analysis/business plans Openness, honesty, respect Formal and frequent communication/feedback process Access to data Establish clear definition of responsibility (project leadership)

Issues or concerns of specific nature may develop when any of the following situations exist: 1. Support on either side is insufficient. 2. Something has caused one party to consider abandoning the partnering relationship. 3. A “better deal” or innovation threatens the partnering relationship. 4. Unequal benefits or conflicting incentives exist. 5. There are forced requirements under the guise of a partnering relationship and fear on the part of the supplier to decline or dissent, particularly if the supplier is small. 6. Key players change or there is a change of ownership.

HOW CAN WE IMPROVE? A fundamental question that needs to be answered from a customer’s perspective is “How can we improve?” The answer is by establishing a process with strategic importance of “key” relationships. Once this process is identified then it needs recognition — the more the better. How do we do that? We can do it by: 1. 2. 3. 4.

Establishing upper management involvement Sharing information: technology exchanges Showing suppliers how to use the data Educating suppliers in tools and methodologies

We can benefit from creating a “mentoring” attitude toward our suppliers. Traditionally we say, “Do this because we need it.” Start saying (and thinking), “Do

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this because it will make you a stronger company, and that will in turn make us a stronger company.” Become a mentor in the Partnering for Total Quality assessment process with your suppliers. Clearly define expectations by: 1. Mutually developing short- and long-term objectives for each relationship 2. Increasing the concentration on areas for mutual success; reducing the concentration on terms and conditions 3. Making decisions based on total cost; increasing the involvement and awareness of suppliers in this process In the final analysis, in order for a successful partnership to flourish both partners — customer and supplier — must recognize that change is imminent, at least in the following areas: 1. 2. 3. 4. 5.

Organization itself Internal, interfunctional communication Customer orientation World-class definition Skills development

Are there indicators of a successful partnering process? We believe that there are. Typical indicators are the existence of: 1. 2. 3. 4. 5. 6. 7. 8. 9.

Formal communication processes Commitment to the suppliers’ success Stable relationships, not dependent on a few personalities Consistent and specific feedback on supplier performance Realistic expectations Employee accountability for ethical business conduct Meaningful information sharing Guidance to supplier in defining improvement efforts Non-adversarial negotiations and decisions based on total cost of ownership 10. Employees empowered to do the right thing

BASIC PARTNERING CHECKLIST The basic partnering principles below may be applied to any customer/supplier relationship, regardless of size of company and number of employees. The principles also apply to relationships within the organization. The investment is primarily an attitude and behavioral change to bring about six sigma quality and beyond. 1. Leadership Our management:

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1. Is personally committed to the principles of the partnering process 2. Has directed organization-wide commitment, adoption, and execution of the partnering principles and philosophy 3. Is committed to generating accurate forecasts to improve delivery schedule stability with our suppliers 4. Ensures that the partnering principles flourish even in stressful times 5. Seeks mutually profitable arrangements with our suppliers 6. Is involved in high-level review of the partnering process. 2. Information and Analysis Our organization: 1. Has standardized measurements and performance for products, processes, service, and administration 2. Respects the protection of intellectual property 3. Treats information gained in open exchanges with respect and confidentiality 4. Provides consistent and specific feedback on supplier performance 3. Strategic Quality Planning Our organization: 1. Avoids short-term solutions at the expense of long-term viability 2. Places more emphasis on overall needs and mutual expectations, less on legal or formal aspects of the relationship 3. Uses reasonable and realistic expectations and milestones with our customers and suppliers 4. Demonstrates a commitment to continuous improvement in all facets of our business 4. Human Resource Development and Management Our organization: 1. Promotes employee accountability for ethical business conduct through performance reviews, holding supervisors accountable for promoting such practices 2. Helps employees understand their roles as customer and supplier internal and external to the organization 3. Trains employees on business practices that are ethical, open, professional, and of high integrity 4. Provides position descriptions with a clear definition of responsibility 5. Supports decision-making authority at the lowest practical level

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5. Management of Process Quality Our organization: 1. Shares basic evaluation criteria with our customers and suppliers 2. Has methods for ensuring quality of components, processes, administration, service, and final product. 3. Checks periodically with our customers to verify that our quality meets their expectations 6. Quality and Operational Results Our organization: 1. Shares meaningful information and data with our customers and suppliers, with frequent and timely feedback on problems as well as successes 2. Provides guidance to suppliers in defining improvement efforts that address all problems 7. Customer Focus and Satisfaction Our organization: 1. Recognizes mutual dependencies with our customers and the need to work together; understands that partnering does not end with the signing of the purchase order. 2. Engages in win/win, non-adversarial negotiations and purchasing decisions based on total cost of ownership 3. Provides prompt disclosure to customers of any inability of the organization to meet current or future requirements; makes realistic commitments to customers

EXPANDED PARTNERING CHECKLIST In addition to the basic partnering principles, expanded partnering recognizes the need for mutual support based on such factors as cost, risk, criticalness, and actual performance. The investment involves an application of resources from both the customer and the supplier. Customer resource availability limits the number of expanded partnering relationships in which any organization can be simultaneously engaged. 1. Leadership Our senior management, in the role of an executive customer partner or executive supplier partner (champion):

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1. Serves in a long-term assignment for each expanded partner relationship 2. Is available to support prompt issue resolution 3. Establishes strong counterpoint relationships with our key customers and suppliers 4. Provides for and supports decision-making authority at the lowest practical levels 5. Encourages and supports prompt responsiveness to communications affecting customer/supplier relationships 6. Maintains a rapid management approval cycle, providing an ombudsman when required 7. Commits adequate time to the partnering process 8. Ensures that cohesive, internal, cross-functional teams are in place to support the partnering process 2. Information and Analysis Our organization, with our suppliers: 1. Uses positive encouragement and support to improve performance and total cost of ownership 2. Participates in joint information-sharing activities to develop value analysis models 3. Shares technical roadmaps, competitive analyses, and plans 4. Focuses on clearly defined, complete, achievable requirements, with less emphasis on contractual terms and conditions 5. Ensures that suppliers understand our long-term procurement strategy 3. Strategic Quality Planning Our organization: 1. Shares short- and long-term improvement plans and priorities with suppliers and customers 2. Works with customers and suppliers to understand their quality needs and plans for continuous improvements 4. Human Resource Development and Management Our company management: 1. Has established technical advisory boards to support supplier activities 2. Communicates regularly with customer and supplier management to understand mutual needs and possible areas for cooperation 3. Encourages employees to submit suggestions for continuous quality improvements 4. Offers the same quality training to supplier personnel as we provide to our own employees

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5. Management of Process Quality Our organization works with customers and suppliers to: 1. Share mutual joint performance measures that are written, measured, and tracked 2. Work toward standardization of quality and certification programs 3. Develop and implement valid quality assurance systems for products, processes, service, and administration 6. Quality and Operational Results Our organization works with customers and suppliers to: 1. Develop joint quality and yield improvement processes 2. Provide access to process data for tool and material development and refinement 7. Customer Focus and Satisfaction Our organization works with customers to: 1. Mutually define expectations, understand mutual requirements, and share risks 2. Ensure that partnering survives lapses in missed generation orders 3. Establish formal, frequent communications as part of the management process

THE ROBUST TEAM: A QUALITY ENGINEERING APPROACH In general, the traditional approach to evaluating the performance of groups in process has been twofold. The first has been to use a developmental model that provides a summary of the different phases or stages in the life cycle of a group. A popular example of this approach is the forming, storming, norming, performing model of group development. Each phase corresponds to a stage in the group life cycle — review Volume I, Part II of this series. The second model has emphasized structural patterns of a group or team. These may be construed in terms of gender, experience, length of service, or positional roles (leader, secretary, or assistant, for example). Using the structural approach, the team can also be analyzed in terms of process; the “peacemaker,” the “aggressor,” the “blocker,” or the “help-seeker,” for example, or Resource Investigator, Coordinator, and so on. Both these models have proven to be useful when trying to describe some aspects of group dynamics, and it may be possible to identify colleagues who fulfill some of these roles or identify teams that have passed through these different

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stages of development. Unfortunately, such a restricted approach to monitoring team process does not provide any feedback as to whether the team is producing predictable results, nor does it identify problems or opportunities for improvement — especially breakthrough opportunities. Specifically, no opportunity exists to determine whether team process is “in control” (capable) or whether the group is “out of control” (chaotic and falling far short of what it could achieve). Some of these issues were addressed in Volumes I and II of this series, and perhaps the reader may want to review them at this time. A further shortcoming in non-systems approaches to team building concerns team process improvement. As long as the team is operating within “acceptable” parameters, no opportunity or drive to improve or maximize the performance of the team exists. Furthermore, the team usually does not have the ability or training to self-regulate and, through self-regulation, to begin to change and adapt to the continual change taking place in the workplace. These and other considerations suggest that a systems approach to team building may have considerable advantages. The robust team involves an examination of teams as systems in conjunction with more detailed parallels between a team systems approach and the model put forward by Taguchi as part of his quality engineering methodology (see Volume V of this series). Using this viewpoint, a system is considered as a means by which a user’s intention is transformed into a perceived result. Therefore, if teams are considered in terms of how successfully they transfer energy when they function, it should be evident that there will be parallels between their functioning and the functioning of an engineered system — as in the P diagram for example. After all, in many ways, a team shares similar features to the manufacturing process of a particular product. Specifications are drawn up (objectives, time scales, etc. are established); the production machinery is put in place (team members are selected); the production process is designed and implemented (teams meet, establish norms, set agendas, and engage in problem solving, decision making, and planning activities, etc.) and the system is regulated by performance criteria (by the individual members’ expectations, assessments, performance appraisals, etc.). In manufacturing, it is important not to separate the performance of the component from its interaction with other components and its integration into large subsystems of the whole process or product. In teams, it is important not to separate the performance of the individual from his/her relationships to other team members, their interactions, and their membership in sub-teams and the team as a whole — rather it is of paramount importance to view them as a team system.

TEAM SYSTEMS Many social psychologists only consider a collection of people to be a group if their activities relate to one another in a systematic fashion. However, it is easier to define a group as a collection of individuals. The word “team,” however, as mentioned in Volume I, Part II, is reserved for those groups that constitute a system whose parts interrelate and whose members share a common goal. Some groups can easily be viewed according to this criterion. A soccer club, its manager, and its players constitute a set of parts necessary to the functioning of the whole — the common

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aim being to win soccer games. However, when does a newly established team become a good or effective team? To see the answer to this question let us examine the team from a systems approach. Input A team has an input or signal. The input is the information, energy, resources, etc., that enter into the system and are transformed through its structures and processes. A broad spectrum of inputs into the system can exist and, depending on the perspective one chooses to take, the boundaries that are drawn around the system can be more or less inclusive of these elements. A system in which the boundary is closely defined will have only the fixed structures and extant processes within it and will have a wide range of inputs, many of which may enter the system simultaneously. A system that has a very broad boundary might include people, materials, resources, and most information as a part of the system, with the input defined very narrowly as a discrete piece of information or energy. Signal The signal as developed in the Taguchi model has a more specific and limited definition. It is an input into the system, but it is limited to the means by which the user conveys to the system a deliberate intention to change (or adjust) the system output. In more general terms, it is the variable to which the system must respond in order to fulfill the user’s intent. From this perspective, most of what are traditionally considered inputs into the system, i.e., people, materials, information, and so on, are already part of the system itself, and the signal is the discrete piece of information that determines the amount of energy transformed by the system. The System The structure of a system comprises aspects of the system that are relatively static or enduring. Process, on the other hand, refers to the behavior of the system. Consequently, process refers to those relatively dynamic or transient aspects of a system that are observable by virtue of change or instability. Traditional models of a system are based upon an input-process-output model. The system acts to transform the energy from the input into the output. This process, once established, is subject to variation due to internal and external factors that produce “error states” or outputs other than the desired output. These outputs can simply be wasted energy or may actually reduce the functional ability of the system itself. If a particular team has a task to perform, e.g., solving a problem, you can consider the team to be a system that has inputs, output, and a process that allows the team members to transform their energy into the desired outputs. Team process can be defined as any activity (for example, meetings) that utilizes resources (the team) to transform inputs (ideas, skills, and qualities of team members) into outputs (discoveries, solutions to problems, proposals, actions, design ideas, products, etc.).

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Often the energy that the team brings to the process is not used to best effect. For example, in a meeting, time may be wasted reiterating points because individuals have not paid attention to what is being discussed or because there is cross talk. This in turn leaves people annoyed and frustrated. These are examples of “error states” or undesirable outputs from the team process. Output/Response In traditional systems models, the output is whatever the system transforms, produces, or expresses into the environment as a consequence of the impact its structures and processes have on the input. An output can be anything from a newborn baby to well done barbecued ribs to a presentation to a text return. This is very important to understand because teams, by their nature, are complex and multifunctional. They cannot and should not be configured to produce one kind of response. Most teams will have a whole range of outputs with accompanying measures that will be used to identify how successful they are and how effective they are in transferring energy. The key is to identify appropriate measures that can be used to monitor the team’s progress. The Environment It is important in attempting to maximize the performance of a team to identify factors that may have an impact on the performance of the team and its ability to maximize the transfer of its input into desired output and over which the team has little or no control. (Remember, the output of the team will be a new design — however defined — and it is up to the team to make that design “wanted” in the preset environment. This is not a small feat.) These factors are designated as internal or external to the system. It is these factors that cause energy to be wasted and undesirable output (error states) to occur. External Variation In teams, external variation factors may include such things as change in team membership, the environment in which the team is working, changing demands from management, corporate cultural, racial, and gender factors, and so on. In developing a group process, it is important to develop group systems and processes that are robust to these factors. In addition, team goals exert a considerable influence on the behavior of individual members, and goals can vary enormously. They could be output targets that will vary in accordance with the team’s task — problem-solving teams puzzling over the root cause of a problem; design teams considering the optimization of a particular system design to achieve robustness; a marketing team attempting to understand the exact details of customer requirements; or sports teams, each of which will have an entirely different set of performance goals depending upon the sport: soccer, football, tennis, golf, and so on. Any analysis of working teams should take into account the objectives of the team and the situation in which the team performs because both will have a profound effect on the team functioning.

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Internal Variation Internal variation, on the other hand, relates to factors that are in the team system and its members. People may bring predetermined ideas about the correct design solution. They may have biases about other team members depending on their race, gender, function, grade, and so on. Certain team members may not get along with other team members and will regularly question, challenge, or contradict the others for no apparent reason. The team may not manage its time well and consequently may find itself chronically short of time at the end of meetings. Team members may not know how to ask open questions that will open up fresh avenues of information. Closed questions will result in familiar dead ends or nonproductive and previously rejected ideas. Team members may not know how to build on the ideas of other team members and, consequently, good ideas may be regularly lost. If the reader needs help in this area, we recommend a review of Volume I, Part II. The Boundary At the simplest level, boundaries can be put around almost anything, thereby defining it as a system. In practice, the identification of the boundary is the key to successful system analysis. The classification of factors (signal, control, and variation) that impact on the system is dependent on the way in which the boundary is defined. For example, by setting the boundary of the system fairly wide, to include the team members, environment, resources, information, and so on, leaving only the directive from the champion or the monthly output target outside, more factors would be considered as control factors and fewer as variation. In this case, the directive from the champion would be the signal factor. The team members, environment (or aspect of it), and so on would be control factors. External variations would then include disruptions to the team process from sources outside the team boundary. Internal variations would include attitudinal, cultural, and intellectual variations among and between team members and variations in environmental conditions (e.g., temperature). By setting a narrower boundary, many of the factors such as environment and resources would be considered external to the system and therefore would become noise factors rather than control factors. These issues are important because they determine the team’s strategy for dealing with variations and establishing a means of becoming robust to them.

CONTROLLING

A

TEAM PROCESS: CONFORMANCE

IN

TEAMS

A tale in Hellenic mythology describes the behavior of Procrustes — an innkeeper by the Corinthean peninsula. Procrustes took his clientele, people of definite natural shape and size, and either stretched or truncated their limbs so that they might fit the mattresses he provided. There are many echoes here of the original approach to quality, “We know what you want, we will design it, you will buy it and you will like it.” Or the now famous quality euphemism, “We are not sure of what is really quality, but we sure know it, if we ever see it.” Fortunately, this philosophy is being transformed into a “customer-driven approach” and the pursuit of Total Quality Excellence through DFSS. It is not entirely

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unreasonable, therefore, when it comes to monitoring groups or teams, to identify an alternative to the current emphasis on fitting the behavior of team members into behavioral roles through a “Procrustean” method, that is, by squeezing identity and function into personality models like those of Belbin, Myers-Briggs, Bion, and so on, through normalization and pressure to conform. Remember, one of the diversity issues is the fact that everyone is different and we are all much better because of that difference. This is particularly the case when old norms are not questioned and challenged regularly or when personality models are used to avoid genuine personal contact or in place of a genuine understanding of the uniqueness of others.

STRATEGIES

FOR

DEALING

WITH

VARIATION

There are four basic strategies for dealing with variation and its effect on the performance of a system: ignore the variation, attempt to control or eliminate the variation, compensate for the variation, or minimize the effect of the variation by making the system robust to it. Adopting the first of these strategies would mean accepting that teams will never function efficiently, but hoping that they will “do the best they can under the circumstances.” As with an engineering system, this strategy would result in a lot of unhappy customers. Generally, with engineering systems, you are encouraged to adopt strategy four first, reverting only to strategies two and three as a last resort because they are difficult and expensive to implement. While strategy four should also be chosen in the case of the team system wherever possible, you have greater flexibility in many cases to consider the other two options. Controlling or Eliminating Variation Procrustes’ behavior is an example of controlling inner variation. While this approach to variation might be considered extreme, you may have some scope for selecting team members with the right characteristics for effective teamwork as well as the necessary technical expertise. External variations are perhaps a little easier to deal with. For example, you could ensure that meetings are held away from the shop floor to reduce distractions due to noise (in the audible sense!) or hold them at an off-site location to minimize interruption. Compensating for Variation The principal means of compensating for variation is by providing some feedback on its effect on system output. The link between structure and process —the way in which structure determines process, and for your purposes perhaps more importantly, the way that process determines structure — is found in the concept of feedback loops. Feedback loops are so named because they are circular interrelationships that feed information from output back to input. Information is transmitted within the system and is used to maintain stability, to bring about structural changes, and to facilitate interaction with other systems.

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Even the simplest model of the effective team includes this concept of feedback loops. By employing information feedback loops, systems may behave in ways that can be described as “goal seeking” or “purposive.” Negative feedback allows a system to maintain stability as in the case of the most commonly quoted example, a thermostat. A thermostat is controlled by negative feedback so that when the temperature increases above a certain level the heating is switched off, but when the temperature decreases sufficiently the heating is switched on. The process of maintaining stability is called “homeostasis.” The capacity for such control is engineered into some mechanical systems and occurs naturally in all biological and social systems. Threats to the stability of the system will be countered in a powerful attempt to maintain homeostasis. System Feedback One alternative approach is to monitor those aspects of team behavior that are observable (i.e., gather “the voice of the process”). Descriptive Feedback offers a non-judgmental method of monitoring what happens in working groups. It allows team members to notice when team process is in control and meeting or exceeding predetermined expectations or drifting out of control and reducing potential. Descriptive Feedback provides three basic functions: 1. It makes explicit what is happening during team process. 2. It describes those characteristics of team process behavior, relationships, and feelings that may degrade or go out of control and inhibit the potential of the team. 3. It determines what, if anything, needs to be changed in order to facilitate continuous improvement in team process. Feedback over time enables a team to establish performance-based control limits. By using these data, specific characteristics or variables relating to team process can be plotted over time. This will identify patterns that emerge and that can be used to identify and capture the degree of variability of the team. Some patterns are related to “in control” conditions, others to “out of control” conditions, just as the patterns of points on a control chart can be used to establish whether a manufacturing process is in control or out of control. Based on feedback that describes what people notice and how they feel, the team is able to regulate its process and identify opportunities for improvement. Minimizing the Effect of Variation The Parameter Design approach used in quality engineering — see Volume V of this series — is concerned with minimizing the effect of variation factors by making the system robust. This involves identifying control factors — in this case, aspects of the team process that are within the control of the team and that can be used to reduce the impact of variation factors without eliminating or controlling the variation factors themselves. An example of a “control factor” functioning in this way is the

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use of Warm-Up and its consideration of “place” (layout, heating, lighting, ventilation) so that best use is made of the facility provided and distractions are minimized, even though the place itself and many of its features cannot be changed. The key to a successful team lies not only in identifying those parameters that are critical for the efficient transformation of inputs to the team process into outputs but also in doing this with minimal loss of energy in error states and maximum robustness to variation factors in the environment. Different types of teams with different outputs required of them would have different parameters established for their most efficient performance. Many of the structures, processes and skills that could be used as control factors in a team process have been identified in Volume I, Part II of this series. Through this process of observation, it is possible to establish control limits in a wider area of team performance. A number of the factors that have an impact on team performance can be observed and regulated through feedback, and “tolerance” for them can be established depending upon the makeup and objective of the team. These factors include warming up and down, place, task, maintenance, process management, team roles, agenda management, communication skills, speaking guidelines, meeting management, exploratory thinking guidelines, experimental thinking guidelines, change management, action planning, and team parameters. The traditional approach to engineering waits until the end of the design process to address the optimization of a system’s performance — in other words, after parameter values are selected and tolerances determined, often at the extremes of conditions and often without considering interactions among different components or subsystems. When the components and subsystems are integrated, and if performance does not meet the target value or the customer’s requirements, parameter values are altered. Consequently, though the system may be adjusted to operate within tolerance, this process does not guarantee that the system is producing its ideal performance. Similarly, traditional approaches to building teams have selected team members according to a number of factors: predetermined skills and knowledge, established roles for team members, and implemented structured norms. They also have waited until the end of the process of team design in order to optimize performance. If the team does not perform within the accepted values of these parameters, then it is adjusted: team members are changed, roles are redefined, norms are more strictly enforced. This, however, is against performance criteria that do not necessarily optimize the team’s performance nor add to the motivation or job satisfaction of the team members. The shift suggested in Parameter Design in engineering (and that may be applied to teams as well) is to move from establishing parameter values to identifying those parameters that are most important for the function of the process and then determine through experimental design the correct values for those parameters. The key is to establish the values that use the energy of the system most efficiently and that are resistant to uncontrollable impact from other factors internal or external to the system itself.

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MONITORING TEAM PERFORMANCE One way of monitoring team performance has already been suggested, namely the use of Descriptive Feedback. Gathering “the voice of the process” enables the team to evaluate its performance and to continuously improve its efficiency and hence its effectiveness, before completing the task. Preliminary work in using process-control charting from Statistical Process Control suggests that there is opportunity for application to group process. This provides a second means of monitoring and continuously improving the team’s performance. Critical “control factors,” identified using the Parameter Design approach, could be measured and monitored in this way. Based upon further refinement, it may be possible to establish control limits, targets, and tolerances for these factors. System Interrelationships A systems model of processes differs from traditional models in many ways, one of which is the notion of circular causality. In the non-systems view, every event has its cause or causes in preceding events and its effects on subsequent events: the scientist seeks the cause or effect. Using the linear method of causality, ultimate causes are sought by tracing back through proximate causes. However, many phenomena do not “fit” the linear model: the relationships between them — and the relationships between the attributes or characteristics of the elements — do not conform to this linear approach to causality. In engineering systems, a direct cause and effect relationship often exists between the component of the system and the transformation of the input into an output. A steering wheel channels the input of the vehicle operator directly into the output of the system. That is, turning the steering wheel to the right or left actually turns the wheels of the vehicle to the right or the left. However, it is equally clear that error states or phenomena are nowhere near as simple or linear in the causal relationship. Feedback loops and circular causality create very complex interactions. Similarly, the choice of lubricants may not affect the performance of the system until months or years later, when early deterioration of a transmission would result in difficulty shifting gears. Similarly, in teams, some cause and effect relationships are clearly related in time and others are not. Interventions by a timekeeper will affect the ability of the team to stick to its agenda. But other factors have more circular relationships. In a global problem-solving team, changing seating arrangements from the long-tabled boardroom style to a circular arrangement will result in more universal eye contact among team members, which may increase the team’s communication. This leads to enhanced exchange of information, which may lead to a clearer identification of the problem which will, in turn, lead to a more targeted search for relevant data, which will finally lead to a root-cause identification for the problem. Changing the seating arrangement may enhance finding a root cause more quickly than might have been the case in boardroom seating, and the cause and effect chain may be quite intricate.

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SYSTEMS ENGINEERING An emerging basis for unifying and relating the complexities of managerial problems is the system concept and its methodology. This concept has been applied more to the analysis of productive systems than to other fields, but it is clear that the value of the concept in management is pervasive. The word “system” has become so commonplace in the general literature as well as in the field that one often wants to scream, for its common use almost depreciates its value. Yet the word itself is so descriptive of the general interacting nature of the myriad of elements that enter managerial problems that we can no longer talk of complex problems without using the term “systems.” Indeed, we must learn to distinguish the general use of the term from its specific use as a mode of structuring and analyzing problems. One of the great values of the system concept is that it helps us to take a very complex situation and lend order and structure to it by using statistics, probability, and mathematical modeling. A major contribution of the concept is the reduction of complexity in managerial problems to a block diagram showing the relationship and interacting effects of the various elements that affect the problem at hand. At its present state of development and application, the systems concept is most useful in helping us gain insight into problems. At a second and very powerful level of contribution, however, systems analysis is gaining prominence as a basis for generating solutions to problems and evaluating their effects, and for designing alternate systems.

“SYSTEMS“ DEFINED We have been using the term systems without defining it. Though nearly everyone may have a general understanding of the term, it may be useful to be more precise. Webster defines a system as a regularly interacting or interdependent group of items forming a unified whole. Thus a system may have many components and objects, but they are united in the pursuit of some common goal. They are in some sense unified, organized, or coordinated. The components of a system contribute to the production of a set of outputs from given inputs that may or may not be optimal or best with respect to some appropriate measure of effectiveness. Systems are often complex, although the definition does not specify that they need to be. It is probably correct to say that some of the most interesting systems for study are complex and that a change in one variable within the system will affect many other variables of the system. Thus in productive systems, a change in production rate may affect inventories, hours worked per week, overtime hours, facility layout, and so on. Understanding and predicting these complex interactions among variables is one of our main objectives in this section. One of the elusive aspects of the systems concept is in the definition of a specific system. The fact that we can define the system that we wish to consider and draw boundaries around it is important. We can then look inside the defined system to see what happens, but it is just as important to see how the system is affected by its environment.

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Thus, invariably, every system can be thought of as a part of an even larger system. One of the dangers of defining systems that are too narrow in scope is that we may fail to see broader implications. On the other hand, a broad definition runs the risk of leaving out important details involved in the functioning of the system. Obviously, there is a large element of “art” in the application of systems concepts. Systems can be open or closed. An open system is one characterized by outputs that respond to inputs but where the outputs are isolated from and have no influence on the inputs. An open system is not aware of its own performance. In an open system, past performance does not control future performance. A closed system (sometimes called a feedback system), on the other hand, is influenced by its own behavior. A feedback system has a closed loop structure that brings results from past action of the system back to control future action. There are two types of feedback systems: the negative feedback, which seeks a goal and responds as a consequence of failure to achieve the goal, and the positive feedback, which generates growth processes wherein action builds a result that generates still greater action. Unfortunately most of the feedback systems in managerial problems are of the negative feedback type where the objective is to control a process.

IMPLICATIONS

OF THE

SYSTEMS CONCEPT

FOR THE

MANAGER

Managers who put the systems concept to work are rewarded initially by the development of a deeper understanding of the systems that they manage. By developing the structure of the interacting effects of system components and the various feedback control loops in the system, managers can see better which “handles” to twist in order to keep themselves in control. Indeed, with a knowledge of the system structure, a manager can see how it might be possible to restructure the system in order to create the most effective feedback control mechanisms. With the availability of large-scale system models (simulation, statistical, reliability, and mathematical models) a manager is better able to assess the effects of changes in one division component on another and on the organization as a whole. Furthermore, the managers of any of the productive operations are better able to see how their units fit into the whole and to understand the kinds of trade-offs that are often made by higher level management and that sometimes seemingly affect one unit adversely. Perhaps one of the most important contributions of systems thinking is in the concept of suboptimization. Suboptimization often occurs when one views a problem narrowly. For example, one can construct mathematical formulas to determine the minimum cost (optimum) quantity of products or parts to manufacture at one time, which results in a supposedly optimum inventory level. If one broadens the definition of the system under study, however, and includes not just the inventory and reorder subsystem but the production and warehousing subsystems as well, it may turn out that the inventory-connected costs are a measure of only part of the problem. If the product exhibits seasonal sales, the costs of changing production levels may be significant enough to warrant carrying extra inventories to smooth production and employment. In such a situation, the minimum cost inventory model would be a suboptimal policy.

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Organizational suboptimization often occurs when the production and distribution functions of an enterprise are operated as essentially two different businesses. The factory manager will be faced with minimizing production cost while the sales/distribution manager will be faced mainly with an inventory management, shipping, and customer service problem. Each suborganization attempting to optimize separately will likely result in a combined cost somewhat larger than if the attempt were made to optimize the combined system. The reasons are fairly obvious, since in minimizing the costs of inventories, the sales function transmits directly to the factory most of the effects of sales fluctuations instead of absorbing these fluctuations through buffer inventories. Suboptimization is the result. By coordinating the efforts of the production and distribution managers, however, it may be possible to achieve some balance between inventory costs and the costs of production fluctuation. Another way to view suboptimization is through the “hidden factory” — the terminology of six sigma. If we take for example the issue of safety, let us examine what is really at stake. No one will deny that the bottom line of all safety programs is injury prevention, more often called “loss control.” To appreciate the concept of “loss control,” however, we must look at the direct and indirect costs (often called the hidden costs) associated with an on-the-job injury. The direct costs are: 1. Medical 2. Compensation The indirect costs are: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.

Time lost from work by injured Loss in earning power Economic loss to injured’s family Lost time by fellow workers Loss of efficiency due to breakup of crew Lost time by supervision Cost of breaking in new worker Damage to tools and equipment Time damaged equipment is out of service Spoiled work Loss of production Spoilage — fire, water, chemical, explosives, and so on Failure to fill orders Overhead cost (while work was disrupted) Miscellaneous (There are at least 100 other items of cost that appear one or more times with every incident in which a worker is injured.)

The point here is that with most injuries the focus becomes the direct cost, thereby dismissing the indirect costs. It has been estimated time and again that the cost relationship of direct to indirect cost is one to three, yet we continue to ignore the real problems of injury. An appropriate system design for injury prevention would

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minimize if not eliminate the hidden costs. Generally speaking, the system should include (a) engineering, (b) education, and (c) enforcement considerations. Some specific considerations should be: 1. 2. 3. 4.

Workers will not be injured or killed Property and materials will not be destroyed Production will flow more smoothly You will have more time for the other management duties of your job

DEFINING SYSTEMS ENGINEERING A simple definition of systems engineering is: A customer/requirements–driven engineering and management process which transforms the voice of the customer(s) into a feasible and verified product/process of appropriate configuration, capability, and cost/price. A system is always greater than the sum of its parts and is no better than the weakest link. The derivative of that, of course, is that optimizing a part does not optimize the whole. This was brought out by Mayne et al. (2001), when they reported that 37% of all the automotive warranty for model year 2000 was in interfacing of parts rather than individual components. The message of Mayne and coworkers and most of us in the quality field has been and continues to be: interactions determine the performance of the system. We cannot, no matter how hard we try, fully understand the whole by breaking down and analyzing parts — yet design is historically done precisely that way. Systems engineering builds on the fact that the whole is the most important entity and that integration to meet cost, schedule, and technical performance is dependent on both technical and management intervention. Ultimately, systems engineering is a team-based activity. This is very important because as we move into the future we see that: 1. Quality is becoming more customer dependent rather than definitional from the provider’s point of view. In other words, we must specify what the product or service must do and how well it must do it, then verify the design to those requirements. 2. Products/services are becoming more sophisticated (complex). 3. Traditionally, product development has been very serial with designs thrown over the imaginary wall to manufacturing — something that today is not working very well. This has resulted in late changes and ultimately higher costs. Systems engineering is based on the notion that design may be on a parallel development process and with a strong consideration for its total life cycle — manufacture, delivery, maintenance, decommission, and recycling. For systems engineering to be effective in any organization, that organization must be committed to integration of several items including timing of development and specific delivery(ies) at specific milestones. A generic approach to facilitate this is the following model, involving the steps of pre-feasibility analysis, requirement analysis, design synthesis, and verification.

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PRE-FEASIBILITY ANALYSIS Before the actual analysis takes place there is a preliminary trade-off analysis as to what the customer needs and wants and what the organization is willing to provide. This is done under the rubric of preliminary feasibility. When the feasibility is complete, then the actual requirement analysis takes place.

REQUIREMENT ANALYSIS The requirement analysis involves the following steps: 1. Collect the requirements — the customer’s needs, wants, and expectations are collected at every level. 2. Organize requirements — group the information in such a way that requirements are easy to address. Determine if the requirements are complete. 3. Translate into more precise terms — cascade the definitions to precise terms, honing their definition to the best possible correlation of real world usage. 4. Develop verification requirements — preliminary verification tests are discussed and proposed here to make sure that they are in fact doable. At the end of the requirement analysis the results are moved to the second stage of the system engineering model, which is design synthesis. However, before the synthesis actually takes place, another feasibility analysis is completed to find out whether the organization is capable of designing the requirements of the customer. This feasibility analysis takes into consideration the organization’s knowledge from previous or similar designs and incorporates it into the new. The idea of this feasibility analysis is to make sure the designers optimize reusability and carry over parts and/or complete designs.

DESIGN SYNTHESIS Design synthesis involves the following steps: 1. Generate alternatives — the more alternatives the better. The alternatives are generated with functionality in mind from the customer’s perspective as reflected in the system specifications. Remember that the ultimate design is indeed a trade-off design. 2. Evaluate alternatives — the generated alternatives are evaluated with appropriate benchmarking data and integrated into the design based on the customer’s requirements. 3. Generate sub element requirements — big chunks or sub elements are chosen and requirements cascaded to each sub element. As the cascading process continues, verification requirements are also developed to test the overall system integrity as more and more sub elements are integrated into the total system.

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At the end of the design synthesis a very important analysis takes place. This analysis tests the integrity of the design against the customer’s requirements. If it is found that the requirements are not addressed (design gap), a redesign or a review takes place and a fix is issued. If, on the other hand, everything is as planned, the process moves to the third link of the model — verification.

VERIFICATION The final stage is verification. It involves the following: 1. Verify that requirements are complete — a review of all requirements from both design and the customer takes place with appropriate tests and correlated to real world usage. 2. Verify that design meets customer’s requirements — CAE tools, labs, rigs, simulations, and key life testing are some of the verification methodologies used at this stage. The intent here is to verify that the selected system and cascaded requirements will meet the customer’s requirements and provide a balanced optimum design from the customer’s perspective. At the end of this stage, if problems are found they (the problems) revert back to the design; if there are no problems, the design goes to manufacturing, with a design ready to fulfill the customer’s expectations. This final stage in essence tests the integrity of the design against the actual hardware. In other words, the questions often heard in verification are: Does the design work? Can you prove it? The beauty of this model is that it is an iterative model, meaning that the process — no matter where you are in the model — iterates until a balanced optimum design is achieved. This is because the goal is to design a customer-friendly design with compatibility, carryover, reusability, and low complexity requirements compared to other, similar designs. Iterations happen because of human oversights, poorly defined requirements, or an increase in knowledge. Another special characteristic of systems engineering is the notion of traceability. Traceability is reverse cascading and is used throughout the design process to make sure that the voices of the customer, regulator, and corporate or lower-level design are heard and accounted for in the overall design. With traceability, extra caution is given to the trade-off analysis. This is because by definition trade-off analysis accounts for designs with certain priority levels among the needs and wants of the customer. In a trade-off analysis, we choose among stated design alternatives. However, a trade-off analysis is also an iterative process, and usually none of the alternatives is perfect [R(t) = 1 – F(t)]. This is important to remember because all trade-off analyses assess risk, both external and internal, of the given alternatives so as to make robust designs. A final word about verification and systems engineering: As we already mentioned, the intent of verification is to make sure that the hardware meets the requirements of the design. The process for conducting this verification is done — generally — in five steps, which are:

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1. Plan — Review all requirements and make a preliminary assessment as to their impact. At the end of this evaluation, take ownership of important requirements and begin the assessment of specific tests and methods. It is not unusual at this stage to review the plan again and perhaps combine, consolidate, or even adjust the plan completely. In this stage we select attribute data, as well, monitor the “unselected” requirement, schedule preliminary tests, and approve the testing schedule. As you begin to zero in on specific targets, you may want to take into consideration features of the proposed design and benchmarking data so that your targets become of value to the customer. If this plan is rich in information, it is possible to begin predicting and formulating prototype(s). 2. Execute — In this stage, the engineer in charge will determine which test(s) to run, when to run them, what the data should look like, and what to expect. Proper test execution is of importance here. 3. Analyze/revise — Analyze the test results, and see if the design has changed in any way. Determine whether to redo the test if the design changed during the test for any reason. At this stage you expect no design changes, only testing revisions and modifications. 4. Sign-off — This is the most common ending for a verification process. In this stage final approvals are given, usually several months before production begins. 5. Archive — This is a step that most engineers do not do, yet it is a very important step in the process. The idea of archiving or documenting is to make sure that key events are appropriately documented for future use. You may want to document unusual tests, time frames of specific tests, or any specific requirements that you had the intention of verifying but could not verify using the planned method. In essence, this phase of verification consists of lessons learned that need to be carried forward to the next design. The focus of this process is to make sure that the requirements are driving the process and not the tests regardless of how sophisticated they are. To be sure, tests are an integral part of verification, but they are the means not the end. The intent of the tests is to verify each requirement, and there is no wrong way as long as the testing method is linked to real world usage. The reason for doing all this is to: 1. 2. 3. 4.

Reduce workload in design verification Improve prototype and testing efficiency by avoiding duplication Improve testing quality resulting in higher sign-off confidence Improve communication and stronger relationships between customer and suppliers

ADVANCED QUALITY PLANNING Before we address the “why” of planning, we assume that things do go wrong. But why do they go wrong? Obviously, many specific answers address this question. Often the answer falls into one of these four categories:

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1. We never have enough time, so things are omitted. 2. We have done this, this way, in order to minimize the effort. 3. We assume that we know what has been requested, so we do not listen carefully. 4. We assume that because we finish a project, improvement will indeed follow, so we bypass the improvement steps. In essence then, the customer appears satisfied, but a product, service, or process is not improved at all. This is precisely why it is imperative for organizations to look at quality planning as a totally integrated activity that involves the entire organization. The organization must expect changes in its operations by employing cross-functional and multidisciplinary teams to exceed customer desires — not just meet requirements. A quality plan includes, but is not limited to: • • • • • • •

A team to manage the plan Timing to monitor progress Procedures to define operating policies Standards to clarify requirements Controls to stay on course Data and feedback to verify and to provide direction An action plan to initiate change

Advanced quality planning (AQP), then, is a methodology that yields a quality plan for the creation of a process, product, or service consistent with customer requirements. It allows for maximum quality in the workplace by planning and documenting the process of improvement. AQP is the essential discipline that offers both the customer and the supplier a systematic approach to quality planning, to defect prevention, and to continual improvement. Some specific uses are: 1. In the auto industry, demand is so high that Chrysler, Ford, and General Motors have developed a standardized approach to AQP. That standardized approach is a requirement for the QS-9000 and/or ISO/TS19469 certification. In addition, each company has its own way of measuring success in the implementation and reporting phase of AQP tasks. 2. Auto suppliers are expected to demonstrate the ability to participate in early design activities from concept through prototype and on to production. 3. Quality planning is initiated as early as possible, well before print release. 4. Planning for quality is needed particularly when a company’s management establishes a policy of “prevention” as opposed to “detection.” 5. When you use AQP, you provide for the organization and resources needed to accomplish the quality improvement task. 6. Early planning prevents waste (scrap, rework, and repair), identifies required engineering changes, improves timing for new product introduction, and lowers costs.

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7. AQP is used to facilitate communication with all individuals involved in a program and to ensure that all required steps are completed on time at acceptable cost and quality levels. 8. AQP is used to provide a structured tool for management that enforces the inclusion of quality principles in program planning.

WHEN DO WE USE AQP? We use AQP when we need to meet or exceed expectations in the following situations: 1. 2. 3. 4. 5.

During the development of new processes and products Prior to changes in processes and products When reacting to processes or products with reported quality concerns Before tooling is transferred to new producers or new plants Prior to process or product changes affecting product safety or compliance to regulations

The supplier — as in the case of certification programs such as ISO 9000, QS9000, ISO/TS19469, and so on — is to maintain evidence of the use of defect prevention techniques prior to production launch. The defect prevention methods used are to be implemented as soon as possible in the new product development cycle. It follows then, that the basic requirements for appropriate and complete AQP are: 1. Team approach 2. Systematic development of products/services and processes 3. Reduction in variation (this must be done, even before the customer requests improvement of any kind) 4. Development of a control plan As AQP is continuously used in a given organization, the obvious need for its implementation becomes stronger and stronger. That need may be demonstrated through: 1. Minimizing the present level of problems and errors 2. Yielding a methodology that integrates customer and supplier development activities as well as concerns 3. Exceeding present reliability/durability levels to surpass the competition’s and customer’s expectations 4. Reinforcing the integration of quality tools with the latest management techniques for total improvement 5. Exceeding the limits set for cycle time and delivery time 6. Developing new and improving existing methods of communicating the results of quality processes for a positive impact throughout the organization

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WHAT IS

THE

DIFFERENCE

BETWEEN

AQP

AND

43

APQP?

AQP is the generic methodology for all quality planning activities in all industries. APQP is AQP; however, it emphasizes the product orientation of quality. APQP is used specifically in the automotive industry. In this book, both terms are used interchangeably.

HOW DO WE MAKE AQP WORK? There are no guarantees for making AQP work. However, three basic characteristics are essential and must be adhered to for AQP to work. They are: 1. Activities must be measured based on who, what, where, and when. 2. Activities must be tracked based on shared information (how and why), as well as work schedules and objectives. 3. Activities must be focused on the goal of quality-cost-delivery, using information and consensus to improve quality. As long as our focus is on the triad of quality-cost-delivery, AQP can produce positive results. After all, we all need to reduce cost while we increase quality and reduce lead time. That is the focus of an AQP program, and the more we understand it, the more likely we are to have a workable plan.

ARE THERE PITFALLS

IN

PLANNING?

Just like everything else, planning has pitfalls. However, if one considers the alternatives, there is no doubt that planning will win out by far. To be sure, perhaps one of the greatest pitfalls in planning is the lack of support by management and a hostile climate for its practice. So, the question is not really whether any pitfalls exist, but why such support is quite often withheld and why such climates arise in organizations that claim to be “quality oriented.” Some specific pitfalls in any planning environment may have to do with commitment, time allocation, objective interpretations, tendency toward conservatism, and an obsession with control. All these elements breed a climate of conformity and inflexibility that favors incremental changes for the short term but ignores the potential of large changes in the long run. Of these, the most misunderstood element is commitment. The assumption is that with the support of management, all will be well. This assumption is based in the axiom of F. Taylor at the turn of the 20th century, which is “there is one best way.” Planning is assumed to generate the one best way not only to formulate, but to implement, a particular idea, product, and so on. Sometimes, this notion is not correct. In today’s “agile world,” we must be prepared to evaluate several alternatives of equal value. (See the section on system engineering). As a consequence, the issue is not simply whether management is committed to planning. It is also, as Mintzberg (1994) has observed, (1) whether planning is committed to management, (2) whether commitment to planning engenders commitment

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to the process of strategy making, to the strategies that result from that process, and ultimately to the taking of effective actions by the organization, and (3) whether the very nature of planning actually fosters managerial commitment to itself. Another pitfall, of equal importance, is the cultural attitude of “fighting fires.” In most organizations, we reward problem solvers rather than planners. As a consequence, in most organizations the emphasis is on low-risk “fire fighting,” when in fact it should be on planning a course of action that will be realistic, productive, and effective. Planning may be tedious in the early stages of conceptual design, but it is certainly less expensive and much more effective than corrective action in the implementation stage of any product or service development.

DO WE REALLY NEED ANOTHER QUALITATIVE TOOL TO GAUGE QUALITY? While quantitative methods are excellent ways to address the “who,” “what,” “when,” and “where,” qualitative study focuses on the “why.” It is in this “why” that the focus of advanced quality planning contributes the most results, especially in the exploratory feasibility phase of our projects. So, the answer to the question is a categorical “yes” because the aim of qualitative study is to understand rather than to measure. It is used to increase knowledge, clarify issues, define problems, formulate hypotheses, and generate ideas. Using qualitative methodology in advanced quality planning endeavors will indeed lead to a more holistic, empathetic customer portrait than can be achieved through quantitative study, which in turn can lead to enlightened engineering and production decisions as well as advertising campaigns.

HOW DO WE USE

THE

QUALITATIVE METHODOLOGY

IN AN

AQP SETTING?

Since this volume focuses on the applicability of tools rather than on the details of the tools, the methodology is summarized in seven steps: 1. Begin with the end in mind. This may be obvious; however, it is how most goals are achieved. This is the stage where the experimenter determines how the study results will be implemented. What courses of action can the customer take and how will they be influenced by the study results? Clearly understanding the goal defines the study problem and report structure. To ensure implementation, determine what the report should look like and what it should contain. 2. Determine what is important. All resources are limited and therefore we cannot do everything. However, we can do the most important things. We must learn to use the Pareto principle (the vital few as opposed to the trivial many). To identify what is important, we have many methods, including asking about advantages and disadvantages, benefits desired, likes and dislikes, importance ratings, preference regression, key driver analysis, conjoint and discrete choice analysis, force field analysis, value analysis, and many others. The focus of these approaches is to improve performance in areas in which a competitor is ahead or in areas where

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3.

4.

5.

6.

7.

45

your organization is determined to hold the lead in a particular product or service. Use segmentation strategies. Not everyone wants the same thing. Learn to segment markets for specific products or services that deliver value to your customer. By segmenting based on wants, engineering and product development can develop action oriented recommendations for specific markets and therefore contribute to customer satisfaction. Use action standards. To be successful, standards must be used, but with diagnostics. Standards must be defined at the outset. They are always considered as the minimum requirements. Then when the results come in, there will be an identified action to be taken, even if it is to do nothing. List the possible results and the corresponding actions that could be taken for each. Diagnostics, on the other hand, provide the “what if” questions that one considers in pursuing the standards. Usually, they provide alternatives through a set of questions specific to the standard. If you cannot list actions, you have not designed an actionable study. Better design it again. Develop optimals. Everyone wants to be the best. The problem with this statement is that there is only room for one best. All other choices are second best. When an organization focuses on being the best in everything, that organization is asking for failure. No one can be the best in everything and sustain it. What we can do is focus on the optimal combination of choices. By doing so, we usually have a usable recommendation based on a course of action that is reasonable and within the constraints of the organization. Give grasp-at-a-glance results. The focus of any study is to turn people into numbers (wants into requirements), numbers into a story (requirements into specifications), and that story into action (specifications into products or services). But the story must be easy to understand. The results must be clear and well-organized so that they and their implications can be grasped at a glance. Recommend clearly. Once you have a basis for an action, recommend that action clearly. You do not want a doctor to order tests and then hand you the laboratory report. You want to be told what is wrong and how to fix it. From an advanced quality planning perspective, we want the same. That is, we want to know where the bottlenecks are, what kind of problems we will encounter, and how we will overcome them for a successful delivery.

APQP INITIATIVE

AND

RELATIONSHIP

TO

DFSS

The APQP initiative in any organization is important in that it demonstrates our continuing effort to achieve the goal of becoming a quality leader in the given industry. Inherent in the structure of APQP are the following underlying value-added goals:

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1. Reinforces the company’s focus on continuous improvement in quality, cost, and delivery 2. Provides the ability to look at an entirely new program as a single unit • Preparing for every step in the creation • Identifying where the greatest amount of effort must be centered • Creating a new product with efficiency and quality 3. Provides a better method for balancing the targets for quality, cost, and timing 4. Allows for deployment of the targets using detailed practical deliverables with specific timing schedule requirements 5. Provides a tool for program management to follow up all program planning processes. The APQP initiative explicitly focuses on basic engineering activities to avoid concerns rather than focusing on the results in the product throughout all phases. Based on the fact that the deliverables are clearly defined between departments (supplier/customer relationships), program concerns and issues can be solved efficiently. The APQP initiative also is forceful in viewing the review process at the end of the cycle as unacceptable. Rather, the review must be done at the end of each planning step. This provides a critical step-by-step review of how the organizations are following best possible practices. Also, the APQP initiative has a serious impact on stabilizing the program timing and content. Stabilization results in cost improvement opportunities including reduction of special sample test trials. Understanding the program requirements for each APQP element from the beginning provides the following advantages: • • • • •

Clarifies the program content Controls the sourcing decision dates Identifies customer-related significant/critical characteristics Evaluates and avoids risks to quality, cost, and timing Clarifies for all organizations product specifications using a common control plan concept

Application of APQP in the DFSS process provides a company with the opportunity to achieve the following benefits: 1. It provides a value-added tool allowing program management to track and follow up on all the program planning processes — focusing on engineering method and quality results. 2. It provides a critical review of how each organization is following best possible practices by focusing on each planning step. 3. It identifies the complete program content upon program initiation, viewing all elements of the process as a whole (AIAG 1995; Stamatis 1998).

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Once program content has been clarified, the following information can be discerned: 1. 2. 3. 4.

Sourcing decision dates are identified. Customer-related significant/critical characteristics are specified. Quality, cost, and timing risks are evaluated and avoided. Product specifications are established for all organizations using a common control plan concept.

Using the APQP process to stabilize program timing and content, the opportunities for cost improvement are dramatically increased. When we are aware of the timing and concerns that may occur during the course of a program, it provides us the opportunity to reduce costs in the following areas: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Product changes during the program development phase Engineering tests Special samples Number of verification units to be built (prototypes, first preproduction units, and so on) Number of concerns identified and reduced Fixture and tooling modification costs Fixture and tooling trials Number of meetings for concern resolution Overtime Program development time and deliverables (an essential aspect of both APQP and DFSS)

For a very detailed discussion of APQP see Stamatis (1998).

REFERENCES Automotive Industry Action Group (AIAG), Advanced Product Quality Planning and Control Plan. Chrysler Co., Ford Motor Co., and General Motors. Distributed by AIAG, Southfield, MI, 1995. Mayne, E. et al., Quality Crunch, Ward’s AUTOWORLD, July 2001, pp. 14–18. Mintzberg, H., The Rise and Fall of Strategic Planning, New York Free Press, New York, 1994. Stamatis, D.H., Advanced Quality Planning. A Commonsense Guide to AQP and APQP, Quality Resources, New York, 1998.

SELECTED BIBLIOGRAPHY Bossert, J., Considerations for Global Supplier Quality, Quality Progress, Jan. 1998, pp. 29–34. Brown, J.O., A Practical Approach to Service: Supplier Certification, Quality Progress, Jan. 1998, pp. 35–40.

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Forcinio, H., Supply Chain Visibility: Is It Really Possible? Managing Automation, July 2001, pp. 24–28 Gurwitz, P.M., Six Questions to Ask Your Supplier About Multivariate Analysis, Quirk’s Marketing Review, Feb. 1991, pp 8–9, 23. Mehta, P.V. and Scheffler, J.M., Getting Suppliers in on the Quality Act, Quality Progress, Jan. 1998, pp. 21–28. Schoenfeldt, T., Building Effective Supplier Relationships, Automotive Excellence, Winter 1999, pp.17–25.

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2

Customer Understanding

In Volume I of this series, we made a point to discuss the difference between “customer satisfaction” and “loyalty.” We said that they are not the same and that most organizations are interested in loyalty. We are going to pursue this discussion in this chapter because, as we have been saying all along, understanding the difference between customer service and customer satisfaction can provide marketers with the competitive advantage necessary to retain existing customers and attract new ones. “Understanding” what satisfaction is and what the customer is looking for can provide the engineer with a competitive advantage to design a product and or service second to none. At first glance, service and satisfaction may appear to mean the same thing, but they do not; service is what the marketer provides and what the customer gets, and satisfaction is the customer’s evaluation of the level of service received based on preconceived assumptions and the customer’s own definition of “functionalities.” The satisfaction level is determined by comparing expected service to delivered service. Four outcomes are possible: 1. 2. 3. 4.

Delight — positive disconfirmation (a pleasant surprise) Dissatisfaction — negative disconfirmation (an unpleasant surprise) Satisfaction — positive confirmation (expected level of service) Negative confirmation, which suggests that you are neither managing expectations properly nor delivering good service

In managing service delivery, relying solely on the objective aspects of service is a mistake. Customers base future behavior on their evaluation of the experience they actually had, which is in effect their degree of satisfaction or dissatisfaction. In addition to determining that satisfaction degree, marketers should seek to learn the reasons underlying customers’ feelings (the insight) in order to tell the engineers what, how and when to make changes and maintain high satisfaction levels when they are achieved. In researching these areas, marketers should note that the why is not the what; nor is it the how. That is, what happened and how it made customers feel does not tell us why they felt as they did. And not knowing that, managing not only the service that customers experience but also their expectations becomes difficult, if not impossible. At times, service providers and customers tend to think differently. Consider this dealership example: After conducting 10 focus groups for an automotive company in a medium-size Midwestern city, the researchers discussed the findings in a review meeting with the head of marketing for the company. The researchers noted that, after having spoken with more than 100 recent customers, they had learned

49

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that the vast majority were frustrated and unhappy about having to wait more than 15 minutes before getting attended to. The marketing executive interrupted, saying, “Those customers should consider themselves lucky; if they were in the dealerships of one of our competitors, they would have to wait 20 to 30 minutes before they were seen by the service manager.” This example includes all the information needed to explain the difference between customer service and customer satisfaction. The customers in this example defined their personal expectations about the service — their waiting time experience — and clearly, a conflict existed between their service expectation (a short wait before being seen by a service manager) and their service experience (waits of more than 15 minutes). Customers then were dissatisfied with the waiting rooms and the dealerships in general. The marketing manager’s response to customer dissatisfaction was to note that the waits could have been worse: He knew that competitors’ dealerships were worse. He also knew customer waits of more than 30 minutes were not uncommon. In light of these data, he judged the 15- to 20-minute waits in the waiting room acceptable. Herein lies the conflict between service delivery and customer satisfaction. The important concept for this marketing executive — and for all marketers — is that customers define their own satisfaction standards. The customers in this example did not go to the competitors’ dealerships; instead, they came to the marketer’s dealership with a set of their own expectations in a preconceived environment. When the marketer used his service delivery criteria to defend the waiting time, he simply missed the point. Unfortunately, this illustration is typical of how many marketers think about customer satisfaction. They tend to relate customer satisfaction directly to their own service standards and goals rather than to their customers’ expectations, whether or not those expectations are realistic. To assess satisfaction, marketers must look beyond their own assessments, tapping into the customers’ evaluations of their service experience. Consider, for example, a bank that thought it was doing a good job of measuring service satisfaction but really was too focused on service delivery. This bank had developed a policy that time spent in the lobby room should be less than 15 minutes for all customers. A customer came into the office and waited 12 minutes in the reception area for a mortgage application. Then she waited another five minutes for the loan officer to clear all the papers from his desk from the previous customer and an additional three minutes for him to get the file and all the pertinent information for the current application. As this customer was leaving, she was asked to fill out a customer satisfaction questionnaire. Under the category for reception area waiting time, she checked off that she had waited less than 15 minutes. Based on this response, the bank’s marketing director assumed the customer was satisfied, but she was not; the customer had been told that if she came in for the mortgage loan during her lunch hour, she would be taken care of right away. Instead, she waited a total of 20 minutes for her application process to begin. She did not have time to shop for the gift her son needed that night for a birthday party, and her entire schedule was in disarray. She left dissatisfied.

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Understanding the difference between service and satisfaction is the first step in developing a successful customer satisfaction program, and all marketers must share the same understanding. Only customers can define what satisfaction means to them. Here are some practical ways to understand customers’ expectations: • Ask customers to reflect on their experiences with your services and their needs, wants, and expectations. • Talk to customers face to face through focus groups, as well as through questionnaires. A wealth of information can be collected this way. • Talk with your staff about what they hear from customers about their expectations and experience with service delivery. • Review warranty data. Remember the three words that can help you learn from your customers: What, how and why. That is, what service did you experience, how did it make you feel, and why did you feel that way? Continual probing with these three perspectives will deliver the answers you need to better manage service to generate customer satisfaction. As Harry (1997 p. 2.20) has pointed out: • • • • • •

We do not know what we do not know We cannot act on what we do not know We do not know until we search We will not search for what we do not question We do not question what we do not measure Hence, we just do not know

Therefore, part of this understanding is to identify a transfer function. That is, you need a bridge (quantitatively or qualitatively) that will define and explain the dependent variable (the customer’s needs, wishes, and excitements) with the independent variable(s) (the actual requirements that are needed from an engineering perspective to satisfy the dependent variable). The transfer function may be a linear one (the simplest form) or a polynomial one (a very complex form). Typical equations expressing transfer functions may look something like: Y = a + bx Y = f(x1, x2…xn) − sin θ  df a  r  a sin θ  sin cos + + =r θ + θ     dθ g cos θ  cos θ  cos2 θ  g cos2 θ  They can be derived from:

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• • • • • •

Known equations that describe the function Finite element analysis and other analytical models Simulation and modeling Drawing of parts and systems Design of experiments Regression and correlation analysis

In DFSS, the transfer function is used to estimate both mean (sensitivity) and variance (variability) of Ys and ys. When we do not know what the Y is, it is acceptable to use surrogate metrics. However, it must be recognized from the beginning that not all variables should be included in a transfer function. Priorities should be set based on appropriate trade-off analysis. This is because DFSS is meant to emphasize only what is critical, and that means we must understand the mathematical concept of measurement. The focus of understanding customer satisfaction has been captured by Rechtin and Hair (1998), when they wrote that “an insight is worth a thousand market surveys.” It is that insight that DFSS is looking for before the requirements are discussed and ultimately set. This will help us in identifying what is really going on with the customer. Let us look at the function first.

THE CONCEPT OF FUNCTION In any business environment, there may be no more powerful concept than that of function. To understand why this is a potent notion, we need to consider what we mean by “function.” What is “function?” Let us start with a common definition: “The natural, proper, or characteristic action of any thing...” This is the Webster’s New Collegiate Dictionary definition, and it is quite representative of what you will find in most dictionaries. This is actually a powerful and insightful definition. Think about any product or service that you purchase. What is it about the product or service (I will use the term “product” from here on, although every issue that will be discussed will be equally valid for services) that causes you to exchange money, goods, or some other scarce resource for it? Ultimately, it is because you want the “characteristic actions” that the product provides. These “actions” may be simple or complex, utilitarian or capricious, Spartan or gilded — but in each transaction, you enter with a set of unfulfilled wants and needs that you attempt to satisfy. Moreover, if the product you purchase actually manages to fulfill the wants and needs that you perceive, you are more likely to be satisfied with your purchase than when the product fails to satisfy your desires. Within these few short sentences, we have the fundamental principles that underpin three of the most powerful tools in the modern pantheon of quality, productivity, and profitability: Quality Function Deployment, Value Analysis, and Failure Modes & Effects Analysis. To put the concept of function into action, we need to refine our definition. The expanded definition we would like you to consider is “The characteristic actions that a system, part, service, or manufacturing process generates to satisfy customers.”

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In this expanded definition, you cannot only see the concept of function at work, but you may be able to recognize the essential abstraction of a process. In a process, some type of input is transformed into an output. As a simple equation, we might say that Input(s) + Transformation = Output(s) In the case of function, the inputs are the unfulfilled wants and needs that a customer or a prospective customer has. These can be and often are intricate; this is why the discipline of marketing is still more art than science. (We will have more to say about this issue in just a moment.) Nevertheless, there exist multiple sets of unfulfilled wants and needs that are open to the lures and attractions provided by the marketplace. In this very broad model, the transformation is provided by the producer. With one, ten, or hundreds of internal processes (within any discussion of process, there is always the “Russian doll” image: processes within processes within processes), business organizations attempt to determine the unmet wants and needs that customers have. The producer then must design and develop products and delivery processes that will provide tangible and/or intangible media of exchange that will assuage the unmet needs or need sets. Finally, the external processes that involve exchange of the producer’s goods for money or other barter provide the customer with varying degrees of satisfaction. The gratification (or lack of satisfaction) that results can then be viewed as the output of the general process. In business, the inputs are not within the control of producers. As a result, producers need powerful tools to understand, delineate, and plan for ways to meet these needs. This can be thought of as the domain of the Kano model or Quality Function Deployment. The transformational activities, however, are within the control of the producer. These “controlled” activities include planning efforts to deliver “function” at a satisfactory price; the nuances and subtleties of this activity can be strongly influenced or even controlled by the discipline of Value Analysis. In addition, fulfillment of marketplace “need sets” also implies that this fulfillment will occur without unpleasant surprises. Unwanted, incomplete, or otherwise unacceptable attempts to produce “function” often result in failure. This implies that producers have a need to systematically analyze and plan for a reduction in the propensity to deliver unpleasant surprises. This planning activity can be greatly aided by the application of Failure Modes and Effects Analysis techniques. To see how these ideas mesh, we need to consider how “function” can be comprehensively mapped. This will require several steps. To apply what will be discussed in the rest of this section, we need to emphasize the importance of choosing the proper scale for any analysis. The probability is that you will choose too broad a view or too much detail; we will try to provide guidance on this issue during our discussion of methods.

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UNDERSTANDING CUSTOMER WANTS

Six Sigma and Beyond AND

NEEDS

The nature of customer wants and needs is complex, deceptive, and difficult to discern. Nevertheless, the prediction of future wants and needs in the marketplace is perhaps the most important precursor to financial success that exists. Knowing and doing something that is profitable are two very separate (but not completely independent) aspects of this challenge. The first task that must be undertaken is to list the customers that we are interested in. Virtually no business is universal in terms of target market. Moreover, in today’s highly differentiated world, it is likely an act of folly to suggest that any product would have universal appeal. (Even an idealized product such as a capsule that, when ingested, yields immortality would have its detractors and would be rejected by some elements of humanity.) So, we need to start by cataloging the customers that we might wish to serve. In this effort, however, we need to recognize that there is a chain of customers. This is often seen in discussions of the “value chain,” a concept explored in detail by Porter (1985). For example, Porter discusses the concept of “channel value,” wherein channels of distribution “perform additional activities that affect the buyer, as well as influence the firm’s own activities.” This means that there are several dimensions on which we will discover important customers. First, there are market segments and niches. These can be geographic, demographic, or even psychographic in nature. Second, there are many intermediary customers, who have an important influence on ultimate purchases in the marketplace. Finally, there are what might be called “overarching” customers — persons or entities that must be satisfied even in the absence of any purchasing power — to enable or permit the sale of goods and services. This is readily visible in the auto industry. From the standpoint of a major parts manufacturer, say United Technologies, Johnson Controls, Dana Corporation, or Federal-Mogul, there are legions of important customers. In the market segment category, there are the vehicle manufacturers, including GM, Ford, Toyota, and all of the others. Contained within this category of customers are many sub-customers, including purchasing agents, engineers, and quality system specialists. As far as intermediary customers are concerned, we can consider perhaps a dozen or more important players. We need to consider the transportation firms that carry the parts from the parts plant to the assembly plant. We also need to think about the people and the equipment within the assembly plant that facilitate the assembly of the part into a vehicle. (If anyone doubts this is important, they have never tried to sell a part to an assembly plant where the assembly workers truly dislike some aspect of the part.) The auto dealer is yet another step in this array of hurdles, and mechanics and service technicians constitute still one more customer who must, in some way, be reasonably satisfied if commercial success is to spring forth. In addition, the auto industry has a web of regulatory and statutory requirements that govern its operation. These include safety regulations, emission standards, fleet mileage laws, and the general requirements of contract law. Behind these government requirements are still more governmental prerequisites, including occupational safety law, environmental law as applied to manufacturing, and labor law. This means that

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the governmental agencies and political constituencies that administer these laws can be seen as the “overarching” customers described previously. Ultimately, vehicle purchasers themselves are the critical endpoint in this chain of evaluation. And within this category of customers are the many segments and niches that car makers discuss, such as entry level, luxury, sport utility, and the many other differentiation patterns that auto marketers employ. Only when a product passes through the entire sequence will it have a reasonable chance of successfully and repeatedly generating revenue for the producer. This provides a critical insight about function. Function is only meaningful through some transactional event involving one or more customers. Only customers can judge whether a product delivers desired or unanticipated-yet-delightful function. In many cases (in fact, most), firms simply do not consider all of these customers. As a result, they are often surprised when problems arise. Moreover, they suffer financial impediments as a result — even though they may simply budget some degree of failure expectation into overhead calculations. A rational assessment of this situation means that the first requirement for understanding function is a comprehensive listing of customers. Frankly, this is very hard work, and it requires time, dedication, and effort. Regardless, understanding the customers that you wish to serve is an essential prerequisite to comprehension of function.

CREATING

A

FUNCTION DIAGRAM

If you want to understand function, the first requirement is the use of a special language. Function must be described using an active verb and a measurable noun. Fowler (1990) calls this linguistic construction a “functive” — a function described in direct terms that are, to the greatest degree possible, unambiguous. In a functive, the verb should be active and direct. How can you tell if the verb meets this test? Can you subject the action described by the verb to reasonable verification? One of the difficulties with this approach is the widespread affinity for ambiguity, the evil spawn of corporate life. To reduce ambiguity, you must avoid “nerd” verbs such as provide, be, supply, facilitate, and allow. Since most people pepper their business speech with these verbs, how can you avoid using them? If you cannot avoid “nerd verbs,” then you might try to convert the noun to a verb. Instead of “allow adjustment” think about what it is that you are adjusting. For example, you could easily restate this “nerd verb” functive with “adjust clearance.” Whenever a “nerd verb” comes up, try converting the noun that goes with the nerd verb to a verb, and then select the appropriate measurable noun. Most of the time, this will reduce the ambiguity. The measurable noun also must be reasonably precise. In particular, it should be relatively unchanging in usage and should rarely be the name of a part, operation, or activity used to generate the product or service under consideration. The test for a measurable noun is very simple: can you measure the noun? Bear in mind, however, that the measurement may be as simple as counting — or it can be a detailed statement of a technical or engineering expectation of the degree to which a function can be fulfilled. Ultimately, the combination of an active verb and measurable noun will give rise to an extent — the degree to which the functive is executed.

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For example, let us consider a simple mechanical pencil. The mechanism of the pencil must feed lead at a controlled rate. This also means that there must be a specific position for the lead. If the lead is fed too far, the lead will break. If the feed is not far enough, the pencil may not be able to make marks. As a result, one function that we can consider is “position lead.” The measurement is the length of exposed lead, and the desired extent of the positioning function may be 5 mm from the barrel end of the pencil. If there are limits on the extent in the form of tolerance, this is a good time to think about these limits as well.* While you are describing function in terms of an active verb and measurable noun, it is very important to maintain a customer frame of reference. Do not forget that function is only meaningful in terms of customer perception. No matter how much you may be enamored of a product feature or service issue, you must decide if the target customer will perceive your product in the same way.**

THE PRODUCT FLOW DIAGRAM

AND THE

CONCEPT

OF

FUNCTIVES

Now that we understand the essential issues involved in describing function, we can learn more about techniques for understanding the many complex functions that exist in a product. If products had just one or two functions, it would be easy to understand the issues that motivate purchase behavior. In today’s complex world, though, products seem to have more features (and hence more functions) nearly every day. How can we understand this complexity? Fortunately, there are common patterns that exist in the functionality of any product. We can see this through the creation of a product flow diagram. A product flow diagram uses simple, direct language to delineate function. This is a valuable aid to help you understand what your product provides to customers. We can start our efforts to develop this diagram by identifying functions. In practice, this is best done by a group or team, and it should be done after all participants have become familiar with the list of customers at whom the product is aimed. A general list of functions can then be developed using brainstorming techniques or other group-based creativity tools. There are a few issues that you should keep in mind while simply listing functions. Functions must describe customer wants and needs from the viewpoint of the customer. A common problem is to confuse product functions with functions being performed by the customer, the designer, the engineer who created the product, or the manufacturer who produces the product. Again, think about a mechanical pencil. Many people will start by describing the function of the pencil as “write notes.” However, the pencil, by itself, cannott write anything. (If you can invent a * When you do this, you have created a “specification” for this function. ** One of the most common and debilitating errors in market analysis is to assume that others will respond the same way that you do. This is a simple but profound delusion. Most of us think that we are normal, typical people. When we awaken in the morning, we look in the mirror and see a normal (although perhaps disheveled if we look before the second cup of coffee) person. Thus, we think, “I like this widget. Since I am normal, most other people will like this widget, too. Therefore, my tastes are likely to be a good guideline to what my customers will want.” In most cases, even if you really are “normal” and even “typical,” this easy generalization is dangerously false.

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pencil that will write notes without a writer attached you will probably become rich.) The function that is more appropriate for the pencil is “make marks.” The best way to start is to simply brainstorm as many functions as you can using active verbs and measurable nouns. There are many ways to brainstorm; in this case, it is usually easiest to have everyone involved use index cards or sticky notes to record their ideas. Remember that brainstorming should not be interrupted by criticism; just let the ideas flow. You will get things that do not apply, and, until you gain experience, you will not always use the “functive” structure that is ultimately important. Do not worry about these issues during the idea-generation phase of this process. Once you have a nice pile of cards or notes, start by sifting and sorting the ideas into categories. In any pile of ideas, there will be natural “groupings” of the cards. Determine these categories and then sort the cards. This can be thought of as “affinity diagramming” of the ideas. You will find some duplicates and some weird things that probably do not belong in the pile.* Discard the excess baggage and look at the categories. Are there any important functions you have missed? Do not hesitate to add new ideas to the categories, either. Finally, you are ready to bear down on the linguistic issues. Make sure that all of the ideas are expressed in terms of active verbs and measurable nouns. Change the idea to a “functive” construction, and then look for the “nerd” verb cards. Convert all of the “nerd verb” functions into true functives, with fully active verbs and measurable nouns. When you are done, you will have an interesting and important preliminary output. Now, count the cards again. If you have more than 20 to 30 cards, you have probably tackled too complex a subject or viewpoint. For example, a commercial airline has thousands — even hundreds of thousands — of functions. If you wanted to analyze function on the widest scale, you would probably be guilty of too much detail if you listed more than 30 functives. On the broadest scales of view, you may only list a handful of functions. Nothing is wrong with a short list, especially for the broadest view. If you have trouble, we can suggest some “function questions” that can assist you in your brainstorming. Try these questions: • What does it do? • If a product feature is deleted, what functions disappear? • If you were this element, what are you supposed to accomplish? Why do you exist? Ask the function questions in this order: • The entire scope of the project • A “system” view • Each element of the project * Do not automatically toss out strange ideas — see if the team can reword or express more clearly the idea that underlies the oddball cards or notes. Some percentage of these cards will have important information. Many will be eventual discards, but do not jump to conclusions.

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• A “part” view • Each sub-element of the project • A “component” view Finally, we can start our next task, which consists of arranging functions into logical groups that show interrelationships. In addition, this next “arranging” step will allow us to test for completeness of function identification and improve team communication. We start by asking “What is the reason for the existence of the product or service?” This function represents the fundamental need of the customer. Example: a vacuum cleaner “sucks air” but the customer really needs “remove debris.” Whatever this reason for being is, we need to identify this particular function, which we call the task function. You must identify the task function from all of the functions you have listed. If you happen to find more than one task function, it is quite likely that you have actually taken on two products. For example, a clock-radio has two task functions: tell time and play music. However, you would be far better served by breaking your analysis into two components — one for telling time, the other for playing music. Alternatively, this product could be considered on a broader basis, as a system — in which case the task function might be “inform user,” with subordinate functions of “tell time” and “play music.” In any event, once you have identified the task function, you will realize that there are many functions other than the task function. Divide the remaining functions by asking: “Is the function required for the performance of the task function?”

If the answer to this question is yes, then the function can be termed essential. If the answer is no, then the function can be considered enhancing. All functions other than the task function must be either essential (necessary to the task function) or enhancing. So, your next task is to divide all of the remaining functions into these two general categories. You can further divide the enhancing functions — the functions that are not essential to the task function. Enhancing functions influence customer satisfaction and purchase decisions. Enhancing functions always divide into four categories: 1. 2. 3. 4.

Ensure dependability Ensure convenience Please senses Delight the customer*

* “Delight the customer” is actually quite rare — most enhancing functions fit one of the other three categories. If you do find a “delight the customer” function, try comparing this with an “excitement” feature in a Kano analysis; you should find that the function fits both descriptions.

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None of these categories is needed to accomplish the task function. In fact, if you do not have a task function (and the associated essential functions), you probably do not have a product. The enhancing functions are those issues that purchasers weigh once they have determined that the task function will likely be fulfilled by your product. So, divide all of the enhancing functions into these four categories. Your next challenge is to create a function hierarchy that will, in finished form, be a function diagram. Start by asking this question: how does the product perform the task function? Primary essential functions provide a direct answer to this question without conditions or ambiguity. Secondary functions explain how primary functions are performed. Continue until the answer to “how” requires using a part name, labor operation, or activity, or you deplete your reserve of essential function cards. Now, you must reverse this process. Ask “why” in the reverse direction. For example, for a mechanical pencil, the task function is “make marks.” One of the functions you must perform to make marks is “support lead.” How do you support the lead? You do it by supporting the internal barrel tube (support tube) that carries the lead and by positioning this tube (position tube). Why do you support the tube and position the tube? You do this to support the lead. Why do you support the lead? You support the lead in order to make marks. The “chain” of function is driven by the how questions from the task function to primary then secondary functions — while this same chain is driven in reverse by why questions from secondary to primary to task function. As you progress, you will notice that you may be missing functions. If you find that you are, add additional functions as needed. After you have completed building “trees” of functions with the essential functions, repeat this process with the enhancing functions. The only difference is that the primary enhancing functions — ensure convenience, ensure dependability, please the senses, and delight the customer — have already been chosen. When you have finished, you will have a completed product flow diagram. At this point, try to delineate the extent of each function (range, target, specification, etc.) for each of the functions. Do not forget: Extent also tests “measurability” of each active verb–measurable noun combination. For example, for the mechanical pencil, the assembly may look like Figure 2.1. The sorted brainstorm list of functives may look like this: Entire project scope: • Make marks • Erase marks • Fit hand • Fit pocket • Show name • Display advertising • Convey message • Maintain point Tube assembly: • Store lead • Position lead

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Eraser

Tube Assembly Lead Barrel EAT AT JOE’S

0,7 mm

Clip FIGURE 2.1 Paper pencil assembly.

• Feed lead • Reposition lead • Support lead • Locate eraser • Position tube • Generate force • Hold eraser Lead: • Make marks • Maintain point Eraser: • Erase marks • Locate eraser Barrel: • Support tube • Support lead • Position lead • Protect lead • Position tube • Position eraser • Show name • Display advertising • Convey message • Fit hand • Enhance feel • Provide instructions Clip: • Generate force • Position clip • Retain clip And, finally, the function diagram (only one possibility among many, many different results) may look like Figure 2.2.

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Maintain point Support lead Basic Functions

Position lead

Support tube Position tube Store lead Feed lead Re-position lead

Make Marks

Ensure convenience

Erase marks

Hold eraser Retain clip

Fit pocket

Supporting Functions

Position clip

Ensure dependability

Provide Instructions

Please the senses

Enhance feel

Fit hand

Delight the customer

Display advertising Convey message

Show name

Position eraser Locate eraser Generate force

FIGURE 2.2 Function diagram for a mechanical pencil.

THE PROCESS FLOW DIAGRAM If you are working with a process rather than a product, you need to create a broad viewpoint “map” that shows how the activities in the process are accomplished. This can be done quickly and easily with a process flow diagram. The difficulty with most process flow diagrams is that they quickly bog down in too much detail. Whenever the detail gets too extensive, people lose interest (except for those who created the chart, but they are only part of the audience). Even though we need detail, we must avoid placing all of the details into one flow chart — at least if we want people to use the resulting charts. So, we will employ a “10 × 10” method that will aid in both communicating and managing the level of detail in a flow chart. If you keep the number of boxes in a flow chart to ten or fewer, most people will find your chart easy to read and understand. You can also use a “standard” symbol set for flow charting. After a great deal of trial and error from our experience, we have found that a simple set of ten symbols will explain almost any business process and provide enough options so that any team can easily illustrate what is going on — see Figure 2.3. By using some of the American National Standards Institute (ANSI) symbols and judiciously mixing in some easy-to-remember shapes, anyone can learn to flow chart a process in just a few minutes. The first step is to select a simple basis or point of view for your flow charts. This could be the view of the process operator, the work piece, or the process owner. (Be careful — if you

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Significant

Incidental

move

move

Output

Process

Input

Decision

Store

Delay

Inspect

Document

FIGURE 2.3 Ten symbols for process flow charting.

confuse your viewpoint while developing a flow chart, you will quickly become confused about the process functions.) Inputs and outputs are the easiest steps to understand. You start with an input and you end with an output. A document may be a special kind of input or output — it can appear at the beginning, at the end, or during the overall process. The process box is the most common box; it describes transformations that occur within the process. Decisions are represented by a diamond shape, and an inspection step (in the shape of a stop sign) is just a special kind of decision. If you delay a process, you use a yield sign. If you store information, you use an inverted yield sign — a pile. Movement is also important. If a move is incidental, you tie the associated boxes together with a simple arrow. However, if a movement is complex (say, sending a courier package to Hong Kong as opposed to handing it to your next-cubicle neighbor), then you may have a special transformation or process step that we call a “significant” move, i.e., a large horizontal arrow. Let us look at a simple process for handling complaints. Your office deals with customer complaints, but you have a local factory (where your office is) and a factory in Japan. How you handle a complaint might look like Figure 2.4. This flow chart shows many of the symbols noted above, but it is not the only way that the process could be flow charted. However, if the team that developed the chart (once again, a team approach is likely to be the most effective technique) can reach a high level of consensus, then the communication of these ideas to others will be powerful and comprehensive. Now that the basics of 10 × 10 (ten steps or fewer using ten or fewer symbols) are apparent, it becomes possible to construct a “hierarchy” of flow charts that will fill in missing details that may have been skirted with the “10 step limit.” The next step is to create a new 10 × 10 flow chart for each box in the top level flow chart that requires additional explanation to reach the desired level of detail. These next flow charts (typically three to five of the boxes require additional detail) make up the second level flow charts. Wherever necessary, go to another level of flow charts; continue creating 10 × 10 flow charts until you have a hierarchy of flow charts that directly addresses all of the details that you feel are important. Finally, for each process box on each flow chart, you will have a process purpose. Why did you do this step? Simple — you had one (or possibly two) purposes in

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Phone notice of customer complaint

Local or overseas factory?

Log complaint into database

Compile information for notice

Pending file

Local

Local factory is notified of complaint

Complaint notice

Overseas Send by courier to Japan

Factory is notified of complaint

FIGURE 2.4 Process flow for complaint handling.

mind when you designed this step into your process. Process purpose can be easily described using the language of function. Once again, you must use an active verb and a measurable noun. Often, a team can move directly to listing process functions from the flow charts. However, especially in manufacturing, it is common for the level of detail hidden in flow charts to be large, especially with intricate or subtle fabrication procedures. You may need to use an additional tool for teasing the “function” information from a flow chart called a “characteristic matrix.” A characteristic matrix is a reasonably simple analysis tool. The purpose of the matrix is to show the relationships between product characteristics and manufacturing steps. The importance of product characteristics in this matrix is significant; by considering the impact of a manufacturing step on product characteristics, we again focus our attention on customer requirements. Too often, manufacturing emphasis turns inward; it is critical that the focus be constantly directed at customers. Of course, there are “internal” customers as well. It is certainly important that intermediate characteristics, necessary for facilitating additional fabrication or assembly activities, be included in the analysis of function. For example, a simple machining process could have the characteristic matrix shown in Table 2.1. In this example, a simple machining step could be shown on a process flow chart with a process box that describes the machining operation as “CNC Lathe” or something similar. However, the lathe operation creates several important dimensions, or product characteristics, that are needed to meet customer expectations. These characteristics are sufficiently varied and complex that an additional level of detail is necessary. Some of these characteristics are important to the end customer; some are important to internal or “next step” process stations. For this example, the three left hand columns establish important functional information. The product characteristic is essentially the “measurable noun” (an

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TABLE 2.1 Characteristic Matrix for a Machining Process Product Characteristic

Target Value

Tolerance

Process Operations Lathe Turn 10

Diameter “A”

6.22 mm

±0.25 mm

Diameter “B”

3.25 mm

±0.1 mm

Shoulder “C”

12.2 mm

±0.5 mm

Radius “D”

0.5 mm

±0.05 mm

Lathe Turn 20

X

Face Cut 30

Deburr 40

C

L

X

C

L

X

C

Cut Radius 50

L X

X = Characteristic Created By This Operation C = Characteristic Used For Clamp Down In This Operation L = Characteristics Used As Locating Datum In This Operation

occasional adjective is acceptable in a functive if there are several identical nouns, such as diameter in this case). The extent is shown in the target dimension and tolerance columns, and the “active verbs” can be constructed or deduced from the “code letters” inserted in the matrix cells in the “Process Operation” columns. In any event, whether you are able to determine functions directly from a process flow chart or whether you find the use of characteristic matrices important, you need to end with a comprehensive listing of function. The important aspect of process function is to use a flow charting technique of some type to assist in reaching the comprehensive assessment of function that is similar to the point-by-point listing that can be achieved by the product flow diagram technique.

USING FUNCTION CONCEPTS QUALITY METHODOLOGIES

WITH

PRODUCTIVITY

AND

Earlier, we suggested that function concepts form a powerful fundamental basis for three major productivity and quality methodologies: • Quality Function Deployment (QFD) • Failure Modes and Effects Analysis (FMEA) • Value Analysis (VA) While we do not intend to explain these techniques fully in this context (however, they will be explained later), we would like to address the usefulness of function concepts in these methodologies. In these discussions, we are assuming that you have a passing or even detailed familiarity with these tools. If not, you may wish to pass over to the discussion of QFD later in this chapter or to Chapters 6 and 12 for lengthy discussions of FMEA and VA.

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For Quality Function Deployment, the most challenging issue is the one that we have just explored: how can one determine the functions that must be analyzed for deployment? In other forms, this is the same question facing practitioners in FMEA and VA. Clearly, the product flow diagram provides several instrumental techniques for improving these activities. A major difficulty in QFD is the often overwhelming complexity of the “House of Quality” approach. Constructing the first house, using conventional QFD techniques, is often the start of the complexity. Many different customer “wants” are listed. This is occasionally done as a “pre-planning” matrix. Moreover, the linguistic construction for these “wants” is undisciplined and subjective. Similarly, in FMEA, the initial list of failure modes is difficult to obtain. In VA, determining the “baseline” value assessment can also be difficult.* The techniques for developing a function diagram, especially the informal suggestions about “sizing” a project, can be very helpful in this regard. QFD, like FMEA and VA, typically fails to deliver the results expected because the project selected is too complex. A QFD study on a car or truck, for example, could easily contain hundreds of thousands of pages of information. That is not to say that the information in this study would not be valuable or that it should not be done; the issue is how complexity of this type should be dealt with. If you start with a systemwide view and construct a function diagram of the limited size previously discussed (20–30 functions maximum, even fewer are better), then this will provide a first level in a “hierarchy” of function diagrams. Subsequent analysis of various subsystems, then components and parts, and finally processes will complete the analysis. While the end result (for a car) would conceivably be of the same magnitude, the belief that all of the work must be done within the same team or by the same organization would be quickly abandoned. Moreover, the knowledge and understanding that is developed is generated at the hierarchical level (in the supply chain) of greatest importance, utility, and impact. Moreover, using the “functive” combination of active verbs and measurable nouns will assist in making QFD a useful tool. The vague, imprecise, or even confusing descriptions of function that are often used in QFD contribute to the difficulty in usage. A vehicle planning team may carry out a QFD study on the overall vehicle, assessing the major issues regarding the vehicle; these could include size, styling motifs, performance themes, and target markets. Subsequently, a study of the powertrain (engine, transmission, and axles) could be completed by another team. The engine itself could then be divided into major components: block, pistons, electronic controls, and so forth. Ultimately, suppliers of major and minor components alike would be asked to carry out QFD studies on each element. The multiplicity of information is still present, but it is no longer generated in some centralized form. This means that accessibility, usefulness, and the likelihood of beneficial deployment of the findings are much greater.** * In Value Analysis, the Function Analysis System Technique or “FAST,” a close cousin of the function diagram, is typically used to establish the initial functional baseline for value calculations. ** If the reader sees an “echo” of the hierarchy of flow charts, this is not coincidental.

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As an added benefit, starting QFD using this approach provides benefits in the completion of FMEA and VA studies, since a consistent set of functions will be used as a basis for each technique. We will next consider each of these in turn. We will start with FMEA, because the importance of function in this methodology is not widely understood or appreciated. In FMEA, determining all of the appropriate failure modes is usually a great challenge. This obstacle is reflected in the widespread difficulty in understanding what is a failure mode and what is an effect. For example, the effect “customer is dissatisfied” is often found in FMEA studies. While this is likely to be true, it is an effect of little or no worth in developing and improving products and processes. Similarly, failure modes are often confused with effect. This can be illustrated with another common product, a disposable razor. How can we determine a comprehensive list of failure modes? Simply start with an appropriate function diagram. For each function, we need to consider how these functions can go astray. There are a limited number of ways that this can occur, all related to function. If you consider the completion of a function (at the desired extent) to be the absence of failure, then pose these questions about each function in the function diagram: • • • • • •

What would constitute an absence of function? What would occur if the function were incomplete? What would demonstrate a partial function? What would be observed if there was excess function? What would a decayed function consist of? What would happen if a function occurs too soon or too late (out of desired sequence)? • Could there be an additional unwanted function?

Each of these conditions establishes a possible failure mode. For the disposable razor, the task function is generally understood to be “cut hair” (not, of course, to shave). The failure mode that is most obvious is an additional unwanted function, namely “cut skin.” Notice that the mode of failure is not “feel pain” or “bleed;” these are failure effects. To make use of these ideas in the context of the function diagram, we must next define “terminus” functions. Terminus functions are simply those functions at the right hand (or “how”) end of any function chain in the function diagram. In the mechanical pencil example, two terminus functions would be “position eraser” and “locate eraser.” Why do you position and locate the eraser? To hold the eraser. Why do you hold the eraser? To erase marks. Why do you erase marks? To ensure correctness. Since this chain is one of enhancing functions, we do not directly modify the task function. Start your analysis of failure modes by testing each of the possible conditions listed above against the terminus functions. After you have completed the terminus functions, move one step in the “why” direction. However, as you move to the left, you will find that you frequently discover the same modes for the other functions. Since the function chain shows the interrelated nature of the functions, this should

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not be surprising. As a rule, you will get most (if not all) of the relevant failure modes from the terminus functions.* So, starting with the terminus functions will speed your work and reduce redundancy. By working through each function chain in the function diagram, a comprehensive list of failure modes can be developed. This listing of failure modes then alters the approach to FMEA substantially; modes are clear, and cause-effect relationships are easier to understand. Moreover, developing FMEA studies using function diagrams that were originally constructed as part of the QFD discipline assures that product development activities continue to reflect the initial assumptions incorporated in the conceptual planning phase of the development process.** Once you have identified failure modes in association with functions, the remainder of the FMEA study — though still involved — is rather mechanical. For each failure mode, you must examine the likely effects that will result from this mode. With a clear mode statement, this is much simpler, and you are much less likely to confuse mode and effect issues. The effects can then be rated for severity using an appropriate table. With the effects in hand, causes can next be established and the occurrence rating estimated. Notice that this sequence of events makes the confusion of cause and effect much more difficult; in many cases, the logical improbability of reversal of cause and effect statements is so obvious that you simply cannot reverse these two issues. Finally, you can conclude the fundamental analysis with an evaluation of controls and detection. Once again, starting with a statement of function makes this clearer and less subject to ambiguity. Understanding the progression from function to mode to cause to effect sets the stage. What is it that you expect to detect? Is it a mode? In practice, detecting modes is extremely unlikely. You are more likely to detect effects. However, are effects what you want to detect? Once an effect is seen the failure has already occurred, and costs associated with the failure must already be absorbed. Let us return to the disposable razor to understand this. If the failure mode is “cut skin,” we must recognize that detecting “cut skin” is extremely difficult. You are much more likely to detect an effect — namely, pain or bleeding. Now, we recognize that we really do not want to detect failures at this point. Instead, we need to ask what are the possible causes of this failure mode. In this simple example, two different causes are readily apparent. From a design standpoint, the blades of the razor could be designed at the wrong angle to the shaver head. Even if the manufacturing were 100% accurate, a design that sets the blade angle incorrectly would have terrible consequences. On the other hand, the design could be correct; the blade angle could be specified at the optimum angle, but it could be assembled at an incorrect angle. Detection would best be aimed at testing the design angle*** and

* This is even more true for a system FMEA than for a design FMEA study. ** Of course, any change that is made in concept during development activities requires a continuous updating of the function diagrams under consideration. *** In the ISO and QS-9000 systems, we can think of this in terms of design verification.

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at controlling the manufacturing process so that the optimum design angle would be repeatable (within limits) in production.* Finally, the Value Analysis process can also make use of the function diagrams that serve in the QFD and FMEA processes. In VA, the essence of the technique is the association of cost with function. Once this is accomplished, the method of functional realization can be considered in a variety of “what if” conditions. If there is a comprehensive statement of function, VA teams can be reasonably sure that ongoing value assessments, based on the ratio of function to cost, have a consistent and rational foundation. Moreover, the teams have a much higher confidence that these “what if” questions take customer issues into proper account. Too often, VA activities are carried out as if function is well understood and only cost matters. In too many cases, no function analysis is even performed. Despite the long-standing cautions against this, this alluring shortcut is often taken to save time, money, or both. The shortcomings of skipping function analysis in VA are not trivial. More disappointing results in usage of the VA methodology have probably been obtained because function was not fully and comprehensively understood. At a very fundamental level, how can a value ratio analysis be performed without a full statement of function? This is like calculating a return on investment without knowing the investment. Moreover, the analysis of value ratio can be misleading if the function issue is not well defined. It is easy to reduce cost. You simply eliminate features and functions from a product. Soon, you will not even be able to accomplish the task function. (In practice, “functionless” VA studies typically eliminate important enhancing functions that make a critical difference in the marketplace, and customers consequently pronounce unfavorable judgments on “decontented” products. VA then gets the blame.) Since value studies typically occur subsequent to QFD and FMEA in product development activities, the difficulty of understanding function is eliminated if function is fully defined and even specified during these earlier activities. By using function as the basis for product and manufacturing activities, a degree of focus and understanding of customer wants and needs is preserved not only during VA activities but throughout the product life cycle.

KANO MODEL The tool of choice that is preferred for understanding the “function” is the Kano model. A typical framework of the model is shown in Figure 2.5. The Kano model identifies three aspects of quality, each having a different effect on customer satisfaction. They are: 1. Basic quality — take for granted they exist 2. Performance quality — the more principle 3. Excitement quality — the wow * This is the issue of “process control” in the ISO and QS-9000 systems — in QS-9000, it goes to the heart of the control plan itself. Also, this is a simplified example. In more detail, the failure mode of “cut skin” can even occur when the blade angle is correct both in design and execution. A deeper examination of these issues quickly leads to the consideration of “robustness” in the design itself.

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+ Y – axis (Customer satisfaction)

-

+ X – axis (product functionality)

-

FIGURE 2.5 Kano model framework.

The more we find out about these three aspects from the customer, the more successful we are going to be in our DFSS venture. (Caution: It is imperative to understand that the customer talks in everyday language, and that this language may or may not be acceptable from a design perspective. It is the engineer’s responsibility to translate the language data into a form that may prove worthwhile in requirements as well as verification. A good source for more detailed information is the 1993 book by Shoji.)

BASIC QUALITY “Basic” quality refers to items that the customer is dissatisfied with when the product performs poorly but is not more satisfied with when the product performs well. Fixing these items will not raise satisfaction beyond a minimum point. These items may be identified in the Kano model as in Figure 2.6. Some sources for the basic quality characteristics are: things gone right, things gone wrong, surrogate data, surveys, warranty, and market research.

PERFORMANCE QUALITY “Performance” quality refers to items that the customer is more satisfied with more of. In other words, the better the product performs the more satisfied the customer. The worse the product performs, the less satisfied the customer. Attributes that can be classified as linear satisfiers fall into this category. A typical depiction is shown in Figure 2.7. Some sources for performance quality characteristics are: internal satisfaction analysis, customer interviews, corporate targets/goals, competition, and benchmarking.

EXCITEMENT QUALITY “Excitement” quality refers to items that the customer is more satisfied with when the product is more functional but is not less satisfied with when it is not. This is the area where the customer can be really surprised and delighted. A typical depiction of these attributes is shown in Figure 2.8. Some sources for excitement quality characteristics are: customer insight, technology, interviews with comments such as high % or better than expected.

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+ Y – axis (Customer satisfaction)

-

+ product functionality

Brakes Horn Windshield wipers -

FIGURE 2.6 Basic quality depicted in the Kano model.

Performance Customer satisfaction + Quiet gear shift

+ X – axis (product functionality)

Wind noise Power -

Fuel economy

FIGURE 2.7 Performance quality depicted in the Kano model.

Customer satisfaction + Style Ride Features -

+ X – axis (product functionality)

-

FIGURE 2.8 Excitement quality depicted in the Kano model.

Items that are identified as surprise/delight candidates are very fickle in the sense that they may change without warning. Indeed, they become expectations. The engineer must be very cautious here because items that are identified as excitement items now may not predict excitement at some future date. In fact, we already know that over time the surprised/delighted items become performance items, the performance items become basic, and the basic items become inherent attributes of the product. A classic example is the brakes of an automobile. The traditional brakes were the default item. However, when disc brakes came in as a new technology, they were indeed the excitement item of the hour. They were replaced, however,

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71 Customer satisfaction +

-

Performance

+ product functionality

Excitement quality over time -

FIGURE 2.9 Excitement quality depicted over time in the Kano model.

with the ABS brake system, and now even this is about to be displaced by the electronic brake system. This evolution may be seen in the Kano model in Figure 2.9. Developing these “surprised and delighted” items requires activities that gain insight into the customers’ emotions and motivations. It requires an investment of time to talk with and observe the customer in the customer’s own setting, and the use of the potential product. Above all, it requires the ability to read the customer’s latent needs and unspoken requirements. Is there a way to sustain the delight of the customer? We believe that there is. Once the attributes have been identified, a robust design must be initiated with two objectives in mind. 1. Minimize the degradation of these items. 2. Preserve the basic quality beyond expectations. These two steps will create an outstanding reliability and durability reputation.

QUALITY FUNCTION DEPLOYMENT (QFD) Now that we have finished the Kano analysis, and we know pretty much what the customer sees as functional and value added items, we are ready to organize all these attributes and then prioritize them. The methodology used is that of QFD. QFD is a planning tool that incorporates the voice of the customer into features that satisfy the customer. It does this by portraying the relationships between product or process whats and hows in a matrix form. The matrix form in its entirety is called the House of Quality — see Figure 2.10. One of the reasons why QFD is used is because it allows us to organize the Ys and ys and xs into a workable framework of understanding. QFD does not generate the Ys, ys, or xs. Ultimately, however, QFD will help in identifying the transfer function in the form Y = f(x, n) QFD was developed in Japan, with the intent to achieve competitive advantage in quality, cost, and timing. To understand this need, one must comprehend what quality control is all about from Japan’s point of view. Japan’s industrial standards define Quality Control (QC) as a system of means to economically produce goods and/or services that satisfy customer requirements. It is this definition of QC that

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Correlation matrix HOW

Importance What

I M P O R T A N C E

Relationship matrix

I M P O R T A N C E

Competitive assessment

Technical difficulty How much Competitive assessment Important control items Importance

FIGURE 2.10 A typical House of Quality matrix.

propelled the Japanese to find not only a tool but a planning tool that implements the business objectives, of which the right application is product development. The definition of QFD is a systematic approach for translating customer wants/requirements into company-wide requirements. This translation takes place at each stage from research and development to engineering and manufacturing to marketing and sales and distribution. The QFD system concept is based on four key documents: 1. Overall customer requirement planning matrix. This document provides a way of turning general customer requirements into specified final product control characteristics. 2. Final product characteristic deployment matrix. This document translates the output of the planning matrix into critical component characteristics. 3. Process plan and quality control charts. These documents identify critical product and process parameters as well as benchmarks for each of those parameters.

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4. Operating instructions. These documents identify operations to be performed by plant personnel to assure that the important parameters are achieved.

TERMS ASSOCIATED

WITH

QFD

There are six key terms associated with QFD: Quality function deployment — An overall concept that provides a means of translating customer requirements into the appropriate technical requirements for each stage of product development and production (i.e., marketing strategies, planning, product design and engineering, prototype evaluation, production process development, production, sales). This concept is further broken down into “product quality deployment” and “deployment of the quality function” (described