Global Design to Gain a Competitive Edge: An Holistic and Collaborative Design Approach based on Computational Tools

Global Design to Gain a Competitive Edge Xiu-Tian Yan • Benoit Eynard • William J. Ion Editors Global Design to Gain...

Author: Xiu-Tian Yan | Benoit Eynard | William J. Ion

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Global Design to Gain a Competitive Edge

Xiu-Tian Yan • Benoit Eynard • William J. Ion Editors

Global Design to Gain a Competitive Edge An Holistic and Collaborative Design Approach based on Computational Tools

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Xiu-Tian Yan, BEng, PhD, CEng, MIET, FITL William J. Ion, Head of Department Department of Design, Manufacture and Engineering Management (DMEM) University of Strathclyde James Weir Building 75 Montrose Street Glasgow G1 1XJ UK

ISBN 978-1-84800-238-8

Benoit Eynard, PhD, MAFM, MDS Department of Mechanical Systems Engineering University of Technology Compiègne BP60319 60203 Compiègne Cedex France

e-ISBN 978-1-84800-239-5

DOI 10.1007/978-1-84800-239-5 British Library Cataloguing in Publication Data Global design to gain a competitive edge 1. Engineering design - Congresses I. Yan, Xiu-Tian II. Eynard, Benoit III. Ion, William J. 620'.0042 ISBN-13: 9781848002388 Library of Congress Control Number: 2008928771 © 2008 Springer-Verlag London Limited Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. The use of registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Cover design: eStudio Calamar S.L., Girona, Spain Printed on acid-free paper 9 8 7 6 5 4 3 2 1 springer.com

Preface

Recent rapid globalisation of manufacturing industries leads to a drive and thirst for rapid advancements in technological development and expertise in the fields of advanced design and manufacturing, especially at their interfaces. This development results in many economical benefits to and improvement of quality of life for many people all over the world. Technically speaking, this rapid development also create many opportunities and challenges for both industrialists and academics, as the design requirements and constraints have completely changed in this global design and manufacture environment. Consequently the way to design, manufacture and realise products have changed as well. The days of designing for a local market and using local suppliers in manufacturing have gone, if enterprises aim to maintain their competitiveness and global expansion leading to further success. In this global context and scenario, both industry and the academia have an urgent need to equip themselves with the latest knowledge, technology and methods developed for engineering design and manufacture. To address this shift in engineering design and manufacture, supported by the European Commission under the Asia Link Programme with a project title FASTAHEAD (A Framework Approach to Strengthening Asian Higher Education in Advanced Design and Manufacture), three key project partners, namely the University of Strathclyde of the United Kingdom, Northwestern Polytechncial University of China, and the Troyes University of Technology of France organised a third international conference. This conference aims to provide a forum for leading researchers, industrialists and other relevant stakeholders to exchange and debate their research results as well as research issue. This conference focuses on papers describing the cutting edge research topics, fundamental research issues related to the global advanced design and manufacture and recent industrial application papers with a goal towards bringing together design and manufacture practitioners from academics, government organisations, and industry from all over the world. The conference aims to cover the recent advancement and trends in the area of design and manufacturing and to facilitate knowledge sharing, presentations, interactions, discussions on emerging trends and new challenges in design and manufacturing fields. The particular focus of this conference is on the understanding of the impact of distributed team based design and manufacture on research and industrial practices for global companies. Being the third conference in this theme since 2004, the aims of the conference are: (a) to become a regular major forum for the international scientific exchange on multi-disciplinary and

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Preface

inter-organisational aspects of advanced engineering design and manufacturing engineering; and (b) to provide opportunities in presenting and formalising the methods and means for industrial companies to design and manufacture successful products in a globally distributed team based environment. It is well know that engineering design activities are mostly undertaken in the developed countries, represented by European, American and Japanese companies, whereas more manufacturing actives are undertaken by more companies that are located in Asian. This trend may start to change as some engineering design work is gradually outsourced in Asia companies as well. This increasing geographical distribution of tasks involved in the whole product realisation process brings great challenge as well as huge benefits fro all stakeholders. It is therefore timely to organise this international conference and bring together leading researchers, academics and industrialists to discuss these issues and promote the future research in these important areas. Out of 385 full papers submitted, the organisers use the review results from international reviewers, and finally selected 174 papers for publication. Based on the topics of the paper submitted, editors have divided them into relevant chapters and produced two books. This book is the first one and contains a selection of refereed papers presented at the third conference. It represents the latest thinking on engineering design and manufacture from mainly Europe and Asia perspectives. It includes 85 papers from 174 accepted refereed papers, focusing on the advancement in the area of advanced design and integrated design and manufacture area. This book is therefore a reflection of the key papers presented in all areas related to the advanced design, its technologies, and interface to manufacturing engineering. More specifically, the book covers the following seven broad topics in engineering design and each of these has been called chapter: Chapter 1: Front End of Engineering Design Conceptual design including shape design and synthesis, engineering guidelines from practical points of view, functional representation, customers’ requirement capture and so forth becomes even important in the context of global design and some of the selected papers just address their importance and research findings for global design. Chapter 2: Engineering Knowledge Management and Design for X In an ear of knowledge economy, capture of engineering design and manufacture knowledge, representation and their management become very important research and practical issues. Knowledge engineering support in various stages of the product realisation process is vital to the success of any enterprises. A a large selection of papers have been devoted to this topic.

Preface

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Chapter 3: Detail Design and Design Analysis Even at the time innovation and new product development becomes the main battle ground for competition, rigorous, reliable and new methods to support the detail design is still important. This has also been identified as an important research topic group from the papers submitted. Chapter 4: Simulation and Optimisation in Design Recent rapid development in computational power of desktop computers made advanced analysis software tools for product simulation and optimisation available even for small to medium sized companies as well as for educational users. This has resulted huge change in the way engineers conduct their engineering design and manufacture business. Sixteen papers have devoted their focus on the use of these technologies. Chapter 5: New Mechanism and Device Design and Analysis Eight papers have been selected to describe some new design and analysis of these devices. It is aimed to show the new Materials sciences focusing on functional ceramic material design and their manufacture; manufacturing systems design, simulation of their manufacturing systems and their optimisation. Chapter 6: Manufacturing Systems Design Design of manufacturing systems has traditionally been considered to be part of manufacturing discipline. Through the papers selected, it is clear that they form integral part of the product realisation process and hence they should be considered at the engineering design process. Chapter 7: Collaborative and Creative Product Development and Manufacture Following the previous chapter, this chapter deals with the collaborative issues of the advanced design and manufacture. Editors deliberately compiled this chapter to be the last chapter to reflect its link to Chapter 6. More importantly, it is appropriate to use this chapter to draw a conclusion to the book on global advanced design.

The editors of the book: Xiu-Tian Yan, Benoit Eynard and William J Ion

Acknowledgements

The editors would like to express their sincere thanks to the Advisory Scientific Board for their guidance and help in reviewing papers. Editors also would like to express their gratitude to the extended reviewers and the conference Secretariats Dr Fayyaz Rehman, Professor Geng Liu, Professor Jingting Yuan, Professor Hong Tang and Mrs Youhua Li for their patience and huge effort in organising the paper review process and answering numerous queries from authors. Without their support, it would have been very difficult to compile this book. The Editors would also like to thank Dr. Andrew Lynn for his kind support and maintenance of the conference paper management system which he developed for journal editing purpose. With a magic touch and modification, this system has provided with editors a wonderful tool to manage over eight hundred submissions in total. The Editors would also like to thank Mr Frank Gaddis for his help and design of the book cover. The editors of the book would also like to thank the sponsoring organisations for their support to the organisation of the Conference.

The Organisers of the ICADAM 2008 Conference: x x x

The University of Strathclyde Northwestern Polytechnical University The University of Technology Troyes

The Conference Sponsors: x x x x x x x x

European Commission; National Natural Science Foundation of China; Institution of Engineering Designers, UK; Institution of Mechanical Engineers, UK; The Design Society – A Worldwide Community; The Chinese Mechanical Engineering Society; Shaanxi Mechanical Design Society; Northwestern Polytechnic University - 111 project.

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Acknowledgements

ICADAM2008 Organising Committee Conference Co-Chairmen: Professor Chengyu Jiang, President of Northwestern Polytechnical University, Xian, China Professor Neal Juster, Pro-Vice Principal of the University of Strathclyde, UK Dr. Xiu-Tian Yan, The University of Strathclyde, UK Advisory Scientific Board Chair: Mr William J Ion, the University of Strathclyde, UK Dr. Muhammad Abid, Ghulam Ishaq Khan Institute of Sciences and Technology, Pakistan Professor Xing Ai, Academician of CAE, Shandong University, China Professor Abdelaziz Bouras, University of Lyon (Lyon II), France Dr. Michel Bigand, Ecole Centrale de Lille, France Dr. Jonathan Borg, University of Malta, Malta Professor David Bradley, University of Abertay, UK Prof. David Brown, Editor of AIEDAM, Worcester Polytechnic Institute, USA Professor Yang Cao, Hainan University, China Professor Keith Case, Loughborough University of Technology, UK Professor Laifei Cheng, Northwestern Polytechnical University, China Professor P John Clarkson, University of Cambridge, UK Professor Alex Duffy, University of Strathclyde, UK Dr. Shun Diao, China National Petroleum Corporation, China Professor Benoit Eynard, Troyes University of Technology, France Professor K Fujita, University of Osaka, Japan Professor James Gao, Greenwich University, UK Professor John S. Gero, University of Sydney, Australia Professor Philippe Girard, University of Bordeaux 1, France Professor Dongming Guo, Dalian University of Technology, China Professor Lars Hein, Technical University of Denmark, Denmark Professor Bernard Hon, University of Liverpool, UK Professor Imre Horvath, Delft University of Technology, Netherlands Professor Weidong Huang, Northwestern Polytechnical University, China Professor Sadrul Islam, Islamic University of Technology, Bangladesh Professor Chengyu Jiang, Northwestern Polytechnical University, China Professor Bert Jüttler, Johannes Kepler University, Austria Professor Neal Juster, University of Strathclyde, UK Professor Yuanzhong Lei, National Natural Science Foundation of China. Professor Hui Li, University of Electronic Science and Technology of China Professor Peigen Li, Academician of CAS, HUST, China Professor Qiang Lin, Hainan University, China

Acknowledgements

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Professor Udo Lindemann, Munchen University of Technology, Germany Professor Geng Liu, Northwestern Polytechnical University, China Dr. Muriel Lombard, University of Nancy 1, France Professor Jian Lu, The Hong Kong Polytechnic University Professor Chris McMahon, University of Bath, UK Professor Phil Moore, De Montfort University, UK Dr. David Nash, University of Strathclyde, UK Professor Henri Paris, University of Grenoble 1, France Professor Alan de Pennington, The University of Leeds, UK Dr. Yi Qin, University of Strathclyde, UK Professor Geoff Roberts, Coventry University, UK Professor Dieter Roller, Stuttgart University, Germany Dr. Lionel Roucoules, Troyes University of Technology, France Prof. Xinyu Shao, Huazhong University of Science and Technology, China Professor Hong Tang, Northwestern Polytechnical University, China Professor Tetsuo Tomiyama, Delft University of Technology, Netherlands Dr. Chunhe Wang, Institute of Petroleum Exploration & Development, China Professor Guobiao Wang, National Natural Science Foundation of China. Professor Runxiao Wang, Northwestern Polytechnical University, China Professor YuXin Wang, Tongji University, China Professor Richard Weston, Loughborough University of Technology, UK Professor Yongdong Xu, Northwestern Polytechnical University, China Dr. Xiu-Tian Yan, the University of Strathclyde, UK Professor Haichen Yang, Northwestern Polytechnical University, China Professor Shuping Yi, Chongqing University, China Prof. Xiao Yuan, Huazhong University of Science and Technology, China Professor Dinghua Zhang, Northwestern Polytechnical University, China Professor Litong Zhang, Academician of CAE, Northwestern Polytechnical University, China Professor Weihong Zhang, Northwestern Polytechnical University, China Professor Li Zheng, Tsinghua University, China

Extended Paper Review Panel Ms. Atikah Haji Awang, The University of Strathclyde, UK Dr. Iain Boyle, The University of Strathclyde, UK Professor Jonathan Corney, The University of Strathclyde, UK Mr. Alastair Conway, The University of Strathclyde, UK Professor Xiaolu Gong, The University of Technology Troyes, France Dr. Pascal Lafon, The University of Technology Troyes, France Dr. Shaofeng Liu, The University of Strathclyde, UK Professor Yuhua Luo, Universitat de Illes Balears, Spain Mr. Ross Maclachlan, The University of Strathclyde, UK Dr. Conrad Pace, The University of Malta Dr. Wenke Pan, The University of Strathclyde, UK

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Acknowledgements

Professor Xiangsheng Qin, Northwestern Polytechnical University, China Dr. Fayyaz Rehman, the University of Strathclyde, UK Dr. Sebastien Remy, The University of Technology Troyes, France Dr. Daniel Rhodes, The University of Strathclyde, UK Dr. Michael Saliba, The University of Malta Dr. Hiroyuki Sawada, Digital Manufacturing Research Center, National Institute of Advanced Industrial Science and Technology, Japan Professor Shudong Sun, Northwestern Polytechnical University, China Mr. David Steveson, The University of Strathclyde, UK Professor Shurong Tong, Northwestern Polytechnical University, China Professor Frank Travis, The University of Strathclyde, UK Dr. Dongbo Wang, Northwestern Polytechnical University, China Mr. Wendan Wang, The University of Strathclyde, UK Dr. Ian Whitfield, The University of Strathclyde, UK Dr. Qingfeng Zeng, Northwestern Polytechnical University, China Mr. Remi Zente, The University of Strathclyde, UK

Contents

Chapter 1

Front End of Engineering Design ......................... 1

Computer Aided Design: An Early Shape Synthesis System............................. 3 Alison McKay, Iestyn Jowers,Hau Hing Chau, Alan de Pennington, David C Hogg Constraints and Shortfalls in Engineering Design Practice............................. 13 Lars Hein, Zhun Fan Modular Product Family Development Within a SME.................................... 21 Barry Stewart, Xiu-Tian Yan Duality-based Transformation of Representation from Behaviour to Structure .............................................................................. 31 Yuemin Hou , Linhong Ji Automatic Adaptive Triangulation of Surfaces in Parametric Space............. 41 Baohai Wu, Shan Li, Dinghua Zhang Research on Modeling Free-form Curved Surface Technology ...................... 51 Gui Chun Ma , Fu Jia Wu, Shu Sheng Zhang Pattern System Design Method in Product Development ................................ 61 Juqun Wang, Geng Liu, Haiwei Wang Development of a Support System for Customer Requirement Capture ....... 71 Atikah Haji Awang, Xiu-Tian Yan Comparison About Design Methods of Tonpilz Type Transducer ................. 81 Duo Teng , Hang Chen, Ning Zhu, Guolei Zhu, Yanni Gou Effect for Functional Design............................................................................... 91 Guozhong Cao, Haixia Guo, Runhua Tan Quality Control of Artistic Scenes in Processes of Design and Development of Digital-Game Products................................................... 103 P.S. Pa, Tzu-Pin Su

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Chapter 2 Engineering Knowledge Management and Design for X .......................................................................... 115 Integration of Design for Assembly into a PLM Environment...................... 117 Samuel Gomes, Frédéric Demoly, Morad Mahdjoub, Jean-Claude Sagot Design Knowledge for Decision-Making Process in a DFX Product Design Approach ................................................................ 127 Keqin Wang, Lionel Roucoules, Shurong Tong, Benoît Eynard, Nada Matta Mobile Knowledge Management for Product Life-Cycle Design.................. 137 Christopher L. Spiteri, Jonathan C. Borg Research on Application of Ontological Information Coding in Information Integration................................................................................ 147 Junbiao Wang, Bailing Wang, Jianjun Jiang and Shichao Zhang RoHS Compliance Declaration Based on RCP and XML Database............. 157 Chuan Hong Zhou, Benoît Eynard, Lionel Roucoules, Guillaume Ducellier Research on the Optimization Model of Aircraft Structure Design for Cost ............................................................................................................... 167 Shanshan Yao, Fajie Wei Research on the Management of Knowledge in Product Development ........ 177 Qian-Wang Deng, De-Jie Yu Representing Design Intents for Design Thinking Process Modelling.......... 187 Jihong Liu, Zhaoyang Sun Application of Axiomatic Design Method to Manufacturing Issues Solving Process for Auto-body ......................................................................... 199 Jiangqi Zhou, Chaochun Lian, ZuopingYao, WenfengZhu, ZhongqinLin Port-Based Ontology for Scheme Generation of Mechanical System ........... 211 Dongxing Cao, Jian Xu, Ge Yang, Chunxiang Cui Specification of an Information Capture System to Support Distributed Engineering Design Teams ............................................................................... 221 A. P. Conway, A. J. Wodehouse, W. J. Ion and A. Lynn Collaborative Product Design Process Integration Technology Based on Webservice......................................................................................... 231 Shiyun Li, Tiefeng Cai Information Modelling Framework for Knowledge Emergence in Product Design .............................................................................................. 241 Muriel Lombard, Pascal Lhoste Flexible Workflow Autonomic Object Intelligence Algorithm Based on Extensible Mamdani Fuzzy Reasoning System .............................. 251 Run-Xiao Wang, Xiu-Tian Yan, Dong-Bo Wang, Qian Zhao

Contents

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DSM based Multi-view Process Modelling Method for Concurrent Product Development ............................................................. 261 Peisi Zhong, Hongmei Cheng, Mei Liu, Shuhui Ding Using Blogs to Manage Quality Control Knowledge in the Context of Machining Processes ..................................................................................... 273 Yingfeng Zhang, Pingyu Jiang and Limei Sun Analysis on Engineering Change Management Based on Information Systems ......................................................................... 283 Qi Gao, Zongzhan Du, Yaning Qu Research and Realization of Standard Part Library for 3D Parametric and Autonomic Modeling.................................................................................. 293 Xufeng Tong, Dongbo Wang, Huicai Wang Products to Learn or Products to Be Used? .................................................... 303 Stéphane Brunel, Marc Zolghadri, Philippe Girard Archival Initiatives in the Engineering Context ............................................. 313 Khaled Bahloul, Laurent Buzon, Abdelaziz Bouras Design Information Revealed by CAE Simulation for Casting Product Development.................................................................... 323 M.W. Fu An Ontology-based Knowledge Management System for Industry Clusters......................................................................................... 333 Pradorn Sureephong, Nopasit Chakpitak, Yacine Ouzrout, Abdelaziz Bouras

Chapter 3

Detail Design and Design Analysis.................... 343

Loaded Tooth Contact Analysis of Modified Helical Face Gears ................. 345 Ning Zhao, Hui Guo, Zongde Fang, Yunbo Shen, Bingyang Wei Simplified Stress Analysis of Large-scale Harbor Machine’s Wheel............ 355 Wubin Xu, Peter J Ogrodnik Bing Li, Jian Li, Shangping Li Clean-up Tool-path Generation for Multi-patch Solid Model by Searching Approach..................................................................................... 365 Ming Luo, Dinghua Zhang, Baohai Wu, Shan Li Fatigue Life Study of Bogie Framework Welding Seam by Finite Element Analysis Method ................................................................. 375 Pingqing Fan, Xintian Liu, Bo Zhao Research on Kinematics Based on Dual Quaternion for Five-axis Milling Machine .......................................................................... 385 Rui-Feng Guo, Pei-Nan Li

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Contents

Consideration for Galvanic Coupling of Various Stainless Steels & Titanium, During Application in Water-LiBr Absorption-Type Refrigeration System......................................................................................... 395 Muhammad Shahid Khan, Saad Jawed Malik Real Root Isolation Arithmetic to Parallel Mechanism Synthesis................. 405 Youxin Luo, Dazhi Li, Xianfeng Fan, Lingfang Li, Degang Liao Experimental Measurements for Moisture Permeations and Thermal Resistances of Cyclo Olefin Copolymer Substrates ........................................ 415 Rong-Yuan Jou Novel Generalized Compatibility Plate Elements Based on Quadrilateral Area Coordinates ...................................................................... 425 Qiang Liu, Lan Kang, Feng Ruan Individual Foot Shape Modeling from 2D Dimensions Based on Template and FFD............................................................................................. 437 Bin Liu, Ning Shangguan, Jun-yi Lin, Kai-yong Jiang Application of the TRIZ to Circular Saw Blade ............................................. 447 Tao Yao, Guolin Duan, Jin Cai

Chapter 4

Simulation and Optimisation in Design............ 457

Research on Collaborative Simulation Platform for Mechanical Product Design................................................................................................... 459 Zhaoxia He, Geng Liu, Haiwei Wang, Xiaohui Yang Development of a Visualized Modeling and Simulation Environment for Multi-domain Physical Systems ................................................................. 469 Y.L. Tian, Y.H. Yan, R. M. Parkin, M. R. Jackson Selection of a Simulation Approach for Saturation Diving Decompression Chamber Control and Monitoring System...................................................... 479 Diming Yang, Xiu-Tian Yanand Derek Clarke Optimal Design of Delaminated Composite Plates for Maximum Buckling Load.................................................................................................... 489 Yu Hua Lin Modeling Tetrapods Robot and Advancement ............................................... 499 Q. J. Duan , J. R. Zhang, Run-Xiao Wang, J. Li The Analysis of Compression About the Anomalistic Paper Honeycomb Core ............................................................................................... 509 Wen-qin Xu, Yuan-jun Lv, Qiong Chen, Ying-da Sun C-NSGA-II-MOPSO: An Effective Multi-objective Optimizer for Engineering Design Problems .................................................................... 519 Jinhua Wang, Zeyong Yin

Contents xvii

Material Selection and Sheet Metal Forming Simulation of Aluminium Alloy Engine Hood Panel ......................................................... 529 Jiqing Chen, Fengchong Lan, Jinlun Wang & Yuchao Wang Studies on Fast Pareto Genetic Algorithm Based on Fast Fitness Identification and External Population Updating Scheme ............................ 539 Qingsheng Xie, Shaobo Li, Guanci Yang Vibration Control Simulation of Offshore Platforms Based on Matlab and ANSYS Program ........................................................................................ 549 Dongmei Cai, Dong Zhao, Zhaofu Qu Study on Dynamics Analysis of Powertrains and Optimization of Coupling Stiffness ......................................................................................... 561 Wenjie Qin, Dandan Dong Parametric Optimization of Rubber Spring of Construction Vehicle Suspension.......................................................................................................... 571 Beibei Sun, Zhihua Xu and Xiaoyang Zhang The Development of a Computer Simulation System for Mechanical Expanding Process of Cylinders....................................................................... 581 Shi-yan Zhao, Bao-feng Guo, Miao Jin Rectangle Packing Problems Solved by Using Feasible Region Method ...... 591 Pengcheng Zhang, Jinmin Wang, Yanhua Zhu Aircraft’s CAD Modeling in Multidisciplinary Design Optimization Framework......................................................................................................... 601 X.L. Ji, Chao Sun Optimization of Box Type Girder of Overhead Crane .................................. 609 Muhammad Abid, Muhammad Hammad Akmal, Shahid Parvez

Chapter 5 New Mechanism and Device Design and Analysis ............................................................................... 619 Symmetric Toggle-lever-toggle 3-stage Force Amplifying Mechanism and Its Applications........................................................................................... 621 Dongning Su, Kangmin Zhong, Guoping Li Kinematics and Statics Analysis for Power Flow Planet Gear Trains.......... 631 Zhonghong Bu, Geng Liu, Liyan Wu, Zengmin Liu Green Clamping Devices Based on Pneumatic-mechanical Compound Transmission Systems Instead of Hydraulic Transmission Systems............. 641 Guang-ju Si, Ming-di Wang, Kang-min Zhong, Dong-ning Su Rapid Registration for 3D Data with Overlapping Range Based on Human Computer Interaction .................................................................... 651 Jun-yi Lin, Kai-yong Jiang, Bin Liu, Chang-biao Huang

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A New FE Modelling Approach to Spot Welding Joints of Automotive Panels and Modal Characteristics .......................................... 661 Jiqing Chen, Yunjiao Zhou and Fengchong Lan Precision Measurement and Reverse Motion Design of the Follower for Spatial Cams ................................................................................................ 671 Zhenghao Ge, Jingyang Li, Feng Xu, Xiaowei Han Static Analysis of Translational 3-UPU Parallel Mechanism Based on Principle of Virtual Work............................................................................ 681 Xiangzhou Zheng, Zhiyong Deng, Yougao Luo, Hongzan Bin A Natural Frequency Variable Magnetic Dynamic Absorber....................... 691 Chengjun Bai, Fangzhen Song

Chapter 6

Manufacturing Systems Design......................... 699

Next Generation Manufacturing Systems ....................................................... 701 R.H. Weston and Z. Cui Tooling Design and Fatigue Life Evaluation via CAE Simulation for Metal Forming ............................................................................................. 711 W.L. Chan, M.W. Fu, J. Lu Modelling of Processing Velocity in Computer-controlled Sub-aperture Pad Manufacturing.................................................................... 721 H. Cheng, Y.Yeung, H. Tong, Y. Wang Load Balancing Task Allocation of Collaborative Workshops Based on Immune Algorithm....................................................................................... 729 XiaoYi Yu, ShuDong Sun Study on Reconfigurable CNC System ............................................................ 743 Jing Bai, Xiansheng Qin, Wendan Wang, Zhanxi Wang Development of a NC Tape Winding Machine ............................................... 753 Yao-Yao Shi, Hong Tang, Qiang Yu TRIZ-based Evolution Study for Modular Fixture ........................................ 763 Jin Cai , Hongxun Liu , Guolin Duan , Tao Yao , Xuebin Chen Study on the Application of ABC System in the Refinery Industry.............. 773 Chunhe Wang, Linhai Shan, Ling Zhou, Guoliang Zhang The Application of Activity-Based Cost Restore in the Refinery Industry .. 783 Xingdong Liu, Ling Zhou, Linhai Shan, Fenghua Zhang, Qiao Lin Research on the Cost Distribution Proportionality of Refinery Units .......... 793 Fen Zhang, Yanbo Sun, Chunhe Wang, Xinglin Han, Qiusheng Wei

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Chapter 7 Collaborative and Creative Product Development and Manufacture.................................................. 803 From a 3D Point Cloud to a Real CAD Model of Mechanical Parts, a Product Knowledge Based Approach ........................................................... 805 A. Durupt, S. Remy, W. Derigent Research on Collaborative Design Support System for Ship Product Modelling .............................................................................. 815 Yiting Zhan, Zhuoshang Ji, Ming Chen Research on New Product Development Planning and Strategy Based on TRIZ Evolution Theory ............................................................................... 825 Fuying Zhang, Xiaobin Shen, Qingping He ASP-based Collaborative Networked Manufacturing Service Platform for SMEs............................................................................................................. 835 Y. Su, B.S. Lv, W.H. Liao, Y. Guo, X.S. Chen, H.B. Shi Virtual Part Design and Modelling for Product Design................................. 843 Bo Yang, Xiangbo Ze, Luning Liu Integrated Paper-based Sketching and Collaborative Parametric 3D Modelling...................................................................................................... 855 Franklin Balzan, Philip J. Farrugia, Jonathan C.Borg Mechanical System Collaborative Simulation Environment for Product Design............................................................................................. 865 Haiwei Wang, Geng Liu, Xiaohui Yang, Zhaoxia He Evolution of Cooperation in an Incentive Based Business Game Environment ...................................................................................................... 875 Sanat Kumar Bista, Keshav P. Dahal, Peter I. Cowling Author Index...................................................................................................... 883

Chapter 1 Front End of Engineering Design

Computer Aided Design: An Early Shape Synthesis System............................. 3 Alison McKay, Iestyn Jowers,Hau Hing Chau, Alan de Pennington, David C Hogg Constraints and Shortfalls in Engineering Design Practice............................. 13 Lars Hein, Zhun Fan Modular Product Family Development Within a SME.................................... 21 Barry Stewart, Xiu-Tian Yan Duality-based Transformation of Representation from Behaviour to Structure .............................................................................. 31 Yuemin Hou , Linhong Ji Automatic Adaptive Triangulation of Surfaces in Parametric Space............. 41 Baohai Wu, Shan Li, Dinghua Zhang Research on Modeling Free-form Curved Surface Technology ...................... 51 Gui Chun Ma , Fu Jia Wu, Shu Sheng Zhang Pattern System Design Method in Product Development ................................ 61 Juqun Wang, Geng Liu, Haiwei Wang Development of a Support System for Customer Requirement Capture ....... 71 Atikah Haji Awang, Xiu-Tian Yan Comparison About Design Methods of Tonpilz Type Transducer ................. 81 Duo Teng , Hang Chen, Ning Zhu, Guolei Zhu, Yanni Gou Effect for Functional Design............................................................................... 91 Guozhong Cao, Haixia Guo, Runhua Tan Quality Control of Artistic Scenes in Processes of Design and Development of Digital-Game Products................................................... 103 P.S. Pa, Tzu-Pin Su

Computer Aided Design: An Early Shape Synthesis System Alison McKay, Iestyn Jowers, Hau Hing Chau, Alan de Pennington, David C Hogg University of Leeds, Leeds, LS2 9JT, UK

Abstract Today’s computer aided design systems enable the creation of digital product definitions that are widely used throughout the design process, for example in analysis or manufacturing. Typically, such product definitions are created after the bulk of [shape] designing has been completed because their creation requires a detailed knowledge of the shape that is to be defined. Consequently, there is a gulf between the exploration processes that result in the selection of a design concept and the creation of its definition. In order to address this distinction, between design exploration and product definition, understanding of how designers create and manipulate shapes is necessary. The research outlined in this paper results from work concerned with addressing these issues, with the long term goal of informing a new generation of computer aided design systems which support design exploration as well as the production of product definitions. This research is based on the shape grammar formalism. Shape grammars have been applied in a range of domains, commonly to generate shapes or designs that conform to a given style. However, a key challenge that restricts the implementation of shape grammar systems lies in the detection of embedded parts, or sub-shapes, which are manipulated according to shape rules to create new shapes. The automatic detection of sub-shapes is an open research question within the shape grammar community and has been actively explored for over thirty years. The research reported in this paper explores the use of computer vision techniques to address this problem; the results achieved to date show real promise. An early prototype is presented and demonstrated on design sketches of martini glasses taken from a student research project. Keywords: shape synthesis, shape grammar, computer vision, sub-shape detection

1.

Introduction

Currently available computer aided design systems enable the creation of digital product definitions that are widely used throughout the design process, for example in analysis or manufacturing. Typically, such product definitions are created after the bulk of [shape] designing has been completed because their creation requires a detailed knowledge of the shape that is to be defined. Consequently, there is a gulf

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A. McKay, I. Jowers, H. H. Chau, A. de Pennington and D. C. Hogg

between the exploration processes that result in the selection of a design concept and the creation of its definition. In order to address this distinction between design exploration and product definition, understanding of how designers create and manipulate shapes is necessary [1]. The research outlined in this paper is concerned with addressing these issues, with the long term goal of informing a new generation of computer aided design systems which support design exploration as well as the production of product definitions. This paper reports on developments towards an automated shape synthesis system intended to augment the generation of design shapes early in the product development process. The system is based on the shape grammar formalism.

2.

Background

Shape grammars are a formal production system where languages of shapes or designs are generated according to shape replacement rules. Their mathematical formalism enables shapes to be manipluated according to their visual stucture, rather than according to underlying representations. As a result, designers are free to manipulate formal descriptions of their designs in a manner that reflects the interactive freedom often associated with sketching [1]. When a designer manipulates parts of a design, emergent patterns and associations can be discovered which suggest new features and relations. Shape rules provide a formal mechanism whereby the structure of the design can be reinterpreted according to these emergent patterns, which can then be recognised and manipulated [2]. Such reinterpretation is a vital element in the exploration of designs and is believed to be a decisive component of innovative design [3]. Since their conception, shape grammars have been applied in a variety of disciplines including art and design, architecture, and product design.The majority of these applications have used shape grammars as a formal approach to the analysis of styles and the generation and exploration of design families. Chau et al [4] provide a comprehensive timeline of research in the application of shape grammars. (reproduced in Figure 1). These have demonstrated the viability of generative techniques to capture and reproduce styles in a range of design domains.

Computer Aided Design: An Early Shape Synthesis System

5

Figure 1. Shape grammar applications to designs

The basic elements of a shape grammar include an initial shape (that seeds shape generation) and a set of shape replacement rules, as illustrated in Figure 2. In this example, two shape replacement rules are defined and the initial shape is a square. The first rule replaces a square with a shape consisting of a square and an overlapping rectangle, whilst the second rule replaces a rectangle with a shape consisting of a rectangle and an abutting square. The shapes at the bottom of the figure show a fragment of the network of shapes that can be generated from the initial shape via application of the two shape rules.

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Initial shape

Rule 2

Rule 1

1 1

1

2

1

2 2

Figure 2. A simple two rule grammar

Application of a shape rule involves two key steps. Firstly, the shape on the lefthand side of a rule must be identified embedded under some Euclidean transformation in the shape from which a new shape is to be computed; this is referred to as “sub-shape detection”. This detection is not restricted to recognising sub-shapes according to the structure that initially defines the shapes, but can be applied to any sub-shapes, even if these sub-shapes emerge as a result of previous rule applications. Secondly, the rule is applied by replacing the sub-shape from the left-hand side of the rule with the shape on the right-hand side of the rule, under the defined Euclidean transformation. A key benefit that results from defining a shape grammar is that it becomes possible to generate large networks of shapes, or design families, where multiple avenues of shape synthesis can be explored by designers. The size of the potential shape networks is vast and sometimes indefinite. An example using the initial shape and rules from Figure 2 is given in Figure 3. At each step, a selection of designs is generated and presented, from which one design is chosen (highlighted in red) which is used to seed further shape generation.

Computer Aided Design: An Early Shape Synthesis System

7

1

2 2

1 1

1

2

1

1

2

KEY 2

The shape from which subsequent shapes are to be computed

Rule that will be applied.

The shapes computed from the selected shape using the given rule.

Figure 3. A network of shapes computed from the two rule grammar in Figure 2

Significant efforts have been directed towards creating systems for automating the application of shape grammars, in order to realise what Smyth and Wallace [5] refer to as a “form synthesis engine” within their model for the synthesis of aesthetic product form. Some progress has been made towards this goal. However a key challenge that restricts such shape grammar implementations lies in the detection of embedded sub-shapes. For example, Chau et al. [4] describe a 3D shape grammar implementation for curvilinear shapes. Once a sub-shape has been detected, this system can automatically apply a rule. However, sub-shapes have to be identified manually (unless they conform to a particular class of shapes consisting of straight lines and circular arcs). Other significant developments have been presented by Tapia [6] who demonstrated a robust implementation for shapes composed of straight lines in 2D and Jowers [7] who reports success with shapes composed of 2D Bezier curves. In these works analytical solutions to the subshape detection problem are presented and shape grammar implementations are described. However, these analytical solutions have a number of limitations, some of which will be discussed in the next section. Instead, this paper reports an alternative approach to sub-shape detection based on the application of approaches that have been established in the computer vision community. Computer vision is concerned with building systems that obtain information from images, and research in this field has resulted in a range of techniques that enable the identification of shapes in real-world situations. For example, statistical learning algorithms have been used for modelling and recognizing new object categories [8, 9]. In contrast to analytic approaches, which search for sub-shapes in

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the mathematical representation of a shape, the method used in this research looks for sub-shapes in visual objects derived from a shape’s mathematical representation. This paper reports early results of an exploration of the application of the techniques used for the recognition of visual objects to sub-shape detection in shape grammar-based design systems.

3. A Computer Vision Based Approach to Sub-shape Detection Previous approaches that have been used to address the sub-shape detection problem have relied on analytical methods to automatically match sub-shapes under transformation. As a result, a number of difficulties have arisen that severely limit the capabilities of the computational systems built upon these approaches. A key premise in the application of shape grammars lies in the fact that the shape to which a rule might be applied, and so in which sub-shapes are to be detected, is a visual entity that is the result of a shape definition process rather than the shape definition itself. When humans search for a sub-shape, visual similarity implies equality whereas when analytical techniques carry out the same process visual similarity does not necessarily imply equality. For example, the two curve segments highlighted in Figure 4 are visually similar but analytically they are distinct because they are segments of infinite curves which are mathematically distinct (as illustrated by the extended curves).

Figure 4. Visually similar curves that are mathematically distinct

Further difficulties result from the dependency of analytical approaches on the formal structures used to represent shapes. These formal structures restrict the general applicability of sub-shape detection algorithms which are suitable only for particular classes of shapes. For example, Tapia’s system addressed the sub-shape detection problem for shapes composed of 2D lines, but the analytical solution employed cannot be readily extended to the freeform curves that typify consumer product designs. Also, in analytical approaches, matching of sub-shapes is achieved by embedding the sub-shape into the shape that is the subject of the search. For this reason, shapes that can be matched are restricted according to the formal structures that were used to define them, for example lines or Bezier curves,

Computer Aided Design: An Early Shape Synthesis System

9

and the embedding properties of shapes are dependent on the formal structures used to represent the shapes. To overcome these problems, the research in this paper has adopted a computer vision approach that involves comparing images in the form of bitmaps according to a distance metric. Existing applications of this approach include word spotting in Chinese document images, visual navigation of robots, merging of partially overlapping images into a single image, and computer-assisted surgery. For image matching, the algorithm used checks whether a template image (representing the sub-shape to be detected) is present in a test image; the lower the separation distance value, the better the match. If the template image is a sub-shape of the first then the distance metric has a value of zero. This metric can therefore be used to determine whether one shape can be embedded in a second. The algorithm has been implemented in an experimental software prototype, where sub-shapes are detected arbitrarily embedded in the target image by considering the distance metric under transformation: currently translation and reflection. The prototype was applied to design sketches produced by undergraduate final year Masters students in Product Design. The application of the prototype is described in the next section.

4.

An Application of Sub-shape Detection to Design Sketches

The software prototype was evaluated on martini glass designs prepared by undergraduate Masters students in Product Design in preparation for a workshop on shape computation. An example of students’ designs is given in Figure 5.

Figure 5. Example martini glass designs

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Designers’ sketches are fed into the system in the form of bitmaps. The software prototype then allows the designer to define a sub-shape to be detected by selecting it as a collection of pixels from the bitmap or by importing an alternative bitmap image. For example, in the screen images in Figure 6, sketches of martini glasses have been imported and are displayed on the left-hand side of each screen. In the top right-hand corner of the screen a stylised image of a martini glass has been imported. In this example, the system searches the image of martini sketches for sub-shapes that match the stylised martini glass image. The sub-shapes identified by the system are highlighted in red in the left-hand sides of the screen.

Figure 6. Screen images of subshape detector in operation

In the software prototype, sub-shapes can be detected under both translation and reflection transformations. Effort is currently being directed towards the implementation of more general kinds of transformation operation and on the definition and application of shape replacement rules. Early developments allow rules to be defined by creating either a new shape to act as the right-hand side or by editing or transforming the shape from the left-hand side. Rules are then applied by removing the pixels that form the left-hand side of the rule and replacing them with the pixels that form the right-hand side of the rule.

Computer Aided Design: An Early Shape Synthesis System

5.

11

Concluding Remarks

The research reported in this paper indicates that there is potential in exploring further the use of computer vision techniques for sub-shape detection. Automated sub-shape detection is a key prerequisite to achieving the goal of a shape grammarbased shape synthesis system to support design synthesis activities. Our vision for how such a system might augment design activity is illustrated in Figure 7. It can be seen that there are three intertwined cycles.

The Shape Synthesis System (S3) generating shapes

The designer designing shapes

Communication between the two

Figure 7. Three interwined cycles

The designer designing shapes and the shape synthesis system computing shapes are independent of each other and joined by a third cycle of communication between the two. Information flowing from the designer to the shape synthesis system is envisioned to be in the form of commonly used design descriptions, such as sketches or, as the designing and computation of shapes proceeds, in the form of shape rules. Information flowing back to the designer will be in the form of lattices of computed shapes (as illustrated in Figure 2) that prompt and inspire the designer. We anticipate that such a system will expand the space within which design exploration occurs and so enhance design activity. A key challenge in the next stage of this research lies in the design of the user interface for communication between designers and the shape synthesis system. This interface is critical in order to ensure a fluid interaction between the designer and the designs that are currently being explored, and in order to avoid disruption to the design process.

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6.

Acknowledgements

The research reported in this paper was carried out as part of the Design Synthesis and Shape Generation project (www.engineering.leeds.ac.uk/dssg/) which is funded through the AHRC1/EPSRC2 Designing for the 21st Century programme. The example martini glass designs were reproduced with permission of Jessica Diniz who graduated with an MDes in Product Design in July 2007.

7.

References

[1] Prats, M and C.F. Earl. Exploration through drawings in the conceptual stage of product design. In 2nd International Conference on Design Computing and Cognition (DCC'06), Eindhoven. Dordrecht: Springer. 2006. p. 83-102. [2] Stiny, G., Introduction To Shape And Shape Grammars. Environment And Planning BPlanning & Design, 1980. 7(3): p. 343-351. [3] Suwa, M. Constructive perception: coordinating perception and conception toward acts of problem-finding in a creative experience. Japanese Psychological Research. 2003. 45(4): p. 221-234. [4] Chau, H.H., et al. Evaluation of a 3D shape grammar implementation. In 1st International Conference on Design Computing and Cognition (DCC'04), Cambridge, Massachusetts. Dordrecht: Kluwer. 2004. p. 357-376. [5] Smyth, S.N. and D.R. Wallace. Towards the synthesis of aesthetic product form. in ASME 2000 Design Engineering Technical Conferences and Computers and Information in Engineering Conference (DETC'00). 2000. Baltimore, Maryland. [6] Tapia, M., A visual implementation of a shape grammar system. Environment and Planning B: Planning and Design, 1999. 26: p. 59-73. [7] Jowers I. Computation with curved shapes: Towards freeform shape generation in design. PhD Thesis, The Open University, 2006 [8] Heap, A.J. and D.C. Hogg. Wormholes in Shape Space: Tracking through Discontinuous Changes in Shape. in IEEE International Conference on Computer Vision 1998, Bombay. 1998. [9] Baumberg, A. and D.C. Hogg. Learning Flexible Models from Image Sequences. in 3rd European Conference on Computer Vision, Stockholm. 1994.

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UK Arts & Humanities Research Council UK Engineering & Physical Sciences Research Council

Constraints and Shortfalls in Engineering Design Practice Lars Hein1, Zhun Fan2 1

IPU, Produktionstorvet, Building 425, DK-2800 Kgs. Lyngby, Denmark. Department of Mechanical Engineering, DTU, Nils Koppels Allé, DK-2800 Kgs. Lyngby, Denmark.

2

Abstract The effectiveness of Engineering Design in practice is what results from a multitude of processes within the realm of Engineering Design itself. However, in order to understand the phenomenon, the processes whereby Engineering Design as a discipline comes together with disciplines from other areas of the company, to sustain the product development process itself, must be taken into account. Therefore, when companies strive to obtain an attractive level of effectiveness of their engineering design activities, the product development process as a whole must be considered. In this paper the first step in an approach by which to optimize the product development process of a company is suggested. This approach makes it possible to arrive at specific conclusions about the constraints and shortfalls of the engineering design activities in a product development context. Keywords: Industry, Constraints, Product Development, Engineering Design, Effectiveness.

1.

Engineering Design and the Product Development Core

The role of Engineering Design in the innovation processes of a company is a central one. Therefore its effectiveness is of great concern not only to the companies that deals with such processes, but also to those that do research into, and teach within the field of, engineering design. However, trying to understand its effectiveness from a purely internal analysis of the engineering design processes and activities leads to an unsatisfactory and incomplete picture. An input/output analysis of the Engineering Design Department of a company yields only the most superficial result which it is almost impossible to relate to the overall success of the company. This is fair warning that any attempt to optimize the processes of engineering design on the basis of an internal analysis will lead to suboptimization (fig.1).

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Figure 1. The Product Development Core (PDC) of a company is where innovation and product development takes place. The PDC of the company has many contributors, not only those formally associated with development such as Engineering Design and Industrial Design.

Some approaches in the research into effectiveness in engineering design deals with relevant engineering design tools and methods, and with the extent to which they are being used in industrial context, some work reporting a low rate of use of the more complex tools [2]. However, what carries the effectiveness of the engineering design and product development processes is more than tools and methods. Generally, at least seven dimensions of the product development core must be considered in order to come to an satisfactory understanding: the organisational structure, the physical environment, the performance measuring system, the knowledge structure, methods & tools, the social system, and the decision structure (fig.2).

Figure 2. The seven dimensions of the Product Development system [adapted from 1].

2.

Constraints and Shortfalls

That the quest to understand the constraints and shortfall of engineering design and of the product development process is relevant is indicated by the frustrations that

Constraints and Shortfalls in Engineering Design Practice 15

are voiced to those who enter into a serious discussion on the subject with people from industry: x x x x x x x x

“We don’t get enough from our investments in product development” “We use too much energy dealing with our current products, and do not innovate” “Arriving at the new products takes us too long time” “We do too many new products of the 5%-improvement kind” “We have no control over our product cost” “The content of new and powerful technologies in our products is low” “Our new products fail to realize the market potential” “Our new products’ contribution to the company revenue is too weak”

The understanding in the research community of the Engineering Design processes has made remarkable progress in the last ten to twelve years [3]. Thus, there is a potential for this understanding to be utilized to reorganize and reengineer the product development organization in those companies, and to change what is basically an unsatisfactory situation. However, there is no direct relation between realizing that there is a problem, and to the cure that must be specified to actually change the company to increase the product development effectiveness, This lack of direct correlation between problems and cure is also recognized by the reported work that is being done on metrics and benchmarking of engineering design [4, 5] and metrics of product development [6, 7].

3.

The Concept of ‘A Diagnosis’

This paper put forth the hypothesis that, as a first step, a diagnosis may be made on the product development core of a company, leading to an understanding of the underlying illness, or illnesses. This approach is based on the assumption that the product development core of a company share important characteristics with those of a living organism. The approach is founded on current research based understanding of the product development processes, combined with the accumulated experience of practicing the use of the diagnostic tools and procedures in real companies. 3.1

Understanding the Current Product Development Core

It is one of the basic assumptions that an indispensable first step is to understand how the existing product development core works, before making a diagnosis. One must be able to understand the composition of the system in the seven aforementioned dimensions (fig.2), and understand how the product development tasks are related to the overall strategies and goals of the company. It is also important to gauge the ‘modus operands and attitudes of key personnel in the

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product development core, in order to understand the micro-mechanisms which are the actual generators of innovation and synthesis. 3.2

Understanding the Current Problems

It is another basic assumption that one must understand in detail where the problems lies with the current product development core, before any serious attempt at repair can be made: If we do not understand where the problems are, as a reflection of what the company in its current state is capable of, we will not succeed in creating a new and better product development core. 3.3

Seeing the Company ‘Freed from the Ties that Binds’

Before attempting the diagnosis, one must identify if and where the company has been tied down by unwittingly accepting imaginary boundaries, rules, or norms related to their product development. The diagnosis should rest upon an understanding of what product development could and should be like in the company, freed from those ties. 3.4

Understanding the Company’s Environment

Lastly, the environment in which the company must function must be understood. Important aspects of the environment is: x x x x x

4.

The market that the company addresses The customers that the company caters to Direct and indirect competition The nature of the applied technology, and the dynamics involved The context and reality of the society where the company must function

Tools for the Diagnosis

The diagnosis is supported by a number of tools, developed from our current understanding of the engineering design and product development processes. Basically, the tools are organised into three sets: Basic reference patterns, Gap analysis, and the ‘Hypotheses of malfunction’ 4.1

Five Basic Reference Patterns

The five basic reference patterns represents five different facets of product development. They are used to compare what is going on in the company with what are generally known to be healthy and productive patterns. Any major deviation from those patterns points to a potential cause of problems. Composition of the Product Development Core deals with the different organisational elements related to the core. How the contributors and stakeholders

Constraints and Shortfalls in Engineering Design Practice 17

interact is highly important to the function and effectiveness of the engineering design activities, and thus scrutiny of the corresponding patterns is essential.

Figure 3. The five basic reference patterns used in the diagnosis: Composition of the Product Development Core, the structure of the product development tasks, the set of coordinated strategies in the company, the four stages of maturity of the product development system, and the seven dimensions of the product development system.

The structure of the product development tasks deals with the mapping of the often complex pattern of development tasks that the product development core is expected to solve. Here it is important to notice that there are often tasks at both high, medium, and low level in the company, requiring very different competences and measures. A check should be made in order to confirm that the capabilities, resources, and organization are adequate to deal with the tasks with satisfactory results. The coordinated strategies in the company deals with mapping the local strategies of the most important functional areas of the company (typically areas such as Production, Service, Product Development, Quality, and Sales), and checking them for reciprocated consistency and support. The four stages of maturity of the product development system deals with the identification of how far the company has come in its lifecycle, and consequently what the role of the product development core ought to be. Basically, the four stages are: 1. Engineering design stage – the young (and small) company where product development is handled by the engineering design group alone, and where a fair share (if not all) of the commercial awareness is also located. 2. The product development stage - where the technical and the commercial competence and

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resources are found in different groups, which must then come together to do product development. 3. The product planning stage – when product development has become so complex that extensive planning and management becomes necessary. 4. The coordinated strategies stage – when further growth and complexity has made the coordination between strong and self sufficient individual departments in the company a major problem. The seven dimensions of the product development system deals with analysing how the company has combined elements from all dimensions into a total working pattern, and of how this patterns compares to the patterns generally known for their functionality, effectiveness, and reliability. Again: Any major deviation from those patterns points to a potential cause of problems. 4.2

Gap Analysis - ‘What We Believe We Are’ vs ‘What We Really Are’

In a company there may many different (and often conflicting) perceptions by people in different positions about product development - with respect to ‘who we are’, ‘what we are doing’, and ‘how we do it’. And even for all of these individual perceptions, the reality may be something different again. The goal of the gap analysis is to arrive at a realization of the gap between ‘what we believe we are’ from ‘what we really are’. 4.3

Specific Ailments – the ‘Hypotheses of Malfunction’

Maybe the most powerful set of tools for establishing the diagnosis is the stock of mechanisms notoriously known to generate constraints and shortfalls, previously identified with other companies. The relevant ‘hypotheses of malfunction’ may be selected from the amoury on the basis of the initial findings of the diagnosis, and subsequently put to the test. The proof or disproof of the individual hypotheses will often emerge from interview with key personnel directly involved in the development processes, or with stakeholders in engineering design or the product development results. Currently the stock comprises some 30 to 40 hypotheses, examples of which are: x x x x x x x

“Not enough management focus on product development.” “A lag of engineering competences in respect of the tasks to be performed.” “The role of engineering design and/or product development in the company is unclear”. “The goals set for engineering design activities are weak and unambitious”. “No link from company strategy through to the engineering design and product development activities.” “The engineering design department is tied down by old debt (= previously unfinished, but unproductive work).” “The chair of the engineering design manager (or of the product development manager) is empty.”

Constraints and Shortfalls in Engineering Design Practice 19

x x x

5.

“The handbook and the procedures for the product development process are being ignored.” “In the projects, the information related to market and customers is not forthcoming, or is weak and unsubstantiated.” “The business acumen has been stifled by bureaucracy.”

Testing the Concept, Tools and Procedures of the Diagnosis

Over a period, the concept of ‘diagnosis’ has been put to the test, and the tools and procedures described above has been tested, modified and optimized. In all, more than fifty companies, of sizes from a few hundred to many thousands employees, has had a diagnosis made either by our group, or by our cooperation partners. The companies have predominantly been manufacturing companies, with a number of service-industry companies also present. The diagnosis was being performed always by two researchers as a team, and in no instances were they themselves employed by, or affiliated with, the company. The presentation of the findings of the diagnosis to the company followed always the same pattern: The findings and conclusions was written up in a formal report, and subsequently presented to the management board - in some instances this group was supplemented by key personnel from engineering design or from the product development core. The management board then discussed the diagnosis, and, as a rule approved the findings and conclusions. The result was then communicated to all relevant staff, and the next phases, those concerned with the re-engineering of the organization, could begin. The conclusion of the test is that the diagnosis arrived at was approved by the individual company in over 90% of the cases. In more that 80% of the cases the go-ahead was given for the subsequent organization re-engineering activities.

6.

Conclusions

In order to deal with the constraints and shortfalls in engineering design practice, the processes by which Engineering Design comes together with disciplines from other areas of the company, to sustain the product development process itself, must be taken into account. The accumulated results of research into Engineering Design and product development is now adequate enough that it may provide the basis for the development of a structured process by which to reduce or remove the constraints and shortfalls in engineering design practice. However, the application and training

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of this process in real companies is required in order to adapt and make operational the suggested tools and procedures. In this paper, the first step of such a structured process, the diagnosis, is proposed. Through rigorous testing in companies in the Nordic countries, the concept of Diagnosis and the corresponding set of tools and procedures has been adapted, and been demonstrated to yield productive results. Future research should focus on the remaining steps in the process. In addition, the testing and practice of the process should be used to collect data for the subsequent generation of metrics by which to benchmark the engineering design capabilities and effectiveness of a company, to add to the data repository in this field.

7.

References

[1] Mørch L., Hein L., “The Seven Dimensions of a Development Organisation”. International Conference on Engineering Design. Proceedings of ICED90, Zürich, August 1990. Series WDK 19. [2] Yang M.C., “Design Methods, Tools, and Outcome Measures: A Survey of Practitioners”. Proceedings of the ASME 2007 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2007, September 4-7, 2007, Las Vegas, Nevada, USA [3] Bligh A., Sodhi M, “Designing the Product Development Process”. Proceedings of the ASME 2007 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2007, September 4-7, 2007, Las Vegas, Nevada, USA. [4] Acosta L.M.C., Trabasso, L.G. & Araújo, C.S., “Analysis of the Balanced Scorecard Formulation Process for Setting up Engineering Design Performance Metrics”, Proc. 14th International Conference on Engineering Design (ICED 03), the Design Society, 2003. [5] Acosta L.M.C, Araújo C.S. & Trabasso, L.G., “A Review of Product Development Performance Metrics Investigations with Emphasis on the Designer Level”, Proceedings Design 2002, Dubrovnik, Croatia, 2002, pp 621-626 [6] O’Donnell F.J. & Duffy A.H.B., “Modeling design development performance”, Int. Journal of Operations & Production Management, Vol. 22, No. 11, 2002. [7] Driva H., Pawar K. & Menon U., "A framework for product development performance metrics", Int. Journal Business Performance Management, Vol.1.No.3, 1999, pp. 312326.

Modular Product Family Development Within a SME Barry Stewart, Xiu-Tian Yan The University of Strathclyde, Department of Design, Manufacturing and Engineering Management, Glasgow UK.

Abstract Product variation is becoming an important factor in companies’ ability to accurately meet customer requirements. Ever increasing consumer options mean that customers have more choice than ever before which puts commercial pressures on companies to continue to diversify. This can be a particular problem within Small to Medium Enterprises (SMEs) who do not always have the level resources to meet these requirements. As such, methods are required that provide means for companies to be able to produce a wide range of products at the lowest cost and shortest time. This paper details a new modular product design methodology that provides a focus on developing modular product families. The methodology’s function is described and a case study detailed of how it was used within a SME to define the company’s product portfolio and create a new Generic Product Function Structure from which a new family of product variants can be developed. The methodology lends itself to modular re-use which has the potential to support rapid development and configuration of product variants. Keywords: Modules, Methodology, Product Family, SME

1.

Introduction

In today’s world of high paced change and ever increasing consumer options, it is often vital for companies to diversify their product ranges to meet customers changing needs. To keep up with such strains and to help handle the subsequent complexity of the design process companies have to find new and innovative ways of managing their product development. These factors are particularly relevant within Small to Medium Enterprises (SMEs) where lack of time and resources and competitive market environments mean that constant pressures are put on companies to grow. Modularity is a concept that is being introduced as a means to meet some of these complexities and help in introducing a greater variety of products to the market in shorter times[1]. The heart of research into product modularity is the development of modular products, therefore, methods for developing more modular products are essential [2]. There has been much research carried out into modular design methods [3] with many different techniques and methodologies proposed to help companies create ‘modular’ products. The benefits of such formal tasks are well documented

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with reported cost savings of up to 64 times [4] and studies showing that by implementing formal methods, as opposed to relying on designers’ natural instincts, significant savings in time and resources can be achieved [5]. One such piece of work has been detailed in previous research [6,7,8] is called the GeMoCURE methodology which proposes a modular design methodology that also takes into account product perspectives, lifecycle objectives, modular re-use and product families. One way to meet the requirement of increasing customer requirements is to introduce product families into a company’s product portfolio. A product family is generally considered to be a group of similar products that are all derived from a common product platform [9]. In order to use such a concept to help companies create product variety, these platforms have to be well defined and implemented which is one of the goals of the GeMoCURE methodology. It aims to do this by creating a structure of well defined modules that can either be combined to form a product platform or added to the platform to generate new products. The methodology uses techniques that allow modules to be formed based on product functions and which takes into account the different perspectives that are inherent within any product development. Modularity is ideally suited to the concept of design for reuse i.e. reusing standard, proven components/assemblies/modules in the design of new products. This has the benefit of making a product more reliable (due to use of proven modules), cheaper due to reduced resources necessary for development (since a larger proportion of modules designed by others are used), easy to maintain, etc [10]. The overall objective of the design methodology is to create the greatest product variation while keeping costs, time and resources to a minimum. This paper will examine how the methodology was implemented within a SME, how it is being used and future objectives.

2.

Modular Product Families

The term module is used widely in many different contexts to describe a variety of different concepts. In the realm of product design, Gershenson et al [3] state that there is no universally agreed definition for a what a module comprises of. Ulrich and Eppinger [11] put forward the notion that ideal modules are ‘chunks’ of components where each ‘chunk’ represents one function or a series of functions. This definition is backed up by Stone et al [12] who states that “ Modules are defined as physical structures that have a one-to-one correspondence with functional structures”. It is possible to summarise from these definitions and from other prominent research [12,13,14] that the main features that define a module are; structural independence, functional independence and minimal interfaces or interactions with other modules or outside influences. The definition that has formed the foundation for the GeMoCURE methodology is built on these key points and is defined by Smith and Duffy [14] who state that “Modules are commonly described as a group of ‘functionally’ or ‘structurally’ independent components clustered such that ‘interactions are localized within each module and interactions between modules are minimised’ [16]”.

Modular Product Family Development Within a SME

23

Modularisation of products can lead to a wide range of different products but one of the uses where modularisation can be most effective is in conjunction with a common product platform. The increasingly more specific demands of customers has led to many companies introducing large product families to try an meet this wide range of needs and variety. An efficient and effective approach is to build product families based on a common product platform which allows for the accurate management of product variety [17]. Schellhammer and Karandikar [18] define such a product platform as “…the common basis for multiple product variants targeted to meet specialised requirements for specific applications and markets.” This proposes the idea that a product platform is a common base upon which modules can be added to create a wide variety of products. This type of product architecture lends itself to modular design as it allows modules to be interchanged and reused to create the maximum range of products from the components available. This is supported by Robertson and Ulrich [19] who state that “The platform concept is characterised by the consequent modularisation of a product architecture and the integration of basic (common) elements (components, functions, interfaces, design rules) over a product family.” Schellhammer and Karandikar [18] also define the platform further by declaring that they consider the “product platform to represent a set of functions, features, parameters, components, and information around which a product architecture to base a family of products and technologies can be developed.” This shows that a product platform doesn't necessarily have to consist of purely physical modules/components and can also contain the underlying technology, the product functions and or even knowledge associated with the product family. In this study, the focused company has a goal of creating a new product family that will feature a standard product platform from which a variety of new products can be developed. In addition, the current products will be structured into a well defined product families from which common modules can be found that can be stored as potential candidates for re-use in the new family.

3.

GeMoCURE Methodology

The GeMoCURE methodology is developed as an integrated approach by combining several methods to allow designers to generate design solutions using modular concepts in a systematic manner. This new methodology contains four significant methods that form the integrated methodology; Generalisation, Modularisation, CUstomisation and REconfiguration (GeMoCURE). Figure 1 shows a detailed pictorial representation of the methodology, illustrating all detailed activities and the prescribed sequence of utilising GeMoCURE in a design and manufacturing company. The following sections detail the key process and constituent activities of the GeMoCURE methodology.

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3.1

Generalisation

The first stage of this new methodology is called the ‘Generalisation’ stage and it focuses on analysing the current company product portfolio (and any new products being added) and creating generalised and generic product development primitives (PDP). This generalisation can be undertaken from two perspectives based on the work reported in [6, 19], namely, function, and structure. Function describes the physical effect imposed on an energy, material and information flow by a design entity without regard for the working principles or physical solutions used to accomplish this effect. Structure is the most tangible concept with various approaches to partitioning structure into meaningful constituents such as features and interfaces in addition to the widely used assemblies and components. Additional perspectives, such as behaviour, solution and life-cycle can also be used to generalise modules. The output from this stage is a series of PDP models from two perspectives that provide generic artefact information and knowledge for each PDP. The methodology has been simplified slightly over previous applications to reflect the nature of the SME business and the complexity of the product portfolio.

Figure 1. The GeMoCURE design methodology

3.2

Modularisation

The modularisation processes are at the heart of the GeMoCURE methodology as they help to define the product families, product platforms and the derivable modules that will help to generate product variety. There are two aspects which

Modular Product Family Development Within a SME

25

have been considered in this approach, namely identification of generic modules and identification of distinctive modules, which focuses more on deriving modules which give unique features and characteristics for the product. The PDPs that were defined in the Generalisation stage are organised into an optimal product structure using a Dependency Structure Matrix (DSM) which uses a genetic algorithm – based on the dependencies between PDPs – to cluster the PDPs into module candidates, see Figure 2. Based on the module definition given in section 1.2, functional modules can be identified by assessing the clusters of components using the Module Identification Module (MIM). This gives a visual display– see Figure 2 – of the strength of the dependencies between PDPs and allows for decisions on what makes the best module to be made. From these results the DSM is then used again to map the modular structure from the functional viewpoint to the structural viewpoint. This is called a Crossviewpoint matrix and allows for the optimal product structure to be maintained throughout the product architecture. The structural concepts can then be stored into a solution depository where they are accurately mapped and searchable so that new products have access to them with the option of modular re-use. The function concepts are also brought together at this point and used to define the product families – more detail on this can be found in section 1.4. Therefore the two main outputs from the generalisation stage are a depository of identified structural concepts and a well defined set of product families that describe the company’s product portfolio.

(a)

(b)

Figure 2. (a) A Dependency Structure Matrix; (b) the Module Identification Module (MIM)

3.3

Customisation

The Customisation stage of the process deals with the development of new products within a product family. It is a process of utilising the available modules, which were identified in the Generalisation stage, to meet a new design requirement by firstly defining the new requirement in the correct terms and then tailoring the modules to meet the requirement. The same Generalisation and DSM

26

B. Stewart and X. T. Yan

techniques are used to describe the new product concept in the same terms as the product family and modules that are in the depository. By comparing the functional concepts and the solution concepts it is possible to generate solutions for the new product. If there are no solutions for certain of the new product functions then these should be designed to integrate with the chosen module solutions and, once properly defined, can be added into the depository and product family. 3.4

Reconfiguration

Once all the modules have been selected, so that they accurately map the function structure and customer requirements, the final stage of the process is carried out. Reconfiguration takes all the modules and configures them into various product layouts while taking into account design processes, markets, standards, interfaces, etc. The output from this short stage will be the final product design ready for production.

4.

SME Product Family Analysis

The GeMoCURE methodology has been implemented, in various forms, within large mulinational companies, but the focus of this research is how it can be implemented within a local Scottish SME. The SME in question is a manufacturer of chain oiling systems that are marketed as after-market maintenance devices. They have a small product portfolio of around 8 products but are keen to expand this by introducing a new product family. The GeMoCURE methodology was implemented into this company with the purpose of introducing modularity concepts that can be used in the design of product families and in module re-use. The steps highlighted in section 1.3 and in Figure 1 were carried out on the SMEs product portfolio to firstly identify the functional modules and the structural modules. To identify functions and perspective dependencies, the functional model proposed by Stone et al[12] was created for each product variant. For the structural concepts a simple structural hierarchy was developed that showed the main structural components and their physical links. These were then added into the DSM matrix and optimised to produce optimal module structures. The functional modules were then mapped onto the structural concepts, using a crossviewpoint matrix, to create a set of solutions for structural modules. The functional modules are then taken and analysed to assess the commonality that existed between them and their products. For each product family they are then split into three distinct categories; common functions, differentiation enable (DE) functions and auxiliary functions. Common functions describes those that are present within all product variations within a family (i.e. comprise the product platform), DE functions describe functions that are selectable and can be used to alter the performance or features of the product platform and auxiliary functions are those that don’t affect he main function or product variants but provide some secondary function. Once these have been identified they can be arranged into a schematic Generic Product Function Structure (GFPS) for the product family which shows all of the

Modular Product Family Development Within a SME

27

options available for product variants within that family – see Figure 3. This structure not only defines the product family but shows all the available configurations therefore opening up the possibility of rapid configuration of new product variants.

Figure 3. An example of a Generic Product Function Structure (GPFS).from a SME

5.

Product Customisation / Configuration

In order to maintain the product portfolio structure, new product development has to follow the steps of the methodology to enable the product to be defined in terms that will allow the product variations to be generated. When a new customer requirement is identified the first step is to carry out the Generalisation of the concepts for the new product. This will define the product in terms of it functions and allow for the inputs to be put into the DSM for the Modularisation stage. By modularising the function concepts the product can now be optimised into a modular function structure that can be used in the Customisation. Once the new concept has been defined in this way a function module comparison can be carried out by searching the GFPS of the product families and the Solution depository. The modules that find matches can then be allocated into the new product scheme while for any functions that don’t have suitable matches a new design will have to be developed. When these new modules are developed it is necessary to keep to the optimal modular structure that was defined as closely as possible. Once all modules – both new and re-used – have been defined it is possible to create a new GPFS for the new product family. Figure 4 shows how the GPFS for the new SME product family is constructed of both new modules and of re-used modules from other product families. By creating the product family in this manner it is possible to use the modules already used within the company in the new product family to allow for several product variants to be produced and to add to the company’s overall product portfolio. The fact that so many of the modules

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B. Stewart and X. T. Yan

are proven, reliable modules that are already in full scale production allows for rapid configuration of these new variants and fast time to market.

Figure 4. The new Generic Product Family Function Structure (GPFS) highlighting the new modules to be developed.

6.

Interface Analysis

When carrying out modular design - with a view to creating product families and with using design for re-use principles – it is necessary to create good definitions of how the modules interact with one another. It is especcially important to have well defined and standardised interfaces between the common modules (the product platform) and the derivable modules [21]. Sellgren and Andersson[22] define an interface as a “pair of mating faces between two elements”. In this case this can be expanded to mean the pair of mating faces between two modules. In order to cope with the variety of different products they may end up in, the interfaces on modules have to be designed robustly and should preferably be defined early in the design process [23]. The importance of defining the interfaces within modules is clear and this has been particularly evident within this SME. When modules are designed to work over several product variants and several product families it is important that there are definitions set down as to how these should be handled. In the methodology an initial stage has been added called ‘Interface Identification’. The purpose of this stage is to look at both the functional and structural modules and assess the interactions between other modules. In the current company portfolio this is a simple task as the designs are in place and products are in manufacture. Therefore it is simply a case of documenting these and adding them into the depository. By also including interfaces in the modules definitions it gives a better idea of how the modules can actually fit together. It is also critical when designing new function modules, as it is imperative that any new modules that are produced are compatible

Modular Product Family Development Within a SME

29

with the product family. This way when the re-used modules have been defined there will be a definitive list of the interfaces that are present and it will be possible to design new modules to integrate with the product platform.

7.

Future Work and Conclusions

The focus of the research so far has been implementing the system within a SME and observing how it handles such an environment. This has shown some clear areas that are required to be improved in the system. The first area is the identification of commonality with the function modules and structural modules as at present this is done intuitively by the designers. There is work being carried out in parallel with this project looking at introducing algorithms into these stages to ensure that the identification is carried out optimally. The second area is the implementation of a more formal interface strategy within the methodology. It has been realised how important this is to the overall feasibility of a module re-use strategy and this will be the focus of future research. The primary aim will be to establish standard interface descriptions and allow these to be modelled into the methodology along with the crucial interface attributes. This paper has demonstrated a new design methodology aimed at aiding designers in producing modular products and families. By using a series of tools and methods a systematic approach to modular design can be achieved that allows for opportunities for module re-use and rapid product configuration which can lead to reduced product lead times and lower development costs. The methodology consists of four distinct stages; Generalisation, Modularisation, Customisation and Reconfiguration. These four stages were described and shown how the system uses a DSM tool to find the optimal product structure. This structure was then used to sort the company’s products into a range of useable modules and a definition of their product families. The system can also be used to create new product variants from these product families by using a system of differentiable modules that can be altered and added to product platforms to create variants. One of the main outcomes of the implementation of this methodology has been the need for a standardised system of interfaces to allow for effective module re-use. If modules are to be used in many different product variants it is essential that a standard system of interfaces is devised that will allow for this to be carried out efficiently. This has been pinpointed as a key topic for future work and will be built upon within the methodology to introduce a standard set of interfaces.

8.

References

[1] Baxter D, Gao J, Case K, Harding J, Young B, Cochrane S, Dani S; (2007) An engineering design knowledge reuse methodology using process modeling. Research in Engineering Design 18:37-48. [2] Thyssen J. and Hansen P.K. (2001) Impacts for Modularisation, Proceedings of International Conference on Engineering Design, ICED ’01, Glasgow, 547-554.

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[3] Gershenson J.K., Prasad G.J. and Zhang Y. (2004) Product modularity: measures and design methods. Journal of Engineering Design, 15:33-51. [4] Synopsys Inc. Who can afford a $193 Million Chip? (1999) Synopsys Design Reuse Cost Model. [5] Duffy A.H.B. and Ferns A.F. (1999) An Analysis of Design Reuse Benefits, Proceedings of the International Conference on Engineering Design, ICED ’99, Munich. [6] Smith J.S. (2002) Multi-Viewpoint Modular Design Methodology, Doctoral Thesis, University of Strathclyde, Glasgow. [7] Yan X.T., Stewart B., Wang W., Tramscheck R., Liggat J., Duffy A.H.B., Whitfield I., (2007) Proceedings of International Design Conference on Engineering Design, ICED ’07, Paris. [8] Wang W.D., Qin X.S., Yan X.T., Tong S.R., Sha Q.Y. (2007) Developing a Systematic Method for Constructing the Function Platform of Product Family,??? [9] Jiao J.X., Simpson T. W., Siddique Z. (2006), Product Family Design and PlatformBased Product Development: A State-of-the-Art Review, Special Issue on Product Family Design and Platform-Based Product Development, Journal of Intelligent Manufacturing, pp.1-36. [10] Pahl G. and Beitz P (1994) Engineering Design: A Systematic Approach, (SpringerVerlag Berlin and Heidelberg GmbH & Co). [11] Ulrich K.T. and Eppinger S.D. (2003) Product Design and Development, Third Edition (McGraw Hill). [12] Stone R., Wood K. and Crawford R. (2000) A Heuristic method for identifying modules for product architectures. Design Studies 21:5-31. [13] Gershenson J.K., Prasad G.J., Zhang Y. (2003) Product Modularity: definitions and benefits. Journal of Engineering Design, 14 : 295-313. [14] Smith J.S, Duffy A.H.B. (2001) Modularity in Support of Design for Re-Use, Proceedings of International Conference on Engineering Design, ICED ’01, Glasgow, 195-206 [15] Huang C., Kusiak A. (1998) Modularity in Design of Products and Systems, IEEE Transactions on systems, man and cybernetics, 28:66-77. [16] Sosale S., Hashiemian M. and Gu P. (1997) Product Modularisation for Re-use and Recycling, ASME, Design Engineering Division, 94:195-206. [17] Hofer A.P., Gruenenfelder M. (2001) Product Family Management Based on Platform Concepts, Proceeding of International Conference on Engineering Design, Glasgow, 491-498. [18] Schellhammer W., Karandikar H. (2001) Metrics for Executing a Product Platform Strategy, Proceeding of International Conference on Engineering Design, Glasgow, 531-538. [19] Wie M. V., Bryant C., Bohm M. R., Mcadams D. A., Stone R. B. (2005) A Model of Functional-Based Representation. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 19:89-111. [20] Robertson, D., Ulrich, K. (1998) Planning for Product Platforms, Sloan Management Review. [21] Sundgren N. (1999) Introducing Interface Management in New Product Family Development, Journal of Product Innovation Management, 16:40-51. [22] Sellgren, U., Andersson, K. (1998) MOSAIC - a Framework and a Methodology for Behavior Modeling of Complex Systems, Proceeding of Produktmodeller’98, 119-137. [23] Blackenfelt M., Sellgren U. (2000), Design of Robust Interfaces in Modular Products, Proceedings of 2000 ASME Design Engineering Technical Conference, Baltimore, Maryland.

Duality-based Transformation of Representation from Behaviour to Structure Yuemin Hou 1,2, Linhong Ji 2 1

Dept. of Mechanical Engineering, Beijing Information Science and Technology University, Beijing, 100085, P. R. China 2 Dept. of Precision Instrument and Metchanology, Tsinghua University, Beijing, 100084, P. R. China

Abstract Behaviour bridges function and structure. The designing process is investigated by analogy with embryo development and this approach leads to a six-stage designing process: the function specification, the behavior representation of function, the behavior induction, the behavior specification, the transformation from behavior to feature, and the parameter optimization. To map the behavior into the feature of structure is a key issue for structure development. The paper presents a bioinspired mechanism: gene transcription and a duality-based algorithem to achieve the transformation. The computational model is established and a design case is illustrated to show the method. Keywords: Behaviour, structure, transformation, duality, representation

1.

Introduction

Behaviour bridges function and structure. Functions can be described from a device-centric and/or an environment-centric viewpoint while structure is a configuration of objects[1]. Behaviors may refer to the value(s) or value relations of state variables of interest, properties of an object, and the causal rules that describe the values of the variables under various conditions[1]. In terms of design variables, function variables describe the teleology of the object; structure variables describe the components of the object and their relationships; behaviour variables describe the attributes that are derived or expected to be derived from the structure variables of the object[2]. Therefore, The transformation from behavior to structure is at the core of designing. Researches on function-structure mapping were mainly focused on operational process and computer-supported searching strategy. The typical mapping models include concept-detail design methodology[3], axiom design[4] and the FBS framework[2]. The mapping strategies involve design grammar[5], X-based reasoning[6-9], mathematical programming, game[10] and so on. One way to investigate the mechanism of mapping is to frame design by analogy with

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Y. M Hou and L. H Ji

embryogenesis. Literature on this field can be classified into evolutionary design[11] and automatic design[12-13] Graph-based approach is a useful tool to establish a computational design model. Related work in this field has mainly focused on the design of mechanisms and dynamic analysis of systems. For example, representation of mechanisms and kinematic chains, automatic generation of the kinematic structure of mechanisms, topological analysis of planetary gear trains, identification of connected components of the designed object, combinatorial representations of multidisciplinary knowledge[14-16]. Duality is mainly used for transformations between physical properties of the static system to the geometrical properties of the kinematical system [17-18]. This paper investigates the transformation from behavior to structure and places emphasis on the mathematical representation of transformation. (The transformation between functions and behaviours has been discussed in other publication [19]). An embryo approach is used to achieve the transformation. Matrices and vertex-edge-face weighted graphs are used to formalize design information. Duality is used to transform the representation of behaviour to that of structure. Computational transformation model is established and a design case is illustrated to show the method. The remainder of the paper starts with the research methodology, follows with transformation model and a design example, and ends with the discussion and conclusion.

2.

Methodology

The process of product design is progressive, from subjective intention to detail description of structures or systems. Key factors to the development of structure may be investigated by analogy with embryogenesis. Embryogenesis is a developmental process that usually begins once the egg has been fertilized. It involves multiplication of cells and their subsequent growth, movement, and differentiation into all the tissues and organs of a biological life[20].. 2.1

Bio-inspired Mechanisms to Map Function into Structure

Basic factors for a biological life to develop from egg to embryo are gene transcription, commitment, cell differentiation and induction[20]. To learn from organisms leads to a progressive design framework consisting of six stages: specifying functions, interpreting functions as behaviour in terms of natural laws, developing behaviours through induction, specifying behaviours, mapping the behaviour and the feature of structure, and optimizing parameters of structure. This process is a simulation of the development of organisms and it can be modeled as six stages: the Function, Surrogate, Property, Specification, Feature, and Parameter models. The Function model represents function specification. The Surrogate model expresses the behaviour of systems in terms of properties that can be described by laws, especially by natural laws. The Property model represents developed property set. A control system is also established at this stage. In mechanical

Duality-based Transformation of Representation from Behaviour to Structure

33

design, the term “property” may denote the stiffness of a structure, the power of a driver, the processing coefficient of a processing unit, the energy transformation coefficient of a sensor or of an actuator, etc. The Specification model represents specified properties of the system. The Feature model relates to the topology and material of the structure, and the Parameter model to the detailed description of artifacts. Bio-inspired mechanisms can be used to achieve the transforms between these models. They are gene transcription, commitment, cell differentiation and induction. The transformation between the Function model and the Specification model has been discussed[19]. The transformation between the Feature model and the Parameter model will be discussed in future publication. Following sections focuses on the transformation from the Specification model to the Feature model 2.2

Transformation from Behaviours to the Feature of Structure

To transform the behaviour into the feature of structure, two processes are needed. One is gene transcription and the other one is commitment. Gene transcription and commitment processes are complex in biology, but, fortunately, they are not so complex in the design of artifact. Commitment can be achieved mainly through decision-making, which will be discussed in other publication. Gene transcription can be achieved partially through dualism. Here, “partially” means that only the representation is transformed.

3.

Modelling the Transformation

Design information consists of a group of concepts. Graph provides ideal tools to represent a group of concepts as well as the relation between them. Matrices are used to represent design concepts. Weighted graphs and dual graphs are used to represent design models. Duality is used to transform the representation of behaviour to that of structure. A weighted vertex-edge graph is used to represent the behaviour and a weighted vertex-edge-face dual graph is used to represent the feature of structure. 3.1

Basic Concepts of Graph

A graph G

V

(V , E ) is a structure which consists of a set of vertices

^v1, v 2,!` and a set of edges

E

^E1, E 2,!`; each edge e is incident to the

elements of an unordered pair of vertices {u,v} which are necessarily distinct [21] . The graph G* (V *, E*) is said to be the dual of a connected graph

G

(V , E ) If there is a 1-1 correspondence f: E-E*, such that a set of edges S

forms a simple circuit in G if and only if f(S) (the corresponding set of edges in G*) forms a cutset in G* [21]. A weighted graph is a graph with weights both for vertices and edges.

34

Y. M Hou and L. H Ji

A vertex-edge weighted graph is extended here to vertex-edge-face weighted graph and the weight is denoted by matrix or cell matrix in order to accommodate all variables and parameters at different design stages. 3.2

Representation

Behaviours are denoted by properties. Properties and property relations are represented by matrix

Pr operty

Rij

^r

^pi | pi

(W 1 ,W 2 ,")`, i 1,2,", n

rij (O1 , O2 ,"), wij

ij

wij J 1 , J 2 ," , `,

i , j 1,2," , n where,

W i , Oi

and

Ji

(1) (2)

represent factors characterizing properties; rij represents

physical relation between two properties, while wij represents signal relation between two properties; n is the number of properties. For mechanical products, generally one gets Pr opertyi [ ki , Ai ,"] ,

rij

rij (Type , F , Ve , a , ") and wij

wij (u , I , Vt , B , T , ve, a , X , F , ") ,

where ki is a stiffness, Ai is a area, Type is a connection type; F is a generalized force, including linear force, rotation and bending moment; Ve is a generalized velocity, including linear and angular velocity; a is a generalized acceleration, including acceleration and angular acceleration. u is a displacement; I is a electrical current; Vt is the voltage; B is the magnetic strength; T is the temperature and X is the position. The feature of structure is represented as

Substructure

^S

i

| Si

si (:, m ); : R 3 , i 1, ns`

(3)

where : is the topology of a substructure; m is the material of a substructure; ns is the number of substructures Parameter of structure is represented as

Subparameter

^Pi | Pi

pi ( para, m); i 1, nP`

(4)

where, para are the parameters of a substructure and m is the material of a subxtructure; nP is the number of final substructures.

Duality-based Transformation of Representation from Behaviour to Structure

3.3

35

Duality-based Transformation

To transform behaviour to the structure, gene transcription is needed, as discussed in section 2.2. Dualism provides a mathematical tool for gene transcription from the Specification model to the Feature model. Consider a graph G (V , E ) . Let n, p, and q be the number of vertices, edges, and faces. The Surrogate, Property and Specification models can each be illustrated by a graph G (V , E ) .

V

{vi , pi } , where pi represents Propertyi

(5)

Relation between properties can be represented as edges.

E {el , Rl }, l 1,2,", p

R

^R

l

| Rl

[ rij , wij ]`, l

(6)

1,2," , p , i , j 1,2," , n

(7)

The number of property, i.e. n, is different in deferent models. In the surrogate model, n=n. In the property model, np will replace n and np>n as a result of induction. In the specification model, some relations may disappear or emerge, so ns will replace np and ns may equals or does not equal np. The Feature and Parameter models can be each illustrated by a dual graph: G* (V *, E*, f *) . When the Specification model can not be represented as a single planar graph, it should be separated into several planar graphs to benefit duality-based transformation. A vertex-edge-face weighted dual graph is used to represent the feature of structure.

V * {v *k | vk * m f k , X k *}, k 1,2,", q

(8)

E* {el * | el * m el , Rl * | Rl * Rl , Ll }, l 1,2, " , p

(9)

f * { f i * | f i * m Subi , Si }, i 1,2,", n

(10)

where Xk* represents the coordinates of subsystems and it is the weight of v*; Ll Subi Sub j . Under the dualism-based transformation, properties that are represented as vertices in a graph evolve into physical descriptions of substructures that are represented as faces in the dual graph; connection properties that are represented as edges in the graph evolve into physical descriptions of adjacent relations of substructures; the space that is represented as faces in the graph evolves into a coordination of substructures. Figure 1 shows the duality-based transformation.

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Y. M Hou and L. H Ji

Dualism not only provides an explanation of the transformation from the abstract property to the physical structure but also provides a means for programming the transformation.

a

b

Figure 1. Duality-based transformation a. prime graph; b. dual graph

3.4

Programming

The computational model of dual transformation is achieved using B-splines in two ways: interactively drawing or automatically transformation. The initial vertices and edges of the dual graph may need to be rearranged. The rearrangement involves moving vertices (i.e., coordination of substructures) in order to minimize the length of the edges (i.e., the contact length of adjacent substructures). The dual graph is developed in five steps. (1) To generate the feature representation of the dual graph. (2) To modify the positions of vertices of the prime graph to make it ease to identify and to make enough space for drawing the dual graph interactively. (3) To choose the vertices X* of the dual graph. This step is optional because the codes are programmed to automatically generate the vertices according to the number of vertices and faces of the prime graph if no vertices be input. (4) To draw the edges e* of the dual graph. In the case of interactively drawing, to draw lines across the edges of the prime graph line by line by pointing a series of points for one line by the mouse. In the case of automatic drawing, codes are programmed in such a way that each edge is drawn as short length as possible aiming at achieving optimal layout of the structure. This strategy also avoids the codes generating a group of dual graphs, which makes decision complex. (5) Finally, to mark the faces. The duality-based transformation can be easily implemented on Matlab. The function ‘getcurve’ is modified to achieve interactively drawing of dual graph, and the function ‘intersect’ is used to evaluate adjacent edges of faces. The challenge of programming is to get the optimal dual graph. Although a group of graphs are available, only a particular dual graph will be useful for reference. Generally, a small size and simple adjacent relation are preferable. Therefore, the codes are programmed to draw an optimal dual graph with the shortest edges..

Duality-based Transformation of Representation from Behaviour to Structure

4.

37

Example

A basic requirement is that the strain experienced at the center of a beam be less than a certain given value, i.e. Δmax<Δlim. 4.1

Behaviour

The Function model can be represented as F = {F1 F2 F3 } , where Fi mean reference body, supporting and loading respectively. The Surrogate model is established to achieve the functions, as shown in figure 2a. Stiffness k is selected as the properties in the Surrogate model to satisfy the basic requirement. The Surrogate model can be represented as

V = {1 2 3]T , [ p1

p2

p3 ]T }

,

E = {[e1 (1,2) e2 (2,3) e3 (2,2)]T , R} ,

⎧ r (0, F ,0,0)

12 12 ⎧ k1 ⎫ ⎪k ⎪ R = ⎪ ( 0 , r F ⎨ 23 23 ,0,0) p = ⎨ 2⎬ ⎪ r (0,0,0,0) ⎪⎩k3 ⎪⎭ ⎩ 22 ,

w12 (0,0,0,0) ⎫ ⎪ w23 (0,0,0,0) ⎬ w22 (u ,0,0,0) ⎪⎭ .

a

b

Figure 2. Graph representation a. the surrogate model; b. the property model

The Surrogate model is input into induction model as a cell matrix. According to induction rules[19]: w22 will generate the Sensor structure Sub4, the Actuator structure Sub5, the Processing Unit Sub6, the Driver Structure Sub9 and the Energy Structure Sub10; r12 and r23 will generate the PartVolume. Outputs are a sketch and matrices of the Property model. Figure 2b shows the output graph. The output matrices are V = {i, pi }, i = 0,1,

{

,10 , E = {e, R} ,

}

T e = [e1 (1,7) e2 (7,2) e3 ( 2,4) ...] , R ,

38

Y. M Hou and L. H Ji

⎧ r17 (0, F12 ,0) w17 (0,0,0,0,0) ⎫ ⎧k1 ⎫ ⎪r (0, F ,0) w (0,0,0,0,0) ⎪ ⎪k ⎪ 23 72 ⎪⎪ . ⎪⎪ 72 ⎪⎪ 2 ⎪⎪ , w24 (u ,0,0,0,0) ⎬ p = Pr operty = ⎨ k 3 ⎬ R = ⎨ r24 (0,0,0) ⎪ r (0,0,0) w (0,0,V ,0,0) ⎪ ⎪g ⎪ 46 ⎪ ⎪ 46 ⎪ 4⎪ ⎭⎪ ⎩⎪ ⎭⎪ ⎩⎪ In the Specification model, the relation properties may be modified after the types of sensors and actuators are determined. 4.2

Duality-based Transformation

Step 1. Generate the feature representation of the dual graph.

[

V * = v1*

][

]

v 2* , X 1*

⎧ X 11 ⎪X ⎪⎪ 21 X * = ⎨ X 31 ⎪X ⎪ 41 ⎪⎩

X 2* }

⎧ e1 (1,7) X 12 ⎫ ⎪e (7,2) X 22 ⎪ ⎪⎪ 2 ⎪⎪ , E * = ⎨ e3 ( 2,8) X 23 ⎬ ⎪e ( 2,4) X 24 ⎪ ⎪ 4 ⎪ ⎪⎩ ⎪⎭

L1 = l1 ⎫ ⎧1 ⎪2 ⎪ L2 = l72 ⎪⎪ ⎪⎪ L3 = l8 ⎬ , f * = ⎨ 3 ⎪4 L4 = l 4 ⎪ ⎪ ⎪ ⎪⎩ ⎪⎭

S1 ⎫ S 2 ⎪⎪ ⎪ S3 ⎬ . S4 ⎪ ⎪ ⎪⎭

Step 2. Modify the positions of vertices of the prime graph. Step 3. Choose the vertices X*. Step 4. Draw the edges e* of the dual graph. See the graph in figure 3. Step 5. Mark the faces. Step 6. Drawing the layout manually. See the graph in figure 4.

a

b

Figure 3. Dual graph drawing a. interactively drawing; b. the modified dual graph

Duality-based Transformation of Representation from Behaviour to Structure

39

Figure 4. The layout of the structure

5.

Analysis and Discussion

The designing process is divided into two levels. The first level compasses the first three stages that develop the behaviour in an abstract level, while the second level compasses the later three stages that develop the structure in a concrete level. To transform the behaviour into the feature of structure, one of mechanisms is gene transcription. Duality-based transformation acts as gene transcription and couples the abstract behaviour and the concrete structure. In dual graph, the vertices of the prime graph that represents behaviours disappear and they are transformed into dual faces that represent substructures. The advantage of duality-based transformation not only lies in the available mathematical representation, but also lies in that it implies the transformation nature. The dual graph also displays the basic layout of components of structure. Duality theory not only provides an explanation on the transformation from abstract property to physical structure but also provides a tool to program the transformation.

6.

Conclusion

A bio-inspired approach is used to investigate the mechanisms to map behaviour into structure. This leads to a six-stage design framework: specifying functions, interpreting functions as behaviour in terms of natural laws, developing behaviours through induction, specifying behaviours, mapping the behaviour and the feature of structure, and optimizing parameters of structure. These six stages can be represented as six models: the Function, Surrogate, Property, Specification, Feature, and Parameter models. Duality-based transformation provides a mathematical representation from behaviour to structures and acts as the gene transcription mechanism. A weighted graph is used to represent the behaviour set, which are denoted by properties.A vertex-edge-face weighted dual graph is proposed to present the feature and parameters of substructures and their interconnection. The dual graph is also useful to assist in the layout of components of the structure. The computational transformation model is established and a design case is illustrated to show the method.

40

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Acknowledgement

This research is partially supported by Aerospace Fund of China and two grants from Beijing Information Science and Technology University.

8.

References

[1] Chandrasekaran B, Josephson JR, (2000) Function in device representation, engineering with computers. Computer Aided Engineering 16:162–177 [2] Gero JS, (1990) Design prototypes: a knowledge representation schema for design. AI Magazine 11(4): 26–36 [3] Pahl G, Beitz W, (1986) Konstruktionalehre, Spring-Verlag, Berlin/Heidelberg [4] Suh NP, (1998) Axiomatic design theory for systems. Research in Engineering Design 10:189–209 [5] Öberg J, O'Nils M, Jantsch A, (2001). Grammar-based design of embedded systems. Journal of Systems Architecture 47: 225–240 [6] Kamal Mubarak, (2005) Design composition in architecture dissertation. Carnegie Mellon University, PhD Dissertation [7] Chen G, Ma YS, Thimm G, Tang SH, (2005) Knowledge-based reasoning in a unified feature modeling scheme. Computer-Aided Design & Applications 2(1–4): 173–182 [8] Horváth I, Vegte WFVD, (2003) Nucleus-based product conceptualization: principles and formalization. Proceedings of ICED ’03, Stockholm 1–10 [9] Bozzo LM, Barbat A, Torres L, (1998) Application of qualitative reasoning in engineering. Applied Artificial Intelligence 12: 29–48 [10] Hernandez G, (2000) Integrating product design and manufacturing: a game theoretic approach. Engineering Optimization 32(6): 749–775 [11] Gero JS, (1996) Creativety, emergency, and evolution in design, Knowledge-Based System 9: 435–448 [12] Lipson H, Pollack JB, (2000) Automatic design and manufacture of robotic life forms. Nature 406(31): 974–978 [13] Teng DX, Tong BS, (2000) Research on bionics structure design based on morphogenesis. Mechanical Science and Technology, 20(4): 483–484 (in Chinese). [14] Al-Hakim L, Kusiak A, Mathew J, (2000) A graph-theoretic approach to conceptual design with functional Perspectives. Computer-Aided Design 32: 867–875 [15] Shai O, (2001) Deriving structure theorems and methods using Tellegen’s theorem and combinatorial representations. Int. Journal of Solids and Structures 38: 8037–8052. [16] Shai O, Reich Y, (2004) Infused design I: theory. Research in Engineering Design 15: 93-107 [17] Shai O, (2002) Utilization of the dualism between determinate trusses and mechanisms. Mechanism and Machine Theory 37: 1307–1323 [18] Shai O, Pennock GR, (2006) Extension of Graph Theory to the Duality Between Static Systems and Mechanisms. Journal of Mechanical Design 128: 179–191 [19] Hou YM, Ji LH (2006) Representation and neural network induction model with growth form design. Advanced Design and Manufacturing for Sustainable Development, Frontiers of Design and Manufacturing, Sydney, Australia 1: 153–158 [20] Slack JMW, (1997) From Egg to Embryo-Regional Specification in the Early Development, Second Edition. Cambridge University Press [21] Tucker A, (1995) Applied Combinatorics, Third Edition. John Wiley & Sons, Inc., New York

Automatic Adaptive Triangulation of Surfaces in Parametric Space Baohai Wu, Shan Li, Dinghua Zhang Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Education Ministry of China, Northwestern Polytechnical University, Xi'an 710072, China

Abstract Based on the advancing front method (AFM), an automatic adaptive mesh generation method is proposed for triangulating three-dimensional parametric surfaces. Both the new node and new triangle element are generated in twodimensional parametric space, while the error between the triangle and the original surface in three-dimensional physical space is kept within the defined tolerance. The validity checking of the new triangle element, including the intersection checking and range control, is then carried out, and the corresponding correction measure is also discussed in the context. Numerical experiments together with analysis are given to illustrate the efficiency and robustness of the algorithm. Keywords: mesh generation, triangulation, three-dimensional parametric surface, advancing front method

1.

Introduction

With the rapid development of numerical techniques for the solution of engineering problems, there has been increasing demand for the automatic mesh generation of surfaces in the past few decades. It is required for instance in finite element methods (FEM), stereolitography (SLA), CAD/CAM and parametric surface rendering[1]. For an application in which a complicated domain is involved, it is quite often that the time spent on the mesh creation is longer than the time used in the numerical analysis[2]. Furthermore, the results of surface triangulation are the input data of the tetrahedral grids and the quality of tetrahedral grid directly depends on the quality of the surface discretization[3]. In recent years, significant efforts have been made towards developing efficient and robust algorithms for the automatic generation of unstructured grids over three-dimensional parametric surface. It appears that among the many methods that are available to date, the following two methods are most effective and reliable to generate high quality meshes[2], i.e. Delaunay based method[4,5] and advancing front method[3,6]. However, only a few efforts have been made for triangulating 3dimensional surface within a predefined tolerance. In order to obtain the

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B. H. Wu, S. Li, and D. H. Zhang

triangulation result which is adaptive to the curvature of the parametric surfaces, Sheng [7] and Vigo [5] studied this kind of surface triangulation based on the Delaunay method. In the research of Cuilliere[3], AFM was used to triangulate three-dimensional parametric surfaces within a predefined tolerance, while the detailed procedure was not mentioned in his study. Comparing with the Delaunay method, one of the advantages of the AFM is that the shape and size of the triangle element can be controlled by adjusting the location of the node [8]. As the main disadvantage, a lot of intersection checking between the new generated triangle element and existing elements must be computed in AFM in order to ensure that the new triangle element is valid. It is very difficult to finish this work in threedimensional space because the triangle elements are always not coplanar and the new generated element perhaps penetrates through the existing elements. So an improved method is needed to finish these works in two dimensions and the results can be mapped back into three-dimensional space within the predefined tolerance. This paper focuses on the automatic adaptive triangulation of the three-dimensional parametric surfaces based on the advancing front method. The error between the triangulation result and the original surface is kept within the predefined tolerance. Some generalized techniques will not be mentioned here because that there are lots of studies nowadays about the implement of the advancing front method. The rest of the paper is organized as follows: Section 2 describes the approach of new node generation and new triangle element formation. The validity checking and corresponding correction of triangle element is presented in section 3. In section 4, some examples are given together with the triangulation results analysis. Finally, conclusions are discussed in section 5.

2.

New Element Generation Approach

For the triangulation of the three-dimensional parametric surfaces, the key challenge for new triangle element generation is how to control the shape of the triangle element in two-dimensional parametric space to satisfy the real geometry property in three-dimensional physical space. Based on the effective circle, the paper presents a new element generation approach which is proceeded in the parametric space, while the real triangle element in physical space satisfies the predefined tolerance. The following paragraphs will discuss the approach in detail. When the triangulation tolerance is defined as H , the triangle element is admissible if the distance between any point interior to the triangle and the original surface is less than the given tolerance H . According to reference[1], the triangulation result is said to be admissible if all its triangle elements are admissible with respect to the original surface. Sheng [7] gave the maximum length of the admissible triangle edge in parametric space. Let r(u,v) be a C2 parametric surface, T is a triangle with vertices A, B and C in parametric space, and l be an arbitrary triangle with vertices l(A)=r(A), l(B)=r(B), and l(C)=r(C) on the surface. p is an arbitrary point in parametric space. Then the triangle l is admissible with respect to the original parametric surface r(u,v) if

Automatic Adaptive Triangulation of Surfaces in Parametric Space

:d3 where,

H

(1)

2M 1 4M 2 2M 3

: is the maximal edge length of triangle T in the parametric space and T

M1

43

w 2 r (u , v) ,M2 sup wu 2 pT

w 2 r (u, v) sup wuwv pT

T

w 2 r (u , v) sup wv 2 pT

,M3

T

In order to obtain a curvature-dependent triangulation of the surface, i.e., an adaptive triangulation, we must deal with non-constant : values along the patch. Vigo [5] developed the above theory and defined :( p ) and R ( p ) functions for each point in parametric space (see Figure 1). :(q0 ) q 0

R( p)

:( p)

p q0

p

:(q0 )

Figure 1. Illustration for definition of R(p)

:( p ) 3 R( p)

H 2 M uu ( p ) 4 M uv ( p) 2 M vv ( p)

min ^max( pq , :(q ))`

qC: ( p )

(2) (3)

C: ( p) is defined as a circle with radius :( p) centered on p . Similarly, circle CR ( p) is the circle of radius R( p ) centered on p . Function R and related circle CR illustrate the bounds on the maximum size of an admissible triangle in parametric space, they are defined as effective radius and effective circle respectively in this paper. A triangle is admissible if each of its edges ab is such that ab d min ^ R ( a ), R (b)` . Giving an arbitrary line segment of the current front in parametric space ab (see Figure 2(a)), the coordinates of the two endpoints are (ua ,va ) and (ub ,vb ) , the

44

B. H. Wu, S. Li, and D. H. Zhang

corresponding points on the surface A, B are shown in Figure 2(b). M is the middle point of curve segment AB, and m is the corresponding location in the parametric space. In some application areas, the quality of triangle element is not very important, such as the application of collision detection in some CAD/CAM area. In order to improve the calculating speed, the triangle element number of the triangulation result is expected as few as possible. So, the triangle element is expected with maximum area within the predefined tolerance.

a

m

A

b

M

B

a

b

Figure 2. One of the current front segments. a. the segment in parametric space; b. the segment in three-dimensional space

The determination of new node c in parametric space is illustrated by Figure 3. R (a ) , R(b) and C (a) , C (b) are the effective radiuses and effective circles of point a and b respectively, and the condition of ab d min R (a ), R (b) is satisfied. The initial new node c in parametric space can be taken as the intersection point of circles C ( a ) and C (b) . Then the effective radius and effective circle corresponding to the new node c , i.e. R (c) and C (c) can be calculated according to equation (3). For the purpose of triangle element abc is admissible, the inequation of R (c) t max ac , bc must be satisfied. In most

cases, the geometry property of the surface is continuous and the above condition can be achieved. If the new node can not guarantee the above inequation, node c should be moved towards the mid-point m along the line segment cm until R(c) max ac , bc is satisfied. As a result, the new triangle element

corresponding to nodes a , b and c in parametric space is admissible, i.e. the triangulation error between the triangle element ABC and the original surface r(u,v) is within the predefined tolerance H .

Automatic Adaptive Triangulation of Surfaces in Parametric Space

45

C (a ) C (b) R (a )

a

m

b

R(b)

c R (c )

C (c)

Figure 3. Finding the new node to satisfy the predefined tolerance

3.

The Validity Checking of the New Triangle Element

In AFM, validity checking of the new triangle element is essential to surface triangulation. It is possible for the new triangle element to intersect with the existing elements and redundant triangle elements will be generated if two adjacent nodes in the new front are too close or too far. Validity checking involves two aspects, i.e. intersection checking between triangle elements and nodes merging or inserting according to the distance between the two adjacent nodes. Both are discussed in detail in the following sections. 3.1

Intersection Checking Between Triangle Elements

When a new triangle element is formed, the intersection between the new element and existing elements must be checked and it is finished in the parametric space in present study. In the two-dimensional space, the sufficient and necessary condition for triangle elements intersection is that at least one couple of the edges of the elements intersect with each other. So the essence of element intersection is the intersection between the line segments in two-dimensional space. Li [10] gives a fast approach to estimate if the two line segments intersect with each other. Giving two planar line segments P1P2 and Q1Q2 (see Figure 4), P1Z and Q1Zƍ are perpendicular to the plane determined by P1P2 and Q1Q2. Then the sufficient and necessary conditions for the two line segments to intersect at one point other than endpoints are:

(( P1 P2 u PQ 1 1 ) PZ 1 )(( P1 P2 u PQ 1 2 ) PZ 1 )0 ® ' ' ¯((Q1Q2 u Q1 P1 ) Q1Z )((Q1Q2 u Q1P2 ) Q1Z ) 0

(4)

46

B. H. Wu, S. Li, and D. H. Zhang

Z' Q1 Z P2

P1

Q2

Figure 4. Intersection checking between line segments

when a new triangle element is formed, the two edges connected with the new node should be checked whether they intersect with all existing triangle elements in the parametric space. If the intersections occur (see Figure 5(a)), the two nodes should be merged to one new node, and the new node can be chosen as the midpoint of the two nodes, as illustrated in Figure 5(b).

a

b

Figure 5. Intersection occurrence and modification. a. intersection occurrence; b. modification for the intersection case

3.2

Nodes Merging or Inserting

In order to guarantee the triangulation precision, it is necessary to check whether the triangle edges formed by the adjacent new nodes are admissible with respect to the predefined tolerance H according to equation (3). Redundant triangles will be generated if the distance between the two adjacent nodes is too small, while the triangulation result will overrun the predefined tolerance if the distance is too large. So, the nodes distribution must be rearranged when the above two cases arise. The basic idea for node adjustment is merging or inserting nodes according to the distance between the two adjacent nodes. The adjustment of the nodes is detailed as follows. As shown in Figure 6, polygonal line 12345 is part of the current front and 6, 7, 8, 9 are the new generated nodes and triangles 126, 237, 348, 459 are the corresponding new triangle elements. R(1), R(2), …, and R(9) are the effective radius corresponding to these nodes respectively. As shown in Figure 7, if common area formed by effective circle 6 and effective circle 9 exists (as the shadow area in Fig. 7), it means that there is at least a point A can make the triangles 23A and 34A to satisfy the predefined tolerance. Therefore it is possible to merge nodes 7 and 8 to point A in order to avoid the redundant triangle generation. Node A can be

Automatic Adaptive Triangulation of Surfaces in Parametric Space

47

chosen as a point which is on the line segment 78 and included by the common area. Meanwhile, the following conditions must be satisfied for merging nodes 7 and 8 to node A :

2A ° ° 3A ° ® 4A ° ° 6A ° 9A ¯

d min R(2), R (A) d min R(3), R(A) d min R(4), R (A)

(5)

d min R (6), R(A) d min R(9), R(A)

1 R(6)

6

1

6

2

R(2)

2

7

7

R(3) 3

3

) R( A

A

8

8

R(4)

4 9

4 5

R(9)

9 5

Figure 6. Part of the current front

Figure 7. Merging two nodes to one point

Inequations (5) means that all triangles relating with node A must satisfy the predefined tolerance. When nodes 7 and 8 are replaced by point A, the triangle elements connecting with nodes 7 and 8 should be adjusted accordingly, such as triangles 267, 237, 348 and 489 in Figure 7 will be replaced by triangles 26A, 23A, 34A and 4A9 respectively. Triangle 378 degenerates into the line segment 3A and should be discarded. The other case which need to rearrange the nodes distribution is that the distance between adjacent nodes is too large with respect to the predefined tolerance. In most cases, a new point (always the mid-point) will be inserted between these two nodes[9]. However this problem sometimes can be settled by adjusting the node location other than node inserting. As shown in Figure 8, node 8 is not included in the effective circle R(7), i.e. the distance between nodes 7 and 8 is larger than the permitted value. Let m be the mid-point of line segment 38, 8ƍ is the intersection point of the circle R(7) and line segment 38. If point 8ƍ is located on the line segment 8m and 78' d min R (7), R (8' ) , then node 8 is replaced by new node 8ƍ, as illustrated by the dotted lines in Figure 8. Another possibility is that the point 8ƍ

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B. H. Wu, S. Li, and D. H. Zhang

locates on the line segment 3m other than 8m, the replacement under this condition will have not any merit comparing with inserting a new node because that this replacement will reduce the advanced distance greatly. So a new node should be inserted in this case, and the new node can be taken as the mid-point of nodes 7 and 8, as point 8ƍƍ in Figure 9. It can be seen that the triangle 378 is divided into two triangle elements, i.e. triangles 378ƍƍ and 388ƍƍ. 1

1 6

2

6 2

R(7)

7 R(7)

7 3

R(8') m

3

'

8

8'

8'' m

8 R(8)

8 R(8)

4

4 9

9

5

5

Figure 8. Node adjustment

3.3

Figure 9. Node inserting

Convergence Checking of Surface Triangulation

In advancing front method, convergence checking is especially important for surface triangulation because the people need to know whether the triangulation is finished or not. In our previous study[9], a simple and effective approach for triangulation convergence checking was developed. The approach is also applicable for this paper, so we will not discuss it here.

4.

Examples and Discussions

As an example, triangulation is carried out in this paper for a centrifugal compressor blade, which is a three-dimensional freeform surface modeled by Bspline method, as shown in Figure 10. The curve lengths of the blade boundaries 1, 2, 3 and 4 are 47.1051, 329.9315, 119.3394 and 227.6364 mm respectively. The area near boundary 3 is the inlet zone of the blade, and is always with high curvature to meet the aerodynamics requirement. 2

1 4

3

Figure 10. The centrifugal compressor blade

Automatic Adaptive Triangulation of Surfaces in Parametric Space

49

Figure 11 (a) and (b) show the triangulation results of the blade surface. The triangulation tolerance is defined as 0.2 and 0.4 mm, total 1470 and 694 triangle elements are generated respectively, as illustrated in Figure 11(a) and 11(b). The triangle quality is not considered in the triangulation procedure. The figures show clearly that the elements in the high curved area are much denser than the low curved area. The edge length of the triangle element depends on the curvature of the original surface.

a Figure 11. Triangulation results of the blade. a. H

b

0.2 ; b. H

0.4

The triangulation result of this study which is adaptive to the curvature of the parametric surfaces is mainly used to construct the bounding box of the blade for collision analysis between the cutter and the blade in multi-axis machining. For this application, the triangulation precision determines the collision detection accuracy, while the quality of the triangle element is not very significant for the collision detection result. In order to reduce the computing complexity, the ideal triangulation result should be with minimum element number under the given tolerance. Comparing with our previous work, the triangle number of the same blade using the presented method is reduced by 13.6% when the tolerance is defined as H 0.2 . It can also be seen that the triangle number decreases obviously with the tolerance increasing. Therefore, one of the key problems is to choose the most appropriate triangulation tolerance when the adaptive mesh generation method is adopted.

5.

Conclusions

A method based on the advancing front method (AFM) for automatic adaptive triangulation of the parametric surfaces has been discussed in the paper. The whole triangulation procedure is carried out in two-dimensional parametric space, including the new node and triangle element generation, validity checking of the triangle element and corresponding correction, and the convergence checking. The triangulation result is adaptive to the surface curvature, the error between the triangle element and the original surface is kept within the predefined tolerance. The practical triangulation of a freeform surface verifies that the algorithm is efficient and robust. Meanwhile, the number of the triangle elements by using this method can be reduced obviously with the same precision, therefore the stability and speed of succeeding numerical computation based on this triangulation result will be improved significantly.

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References

[1] Vigo M, Garciia NP, Crosa PB, (1999) Directional adaptive surface triangulation. Computer Aided Geometric Design 16: 107–126. [2] Lee CK, (1999) Automatic adaptive mesh generation using metric advancing front approach. Engineering Computations 16: 230–263. [3] Cuilliere JC, (1998) An adaptive method for the automatic triangulation of 3D parametric surfaces. Computer-Aided Design 30:139–149. [4] Borouchaki H, George PL, Hecht F, (1997) Delaunay mesh generation governed by metric specifications. Part I. Algorithms. Finite Elements in Analysis and Design 25: 61–83. [5] Vigo M, Pla N, (2000) Computing directional constrained Delaunay triangulations. Computers and Graphics 24: 181–190. [6] Francois V, Cuuilliere JC, (2000) Automatic mesh pre-optimization based on the geometric discretization error. Advances in Engineering Software 31:763–774. [7] Sheng X, Hirsch BE, (1992) Triangulation of trimmed surfaces in parametric space. Computer-Aided Design 24:437–444. [8] Guan ZQ, Song C, Gu YX, (2003) Recent advances of research on finite element mesh generation methods. Journal of Computer Aided Design and Computer Graphics 15: 1– 14. [9] Wu BH, Wang SJ, (2005) Automatic triangulation over three-dimensional parametric surfaces based on advancing front method. Finite Elements in Analysis and Design 41: 892–910. [10] Li YH, Hua YX, (2003) A Method to Quickly Accessing the Intersection of Line Segments. Mapping Aviso: 30–31.

Research on Modeling Free-form Curved Surface Technology Gui Chun Ma1 , Fu Jia Wu1, Shu Sheng Zhang2 1

North University of China, Taiyuan Shanxi 030051, China 2Northwestern Polytechnical University, Xi’an Shaanxi 710072, China

Abstract In the geometrical design system, there are a lot of methods about how to construct a free-form curved surface. With the development of shipbuilding and aviation, the progress of science and technology, it sets a higher demand for the technology of modeling a free-form curved surface. In this paper, we have elaborated the production, development, application, and the present situation as well as development tendency of the free-form curved surface modeling. In addition, we have proposed a new and easy-to-apply method for modeling a free-form curved surface from its perspective projection and the normal vectors at the controlling points on the free-form curved surface. A briefly essentials about perspective projections and normal vectors is summarized. The details of our method are given as follow. Typically we assume four controlling points P00 , P01 , P10 and P11 not coplanar. The perspective projections of the four controlling points on two planes P00 P01P10 and P01P10P11 are known. Equations for calculating the three-dimensional coordinates of these four controlling points are derived, and thus a small patch of the free-form curved surface to be constructed is obtained. This typical processing is repeated until the entire free-form curved surface is determined. A numerical example shows preliminarily that our method is easy-to-apply. By using of our modeling method, it is convenient to control the shape of the free-form curved surface to be constructed. The geometrical structure of the modeling free-form curved surface is apparent. Keywords: modeling free-form curved surface, perspective projection, curved surface, computer-aided design

1.

Instruction

The CAD/CAM technology originates from the aviation industry. Because the airplane contour is not only complexity but also includes the mass of free-from curved surface, the relationship between the CAD/CAM technology and modeling free-from curved surface technology is tightly from beginning to end. People been exploring explored new methods of modeling a free-form curved surface for many years. At the beginning of proposing B-spline functions, modeling curved surface

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G. C. Ma, F. J. Wu and S. S. Zhang

had developed from parametric spline, Coons, Bézier, B-spline to a geometry theory system which is composed of Rational B-spline surface and Implicit algebraic surface practicing as the main body, and interpolation, fitting and approximation practicing as the framework for 50 years.[1] With the development of production, B-spline has an obvious insufficiency. Simultaneously, NURBS can express quadric surfaces precisely, and the weighting factor make it easy to control and realization easily. Moreover, it can be promoted directly in four-dimensional space. Therefore, the ISO has promulgated the international standard STEP about the industry product data exchanging in 1991. It regards the NURBS as the only mathematics description method which defines the geometry shape for the industry product.[2] The modeling methods above are all based on controlling the free-from curved surface shape by changing the date point position. The designer, whose spatial thought ability is strong or experienced, can operate the free-from curved surface shape with wishes fulfilled by these modeling methods. And, they can estimate which will occur in the free-from curved surface shape because of the change of the point. In opposite, the designer whose spatial thought ability is weak or is lack of experienced, can not judge the points position and the structure of free-from curved surface. In addition, the free curved surface can only be demonstrated in the monitor or planed on the blueprint, and all these graphs are two-dimensional. They cannot reflect the three-dimensional free-from curved surface exactly. Therefore, it is easy to cause misunderstanding. In order to solve the problems above, we have proposed a new and easy-to-apply method for modeling a free-form curved surface from its perspective projection and the normal vectors at the controlling points on the free-form curved surface.

2.

The Research Situation of Modeling Surface Technology[3]

2.1

Deformation or Shape Blending

The traditional NURBS curved mode changes curved surface partial only by adjusting the control apex or the weighting factor. It carries operation on the level directly in the curved surface point by layer model. Some simple curved surface design method based on the parameter curve such as Sweeping, Skinning, Revolving and Stretching all make its deformation by adjusting the curve. The computer animated mapping and modeling entity need urgently to develop the methods of the expression or the coordination which have nothing to do with distortion. Then, some deformation method have been developed, such as FFD(Free-Form Deformation), the elastic deformation and the thermo-elasticity mechanics, the transformation by solution restraint, the transformation by geometry restraint as well as the coordination such as the polyhedron correspondence relations and the Minkowski and operation in picture morphology.

Research on Modeling Free-form Curved Surface Technology

2.2

53

Reconstruction

In the curved surface making about animating manufacture of designing a fine car body or person face sculpture, it always manufactures the model with the greasy dirt and then does three dimensional data point sampling. In the visible medicine picture, it usually uses CT slice to obtain the three dimensional data point of human internal organs surface. A geometry model of restoring the primitive curved surface from partial sampling information is called to be reconstruction. The sampling tool contains laser ranging scanner, medicine imagery meter, contact survey digitizer, radar or seismic survey instrument and so on. According to the forms of reconstruction, it can be divided into function reconstruction and discrete reconstruction. The former representative achievements were that Eck established the reconstruction of free topologic B-spline surface in 1990, and Sapidis invented the method of drawing up with the set of discrete points in 1995. The latter active method was establishing the approaching model of the plane piece of the set of discrete points, like Hoppe established lamination linearity in 1992 and the lamination smooth curved surface model in 1994. Recently, the reconstruction research has formed the upsurge. 2.3

Surfaces Simplification

The same as the reconstruction, this research area is one of international hot spots at present. Its basic thought is to remove the redundant information in the discrete curved surface which is three dimensional reconstructed or the modeling software output result(mainly is triangle network) and to guarantee accuracy, so as to make the graphical display timeliness, the data storage efficiency and the data transmission rapidity. This technology has advantages to establish the level approaching model, and carries on the lamination demonstration, transmission and edition to the multi-resolution curved surface model. The specific methods contain the method of rejecting the grid apices, the method of deleting the mesh boundary, the method of optimizing the grid, the method of the biggest plane to approach the polygon and the parameter sampling method.

3.

Development Tendency of Modeling Surface

3.1

Modeling Curve Surface with Energies Superior Method[4]

In 1987, Terzopoulos, a Canadian scholar, put deformable curve surface technology which based on the physical energy model into computer graphics. With the physics energy model established by the Lagrange equation, partial differential equation was solved by difference method to obtain the energy curved surface, which laid the foundation for the energy optimization modeling. In 1991, Professor Gossard and Dr. Celniker from MIT have further developed the energy optimization thought. They introduced it to the alternately design of the free curve surface, and proposed the characteristic line method to enhance flexibility of the curved surface design. In the energy optimization, Moreover, Welch and Witkin

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studied the function of offset point, parametric curve and normal vector etc., and introduced the restraint processing methods of Null-Space Projection. This means that based on the energy model physical level, although alternately or the automatic shape design may be carried on, it may still invoke present geometry operation on the geometry level. Research on distortion curve and modeling curved surface based on the energy model has already obtained the huge achievement, but also many questions are needed to solve, including: the computational efficiency, the interactive speed enhancement is limited when using finite-element method; alternately controls which is how alternately to chose the physical parameter; Energy functional choice that is how to enhance the computational efficiency and to guarantee balance of curved surface quality. 3.2 Modeling Surface Method Based on Partial Differential Equation (PDE) The idea based on modeling surface method of partial differential equation origins from taking the structure question of transition surface as the side value question of a partial differential equation. Afterwards, it was found that curved surface physiques in the actual problems could be easily structured with this method. For example, contour of hull, airplane and propeller leaf blades etc.[5] The PDE method is one new modeling surface technology, this method is only one curved surface design technology, but not the curved surface expression method. 3.3 Application of Wavelets Technologies in Modeling Curve Surface The wavelet analysis is unprecedented progress to the Fourier analysis. It is not only the powerful analysis technology, but also a kind of fast computation tool, and is of important theory significance and useful value. The wavelet is the powerful tool to portray the data interior relevant structure, and approaches the aspect in the data compression and approximation. In recent years, the wavelet analysis has obtained the widespread application in the computer graphics day by day, including radiation computation, curve and curved surface edition, body drawing, image editing, body distortion and progressive transmission and so on. Frinkelistein and Salesin have studied on the wavelet multi-resolutions analysis theory in closed interval. They used B-spline wavelet in closed interval, studied the B-spline curve, the multi- resolution expression of the B-spline curved surface with the tensor accumulates and application in the multi- resolutions edition. Lounbery extended recognition analysis and the wavelet theory to the free type of topology curved surface, developed the application objects of the wavelet technology. Eck has put MRA into free grids LOD (level-of-detail) approaching method, which caused any polyhedron and the grid curved surface all may be expressed by using the multi-resolutions. Certain expanded MRA, may carry on the multi-resolutions analysis to the color grid. Gotler and Cohen studied the wavelet’s application in the modeling geometry of variation. [6]

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4. Projections of Controlling Points and Normal Vectors of Curved Surface 4.1 Projections of Controlling Points The geometric model of perspective projection is shown in Figure 1. Where the point Pc ( x c , y c , z c ) is the center of perspective projection, xoy is the projective plane, and the point Pt ( xt , y t ) in the plane xoy is the perspective projection of a point P( x, y, z ) in three-dimensional space. Thus the perspective projection equations are given by the equations (1) xc z xzc ½ xt z zc °° (1) ¾ yc z yzc ° yt z zc °¿

Figure 1. Geometric model of perspective projection

4.2 Normal Vectors of Curved Surface On the basis of giving the perspective projections of controlling points which control the position and shape of a free-form curved surface, the normal vectors of the curved surface play a main role in controlling its three-dimensional shape. In order to control the three-dimensional shape of a free-form curved surface, the designer needs to provide the normal vectors of the free-form curved surface at all of controlling points. For example, giving the normal vector P00 ( a, b, c) on a controlling point P00 is a directed line segment connecting the origin of coordinates with point (a, b, c) . References[7-9] have given some methods constructing normal vectors from an image automatically. In our method, designers are only needed to provide the directions of normal vectors at controlling points with spherical coordinates.

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4.3 Three–Dimensional Controlling Points Existed methods for modeling a free-form curved surface are mostly based on three-dimensional controlling points on it. For employing these modeling methods, we need to enumerate the three-dimensional coordinates of all controlling points according to their perspective projections and normal vectors. All of current methods for modeling a free-form curved surface are mostly to construct a small patch of free-form curved surface by using of four controlling points, and then join smoothly them to model the whole free-form curved surface. The four controlling points are generally not coplanar. Two planes P00 P01P10 and P01P10P11 can be established are constructed from the four controlling points P00 , P01 , P10 , P11 as shown in Figure 2. Using average the normal vectors of a free-

form curved surface on these controlling points by using of methods such as weighted arithmetical mean or geometric mean, the normal vectors of the planes can be estimated.

Figure 2. Perspective projections of controlling points

If a point on a curved surface in three-dimensional space is determined arbitrarily, the point only reflects the spatial position of the curved surface but its geometrical shape. The z coordinate z 00 of the controlling point P00 on a free-form curved surface is supposed to known in this paper. Assuming p 00 ( x00 , y00 , z 00 ), p 01 ( x01 , y01 , z 01 ), p 01 ( x01 , y01 , z 01 ), p 01 ( x01 , y01 , z 01 ) are the three-dimensional coordinates of controlling points P00 P01P10 and P11 , respectively, and p t 00 ( xt 00 , yt 00 ), p t 01 ( xt 01 , yt 01 ), p t10 ( xt10 , yt10 ), p t11 ( xt11 , yt11 ) are their corresponding perspective projections, and n1 (n x1 , n y1 , nz1 ), n 2 (nx 2 , n y 2 , nz 2 ) are the normal vectors of two planes P00 P01P10 and P01P10P11 respectively. By means of perspective projection equations (1), we can obtain the conclusions as following

Research on Modeling Free-form Curved Surface Technology

x00 y00 x01 y01 x10 y10 x11 y11

xc z 00 xt 00 ( z 00 z c ) ½ ° zc ° yc z 00 yt 00 ( z 00 z c ) ° ° zc ° xc z 01 xt 01 ( z 01 z c ) ° ° zc ° yc z 01 yt 01 ( z 01 z c ) ° ° zc ° ¾ xc z10 xt10 ( z10 z c ) ° ° zc ° yc z10 yt10 ( z10 z c ) ° ° zc ° xc z11 xt11 ( z11 z c ) ° ° zc ° yc z11 yt11 ( z11 z c ) ° ° zc ¿

57

(2)

where unknown parameters are z 01 , z10 and z11 . As z00 is known, z 01 and z 10 can be determined from the plane P00 P01P10 and equations (2) as following z01

z10

nz1 z00 zc nx1 zc ( xt 00 xt 01 ) nx1 z00 ( xc xt 00 ) ½ ° nx1 ( xc xt 01 ) n y1 ( yc yt 01 ) ° ° n y1 zc ( yt 00 yt 01 ) n y1 z00 ( yc yt 00 ) ° nz1 zc ° ¾ nz1 z00 zc nx1 zc ( xt 00 xt10 ) nx1 z00 ( xc xt 00 ) ° ° nx1 ( xc xt10 ) n y1 ( yc yt10 ) ° n y1 zc ( yt 00 yt10 ) n y1 z00 ( yc yt 00 ) ° ° nz1 zc ¿

(3)

Similarly, z11 can be obtained according to the plane P01P10 P11 and equations (2) as following z11

n z 2 z10 z c n x 2 z c ( x t10 x t11 ) n x 2 z10 ( x c x t10 ) n x 2 ( x c x t11 ) n y 2 ( y c y t11 ) n y 2 z c ( y t10 y t11 ) n y 2 z10 ( y c y t10 ) nz 2 zc

(4)

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Thus the z coordinates of all of the controlling points are determined, and we take them into the equations (2), and determine the ( x, y) coordinates of all of the controlling points. So ( x, y, z ) coordinates of all of the controlling points are obtained. We can construct the free-form curved surface with bicubic parameterized splines by means of ( x, y, z ) . z

In order to model a small patch of free-form curved surface with bicubic parameterized splines, it is needed to utilize the tangent vector of every controlling point on its boundaries. The normal vector and the tangent vector of every point on a curved surface are perpendicular to each other, that is n ij Tuij 0, n ij Tvij 0 . Where T and T are the tangent vectors of the curved surface in u and v uij

vij

directions at a controlling point Pij respectively. Thus we can determine the tangent vector at every controlling point of the boundaries of a small patch of freeform curved surface with bicubic parameterized splines. After the three-dimensional coordinates of controlling points Pi , j , i 0,1, " m; j 0,1, " n, are determined by above method, the free-form curved surface is constructed based on interpolating points ui v j j , j 0,1," n using the bicubic parameterized splines.

i, i

0,1, " m and

The bicubic parameterized equations of a free-form curved surface are given by Pu, v

>F0 s

ª Pi , j «P « i 1, j « Pu ,i , j « ¬« Pu ,i 1, j

Where u ui s ,i 'i

F1 s 'iG0 s 'iG1 s @ x

Pi , j 1 Pi 1, j 1 Pu ,i , j 1 Pu ,i 1, j 1

Pv,i , j Pv ,i 1, j Puv ,i , j Puv ,i 1, j

0,1, " m 1; t

Pv ,i , j 1 º ª F0 t º Pv ,i 1, j 1 »» «« F1 t »» Puv ,i , j 1 » «' j G0 t » » »« Puv ,i 1, j 1 ¼» ¬« ' j G1 t ¼»

v vj 'j

,j

(5)

0,1, " n 1

4.4 A Numerical Example In our numerical example, the center of the perspective projection is taken as ( xc , y c , z c ) (500,0,1500) . The perspective projections of the controlling points are shown in Figure 2. The perspective projections of controlling points, the normal vectors at the controlling points, and the three-dimensional coordinates of the controlling points determined by using our modeling method are shown in Table 1. A small patch of the free-

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form curved surface constructed in terms of controlling points and the normal vectors of the curved surface are shown in Figure 3.

Figure 3. A patch of a free-form curved surface constructed Table 1. Projections of controlling points, normal vectors at them, and three-dimensional coordinates of the controlling points.

xt,yt ˥,ĳ x y z xt,yt ˥,ĳ x y z xt,yt ˥,ĳ x y z xt,yt ˥,ĳ x y z

P00 30,30 0,150

P01 30,10 27,162

P02 30,-10 64,162

P03 30,-30 90,150

30 30 0 P10 10,30 -27,162

30 10 0 P11 10,10 0,165

30.85 -9.982 -2.714 P12 10,-10 90,165

33.129 -29.8 -9.985 P13 10,-30 117,162

12.206 29.865 -6.754 P20 -10,30 -64,162

12.206 9.955 -6.754 P21 -10,10 -90,165

13.365 -9.931 -10.297 P22 -10,-10 180,165

15.797 -29.65 -17.745 P23 -10,-30 154,162

-6.243 29.779 -11.005 P30 -30,30 -90,150

-7.442 9.949 -7.522 P 31 -30,10 116,162

-7.442 -9.949 -7.522 P32 -30,-10 153,162

-6.392 -29.79 -10.612 P33 -30,-30 180,150

-25.76 29.76 -11.992

-26.99 9.943 -8.506

-25.88 -9.922 -11.66

-25.07 -29.72 -13.94

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Conclusions

A new method is proposed for modeling a free-form curved surface from its perspective projection and the normal vectors of the curved surface at controlling points on it. We have introduced the method for determining z coordinates of controlling points using the perspective projections of controlling points, normal vectors of the curved surface, and construct a free-form curved surface by using of our modeling method. Designing initial datum of a free-form curved surface is feasible, and has the advantages of agreeing with the designers’ usual design practice in our modeling method. The initial datum of a free-form curved surface are clear geometrically, good geometric intuition. Our modeling method is convenient to control the shape of a free-form curved surface and easy to use by designers. By using of our modeling method, designers first need to give out the perspective projections of all of controlling points on a free-form curved surface according to the principle of perspective projection in terms of the features of the free-form curved surface which they want to construct. The projections of controlling points can also be obtained from an image or a drawing of the freeform curved surface. The normal vectors of the free-form curved surface are determined according to bending sizes and directions of the curved surface at the controlling points, and thus the free-form curved surface that designers want to model can be constructed automatically. If the designers are dissatisfied with the constructed free-form curved surface, they can reconstruct it by modifying the positions of projections of the controlling points or the normal vectors of the freeform curved surface at controlling points, until they are satisfied with it.

6.

References

[1] Guan Fu-qing, Luo Xiao-nan, Li Luo-luo etc. Computer-aided design of geometric shapes [M]. Beijing: Higher Education Press, 1998. [2] Zhu Xin-xiong. Free Modeling Curve surface technology [M]. Beijing: Beijing aviation space University Press, 2000. [3] Shi Fa-zhong, Computer Aided Geometric Design and Rational B-Spline. Beijing: Higher Education Press, 2001. [4] Eon J, Troopette. A new approach towards free-forrn Surfaces control [J].CAGD, 1995(12):395-416. [5] Bloor, Wilson. Special approximations to PDE surfaces[J].CAD, 1996, 28(2):145-152. [6] LounsberyM, PeroseT, Warren J. Multiresolution surface of arbitrary toplogical type [J].ACM Transactions on Graphics,1998.16(1):34-73. [7] F. Uiupinar and R. Nevatia, Perception of 3-D Surfaces from 2-D Contours. IEEE Trans. Pattern Analysis and Machine Intelligence, 15(1),1993:3-18. [8] R. Horaud and M. Brady, On the Geometric Interpretation of Images Contours. Artificial Intelligence, 1988, 37:333-353. [9] I. Weiss, 3-D Shape Representation by Contours. Computer Vision, Graphics and Image Processing, 41(1), 1988: 80-100.

Pattern System Design Method in Product Development Juqun Wang, Geng Liu, Haiwei Wang School of Mechatronic Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi, China, 710072

Abstract The conception of pattern system design was presented in this paper after analyzing the existent pattern design methods in product development. Two pattern design methods having system characteristics were classified, that were process pattern and object pattern. A new pattern system design method was put forward with integrating process pattern and object pattern, which was Process-Object Integration (P-OI) pattern system design method. A group of design elements were abstracted which could reflect full objects and whole process, and then they were integrated into a system associated with each other according to some certain logical relation. The pattern system design method had many good characteristics: share, reuse, system standard, process and object integration, system open, etc. A new concept for developing product design method was provided, which can increase design efficiency, optimize design quality, and reduce development cost. Keywords: Pattern system design, Product development, Design element, P-OI pattern system design method

1.

Introduction

Pattern design is a design method that picking up commonness in huge and complex design fields, setting up a reusable and creatable, optimizing quality, reducing cost, having the advantages of share, simple and credibility. However, there were some problems in existed pattern design methods such as lacking system standard, scarcity in combination of portrait and landscape orientation, disjoint of each design phase. Along with the requirements of domain cross subjects and integration development, the design of complex products will develop consequentially to systematization. The basement is established to research the pattern design by existed design, concurrent design [1] pattern of single element developed to more elements, DFX, similar system [2] etc. Taking system science as guidance, combining similarity theory as the academic foundation of the pattern system design, a concept of pattern system design is presented and a new pattern system design named processobject integration is developed in this paper.

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J. Wang, G. Liu and H. Wang

Development of the Pattern Design

Pattern design method of products exploitation is a modern design method talent showing itself in the pattern theory and methods in 1970’. By 30 years' development, it has taken on four types-segment pattern, process pattern, aspect pattern and object pattern as yet. IDEF founded by Ross and Douglas in America in 1970s, is a representation of segment pattern[3]. By way of structure analyzing and design technique, IDEF is a series patterns used on building product analyzing, design, produce and management model. Parallel engineering presented in research report of national defend analysis lab of America in 1988 is a typical parallel pattern design. Along with the enlargement of DFX research and application area, more and more designs face to aspect is welling up. And it contains face to function, structure, produce, assemble, quality, cost, and environment etc. most of DFX[4] nowadays run in the disassembly of the product structure step by step. “Function-structure-action”[5] complex transfer pattern based on object pattern and function structure pattern is an object pattern research most. The representation is presented by Gero in Sydney University in Australia. At present, most of the study based on the consequence of the example. And the pattern design through example match and consequence system is the focus of recent study[6].

3.

Pattern System Design

3.1

The Concept of Pattern System Design

It’s no appellation as pattern system design in reference yet. However, in fact, existed parallel design, some function and structure pattern design faced to whole object are pattern system design. In order to standardise the terminology the pattern design methods and research the pattern design system science deeply, this paper presents the concept of the pattern system design which is a design method composed pattern design and system design, is a pattern system design method. 3.2

LARS System Constructed by Three Elements

Through the observation, analysis and study deeply on the character, function and effect of the system elements, a system is regarded as composition of three elements as following: 1. Link Element Link Element is an element has link function in the chain of the system. Link element has three characters: 1) just act in the system; 2) a link element has direct relation with neighbor elements; 3) link element is indispensable, a system will disaggregate immediately by taking out a link element. 2. Aspect Element Aspect Element is an element has a certain aspect element in the whole system. Aspect element has three characters: 1) Aspect element is an element relating

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system with environment; 2) In system, an aspect element act with all link elements and other aspect elements. 3) Aspect element is not only the abuttal relation but having general function inside the system. 3. Relation Element Relation Element is the contact mode in the system elements. For example, subjection, juxtaposition, succeed, sequence, aggregation, alternation etc. Now the definition of system is definitude and embodied, which system is composed by link element, aspect element and relation element organic contact, LARS for short. We give two format definitions as follows. 1. the symbol format definition of LAR:

LARS := < LE, AE,RE > where㧦 LE —— Link Element;

LE = {LE1 ,LE2 ,...LEi ..., LEn } (i = 1,2,...i...,n) i —— the number of the link element AE —— Aspect Element; AE = {AE1 , AE2 ,LAE j ..., AEm } (j = 1,2,...j...,m)

j —— the number of the

aspect element RE —— Relation Element;

RE = {RE1 ,RE2 ,...REk ..., RE p } (k 1, 2,...k ..., p)

k —— the number of the

relation element 2. the graphic format definition of LAR LARS :=<Ⴜ ,႒ ,໖ > ż——Link Element㧧Ƒ——Aspect Element㧧ᤫ——Relation Element‫ޕ‬ The format structure is stable relatively in the main because the stable association among the characters of the three elements. Hereby, we give a general format of LARS in Figure 1. This format is suitable for any type of input-output format. It is not affected in general format but a little change in local details with element granularity transformation and flexion management.

Figure 1. LARS distributed net structure

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3.3

Kinds of the Pattern System Design

3.3.1

Process Pattern System Design

Process starts early, develops mature relatively and takes the lead in systematizing. Considering from time dimension, the whole structure of Process pattern system design presents sequence format, including serial and parallel pattern system design. The researches on process pattern system design are following: 1. continuity of the design process. The continuity of the design process is necessary to carry out process pattern system design and effective to use the design resource 2. optimize the path of design. The one of aim to study process pattern system design is to find a design path which response quickly. For example, research on logic relation management of every step during the design process, research on high efficient arithmetic etc 3. deep development of parallel design. Parallel design is the representational process pattern system design method at the present time. And it is need to more research and compliment on standard, share, parallel and conflict harmonizing. 4. other process pattern system design methods. For instance knowledge current, net current etc. then process pattern system design comes into a new process pattern system design method by bog change in content, organization and structure.

3.3.2

Object Pattern System Design

The main thought of the object pattern system design was “break up the whole into parts, analyze step by step”. No matter the design is to object or aspect pattern system, general collectivity structure is tree structure. Object pattern design method, appearing at the end of this century, such as spiral gene evolution, networking, multi Agent design system and so on, is reinforced in the system. Since the middle 1990’s, several system design methods are presented, including machine system, complex system, extreme system, 1+3+X integrated design method, method of integrated design for complex mechanical product similarity system etc. These design method developed the new approach for the object pattern system design method and theory.

3.3.3

Integrated Pattern System Design

In order to strength macrocosm of pattern system design, an integration pattern system design as the basic type is presented in this paper. Integration pattern system design can be divided into three types as following: 1. Colligation method integration pattern system design. Colligation method is a system method that alternates the existed colligation design method or integrates different design methods to make it pattern.

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2.

Human-machine intelligent integration pattern system design, namely pattern system design made up of cooperation by human and machine intelligent. Based on human intelligent, depended on human-machine intelligent integration technique, this design method resolves the problems of the innovate products. There are more connotative integrations in the design, and it can extend the function of the pattern system design. 3. Process-object integration pattern system design. The integration of process and object is an integration of two types of system composed by time and space. It is more integrated and more compacted in the system. Components and the relation in the integration pattern system are more complicated than series and parallel pattern system. The collective structure will change with different emphases of the system integration.

4.

P-OI Pattern System Design Method

P-OI(Process-Object Integration) pattern system design is a concrete method of integration design. The start or end of Element design is the start or end of process and object design. P-OI pattern system design is achieved though elements design and system conformity. The guideline to build a method is as follows. 4.1

Determine the Design Process for the System

The generalized design processes of product exploitation include product programming, concept design, detail design, construction design and service design. Product programming and service design are periphery design, and concept design, detail design and construction design are the principal part of product design. This system just takes the principal part into account. For conceptual design, there are concept and concept design in the detail design and construction design phase. All the content in the detail design and construction design are contained in the phase of concept design. In fact, two kinds of classify are reasonable from different point. Therefore, we can confirm two design processes according to two different classify, namely phase design process and arrangement design process. 1. Phase design process: made up of three phases, scheme phase - including the arm function of the products, work principle, and whole distributing structure; concrete phase - including components and assembly sketch design; materialization phase - the techniques process of produce and assemble product. 2. Layer design process: made up of three layers, conception layer - the result is product concept; detail layer - the results is assembly and component; construction layer- including techniques files, NC programming, techniques and the design of working procedure, cutting tool, clamp and measure. Each design layers contains all the design elements. Phase design process and layer design process observe design process in two different points of view. They have some in common and some difference in

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evidence. As a general design process face to the object, it is not necessary to differentiate, but it should be definite when according to the process design or needing a result of a certain process. The crossover and difference between two design processes is shown in Figure 2.

Figure 2. Crossover and difference between two design processes

4.2

Select the Design Element of the System

LEs of constructed system in the method are function, principle, layout, shape, color, structure, human, material, techniques, manufacture, and assemble. AEs are quality, environment, cost and management design elements. REs are transform, parallel and interaction. Hereby, there are 18 design elements in the system. 4.3

Construct P-OI Pattern Design System

4.3.1

Ensure Whole Structure, Distribute Design Elements

According to the type and function of the design elements, it is necessary to desperate LE from AE, and to arrange them in landscape orientation and portrait process though RE. The PO-I pattern system ensured by it is a layout net structure, as in Figure 3. It is a pattern drive structure has no relationship with platform, and use different interface with different platform to implement share and reuse.

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Figure 3. The whole structure of P-OI pattern design system

The guideline of the PO-I pattern system is design elements construct to design system. All of the elements present the maturity of the product, and express object pattern of the whole product. These elements come to object pattern by a certain arrangement, come to process pattern from landscape orientation and portrait simultaneously. Then compose the object and process pattern of the product to POI pattern.

4.3.2

Form the Conformity Mechanism, Integrate the System

The aim of the conformity is design process and object integration pattern system. And the content of the conformity are conformity in the elements, conformity in design phase or design layer, system conformity. The conformity process is under the reference frame as Figure 4 shows. The reference frame construct with three coordinate axes and cube, and three coordinate axes represent phase process design, layer process design and object design. The tube is made up of 15 design elements. In the element design process, process design and object design is done at the same time. The process design is composed of phase process design and layer process design. Then process design and object design make into P-OI design.

Figure 4. The coordinate system of P-OI pattern system

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Figure 5. The conformity mechanism between designs

Conformity mechanism is a program used to synthesize the design element and required the cooperation of communication technique and collaborative technique. The whole design process is a process with continuous information interaction and feedback. All design elements from function design to assemble design construct a concurrent design process. The conformity mechanism for design elements is illustrated in Figure 5. The aspect design and process design element including quality, environment, cost and management. They have intercurrent relationship with each other. In order to reflect the effect of aspect design element to process design element roundly and reduce the difficulty, the aspect elements are considered in each process design element.

5.

Application in the Product Development

The flow of the P-OI pattern system design method is illustrated in Figure 6. The method is an all-purpose design method, and its application is detailed below: 1. Process and object integration design: The basic function of the method is the integration of design process and object. This compositive method enhances design efficiency by separating process and object design. 2. Automatic or semiautomatic programming design: The design method can make the object and process into a pattern and dose not have to take over the design and running order of object and process. The design can run accord to the developed program completely and its performance is better and smarter than the concurrent design. 3. Conceptual design: The selected process design element must be arranged to form the whole design process. These design elements combined with the aspect design element form conception, seamless connection of particular and construction design. 4. Combined Industrial design and engineering design: The industrial design and engineering design are combined to form the whole pattern system since the design elements are selected in this method.

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Figure 6. The design flow of the P-OI pattern system design

5.

Flexible design: Based on the certain whole structure, the object-process integrated pattern system can reduce and compose the design element and complete the design for one layer or phase, also can complete the design oriented one aspect. 6. Innovation design: Combining the humachine intelligence and tool platform technology, the whole innovation mechanism is constructed because the design element is considered in conceptual design and the design run through the particular design and construction layer longitudinally and transfer to next design element laterally. In this mechanism, the innovation space is kept not only in the conceptual design layer but also in particular and construction design layer.

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7.

Reverse engineering design: In order to achieve the reverse engineering design, P-OI pattern system design break up the reverse reconstruction model, reverse analysis, reverse design into various design element, also design and conform them. 8. Workflow design. P-OI pattern system design is not only a pattern system design method, but also a sort of workflow of pattern system design used to manage the design flow.

6.

Conclusions

Based on the research of system composed of elements, classify elements three kinds, which form LARS. It has three important effects: 1) benefit to understand, analyze, and handle system issues; 2) associate system theory with similarity theory to form similarity system; 3) benefit to structure formally handle and construct system, improve system response capability, standardize application, simplify complex problems. As one kind of integration pattern system design, P-OI pattern system method is a pattern system design method integrating design process and design object, which takes design elements as organizational content and takes phase design process and layer design process as organizational route. Pattern system design for product development is still at the abecedarian seedtime, and abroad and deeply research is not spread. Aforementioned several pattern system design methods are just the preliminary research results based on conclusion of some practical design methods. Standard research to pattern system design is a kind of huge and complex system engineering, which should be developed more deeply.

7.

References

[1] Stephen, C Y Lu. Beyond concurrent engineering: a new foundation for collaborative engineering, the worldwide engineering grid [J]. Proceedings of 11th International Conference on Concurrent Engineering, Beijing: Tsinghua University Press and Springer, 2004, 11̚22 [2] Zhou Meili. Integration Design Principle and Methods of Diversity for Complexity Mechanical Products Similarity System [J]. THE CHINESE MECHANICAL ENGINEERING SOCIETY MECHANICAL DESIGN SOCIETY,2005(in Chinese) [3] Chen Yuliu. Modeling Analysis and Design Method for IDEF [M]. Beijing: Tinghua University Press, 1999(in Chinese) [4] Geoffrey Boothroyd, Peter Dewhurst, Winston Knight. Product Design of Oriented Manufacture and Assemble [M]. Beijing: China Mechanical Press,1999 [5] Gero J. S. Creativity Emergence and Evolution in design [J]. Knowledge-Based System. 1996, (9): 26~36 [6] Xiong Lihua, Wang Yunfeng. Research on rapid cost evaluation based on case-based reasoning [J]. Computer Integrated Manufacturing Systems, 2004, 10(12): 1605~1609(in Chinese)

Development of a Support System for Customer Requirement Capture Atikah Haji Awang, Xiu-Tian Yan DMEM, University of Strathclyde, James Weir Building, 75 Montrose Street, Glasgow, Scotland, G1 1XJ, UK

Abstract This paper describes the work being done to explore the potentials of establishing an automated customer requirement capture process at the start of a design process. Traditionally the process involves two stages; market research through marketing and identification of “the customer’s voice”, and the establishment of product design specifications from marketing by the design team. The approach is prone to errors in capturing what customers really need and it is difficult that design engineer perceptions can be validated and verified by customers. This may mislead the design engineer to waste his or her time and effort; and the company’s money to buy technologies in developing a wrong product. This research is trying to develop an interactive system in understanding the need identification of a product. For this purpose, users mainly the customers are required to validate whether the design information available in the database matches their requirement Keywords: requirement capture, customer needs, support system

1.

Introduction

Design is a process of generating solutions, which should satisfy all design requirements including expected performance, customer needs, legislation considerations, material properties and behaviours, and other engineering related issues. Researchers have made several attempts to describe the design process, some limit the description to technical level of generating solutions, while some include other non technical activities that indirectly related to design activities such as market analysis and product selling [1-4]. A definition by Pugh [2] summarises the whole design process as a concept called total design. Total design requires a blend of different skills in order to produce a marketable and functioning product. In total design, the process usually starts with collecting information on customer needs and expectations from the market, and ends with selling products in the market.

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Customer Requirement Capture

The process of understanding customer requirements and converting them into product specifications are done by design engineers mostly based on their experience in designing a particular product [5]. Though there are design methodologies that formalise the requirement capture in theory, what happens in real situation is very different. A series of case studies conducted by Darlington and Culley [6] prove that design engineers took an ad-hoc approach to understand customer requirement and come out with product specifications based on the requirements they have. The case studies have been conducted on experienced engineers working in established manufacturing companies, and if the sample taken is a true representation of the process in industry, this is a disadvantage to new design engineers or those what have not designed the same product before. The case studies involved mechanical and electronic engineers who were assigned to develop mechanical and electronic product requirements. These case studies show that because of the general nature of the product, mechanical designers tend to process information from conceptual design to performance validation mentally, rather than validating the product according to specifications. The case studies also show that there are different groups of customers existing in the market. The first group has no knowledge or experience with the product. Their requirements were expressed in the simplest ways and very general. Designers have to take extra effort to study other background information of this group such as demography and daily activities in order to understand their needs. This is the critical measure of requirement capture success because they may have said something without or with very little thought of the technical specification or constraints, hence lack of information. For the other two groups, one of them may have experience with a product, so they could give some of specifications such as physical description. For the last customer group, they are able to provide full specification of the product because they work along with engineers to design a customised product. Therefore usually no further requirements to be developed. As the majority of the population come from the first category, design engineers usually have problems to capture requirements from customers because there are many vague sentences which may leave designers with ambiguities and uncertainties. In this situation, designers tend to make decision based on their cognitive perception of the uncertainties [7]. This is a major disadvantage to novice designers. Furthermore, in any product development process, it is very critical to fully understand customer voice because inaccurate translation of customer requirement can lead to a wrong product being manufactured, thus negative implications on quality, cost and lead times [8].Another major disadvantage of this is that there is no way customers can validate that design engineers have captured their requirements correctly. The only time to validate this is when the product is being sold in the market, whether it succeeds or fails. Chen, etc. [9] has attempted to develop a multi-layer reference technology for knowledge management framework to facilitate knowledge sharing. The retrieval mechanism is based on the functional mechanism, which has helped designers to find design history based on product functions mentioned by customers. Other design researchers have also succeeded in translating customer requirements to

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conceptual solutions by matching customer requirements with functional domains of the product[10-16]. Krishnapillai and Zeid [17] attempt to understand customer requirements in term of product attributes using a configuration table if function-based mapping is not attainable. The capturing process has three stages; direct mapping, function-based mapping and requirement mapping based on transformation table. However, the work is still based on performance and functional of the products, which are easy to translate into product technical specifications. The works could be extended to understanding requirements such as appearance, ergonomics and cost related issues. Another approach to effectively capture the genuine customer needs was developed by Wei Yan, etc. [18]. The approach integrates picture sorting and fuzzy evaluation to elicit and analyse customer requirements. The approach improves the previous sorting techniques by eliminating the uncertainties, imprecisions and customer subjective judgements by introducing customer validation through interviews in the design process. The interviews allow customers to choose the most preferable design by sorting pictures of design alternatives produced based on the available products in the market. The interview results then analysed statistically and this new approach then helps designers to choose the most preferred design alternative, which is close to market orientations and customer demands. However, in this approach, designers first come out with design alternatives for customers to choose which design they prefer. Customers are given limited choices within design alternatives. This technique is very useful if applied to a group of customers who have no specific expectation of the product because the interview process is just to validate whether or not the design alternatives accepted by customers. To get the real voice of customer (VoC), the interview must be conducted before the generation of the design alternatives, and second interview is to validate whether designers have interpreted VoC correctly. As for the scope of this project, the method proposed previously will be applied because by having initial customer requirements and customer validation, it is hoped that product specifications will be the truest version of what has been demanded by customers. A program called Knowledge Acquisition and sharing for Requirement Engineering (KARE) has been developed at the University of Nottingham [19]. KARE automates the conversion process and understanding of customer voice by matching customer requirements to product characteristics in a complex system such as manufacturing. KARE has been designed to integrate knowledge from suppliers and customers to produce tender documents by having database of customer requirements, system and product lists, supplier lists, and constraints. If any requirement is unable to be met due to company or certain constraints, customer and supplier will confer requirements during negotiation. New requirements derived from the requirement negotiation will then re-enter the requirement analysis cycle. This is an improvement to the previous works in requirement management as previously most representations of product definitions are around representations of physical product structures, shape-related or function-related properties, or just having electronic database of various product properties [15, 20-23]. The purpose of studying this area is to develop a support system to automate customer requirement capturing process. At the initial design stage, design

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engineers try to understand customer needs or requirements that usually come from market surveys. Those statements are qualitative and vague as customers are expressing what they want from the products or their experience with current products. This may lead to misinterpretation of the requirements as design engineers usually perceive the requirements based on their experience. With the increasing product complexity, globalisation and market competitiveness, designers now need to clearly understand customer requirements and their transformation into product specifications is a critical part of the design process [2, 4, 24, 25].

2.

Proposed Support System

2.1

Product Design Specifications

Pugh [2] classifies Product Design Specifications (PDS) into 32 design elements, which include engineering and non-engineering aspects of a product. A study has been performed to select the most important PDS elements. The selected elements are the result of comparisons made among final year design projects and an industry survey for product design specifications concerned by customers and designers [26-29]. There are 17 mostly used design specifications for mechanical and electromechanical products. There are some specifications, which are not of customer concerns but more of company concerns such as company constraints, standards and specifications, and patents and other product data that have been excluded during the screening. The element of customer needs is also removed because all the product specifications are to be mapped to customer requirements, while the element of disposable is included in response to the growing environmental concern. Figure 1 shows the number of PDS included in the projects and after comparing these elements with the ones widely used by a minimum of 50% companies in industry, 13 PDS elements have been selected for the support system. Figure 2 shows the selected PDS elements for the artefact of this case study; an automated bicycle learning assistant as adapted from a student project [27]. Elements such as performance and maintenance can be translated directly to quantitative measures such as functional requirements, therefore both are popular among designers. For customers, they usually define these two elements as product applications. Although aesthetics, appearance and finish is difficult to measure quantitatively, it is usually one of the first qualities that attracts customers to buy a product. Generally, cosmetic quality described by customers as ‘attractive’ or ‘bright colour’, which are very vague and ambiguous. Some elements are related one another that when one decision made to fulfil one specification will affect others, for example materials, weight, working environment, product cost, disposable, maintenance and safety.

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To enable knowledge sharing, customer requirements and their possible related product specifications extracted from previous design projects are stored in a database. These will be used in a knowledge base analysis performed by the system to map customer requirements to product specifications. A template is to be designed to match the customer words to specifications based on word query.

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No. of Project

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0

Ae

PDS Elements

Figure 1. PDS Elements Included in Student Projects Automated Bicycle Learning Assistant

Materials Lightweight material

Safety No small parts No removable parts No sharp edges Non toxic paint

Size Wheel sizes 10” – 18” Maximum bike frame protrusion 500 mm Should not protrude above the height of the tyre

Weight Light enough to handle Max. weight to put on bike frame for control system – 1 kg.

Installation Minimum part number

Life in Service 5 years of continuous use 20 years of life expectancy

Performance Stabilising a child Minimal effect on cycling experience when removed Low voltage Self powered Speed range 0 – 20 mph Run 2 hours without recharge No change in operation for speed change Differentiate turning and falling Beginner to advanced Loading 392 N on saddle, 275N passing through rear wheel

Ergonomics Comfortable seat Handle length for children

Working environment Working temperature -5˚ – 30˚ C Storage temperature -3˚ – 50˚ C All weather conditions Useable in uneven terrain with no need for instant cleaning No storage cleaning required

Product Cost Manufacturing cost £12 48% profit Maximum selling price £35

Figure 2. Product Design Specifications

Aesthetic, Appearance and Finish Easy to clean

Disposable Die assembly to be considered for easier recycling and disposal ISO14001

Maintenance Low/no maintenance training Reset/recharge once per 2-hour session Any hydraulics/pneumatics must be easy to maintain, carried out by parents Any electrical supply should be easily accessible Any electrical supply should be quick to change with prior warning Any specialised tool must be easily attainable

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The selection of related words is based on previous case studies of the same product. The database is dynamic, new matching specifications can always be added to the library. Therefore, apart from judging customer requirements based on their design experience, designers can also make critical analysis by comparing their perceptions with the one retrieved by the database. 2.2

Support System Architecture

The support system architecture as illustrated in Figure 3 constitutes a user interface and a data processing module which comprises of tasks, domain knowledge and inference knowledge. Tasks are the procedures performed by the support system to process the requirements. Requirements are analysed and mapped to the list of customer needs in domain knowledge. Domain knowledge constitutes pre-determined information of the design process and product specifications. Other than the list of customer needs, question lists for users and product design specifications are also categorised as domain knowledge. During this process, the system produces a list of inference knowledge. Examples of inference knowledge are conflicting requirements, fulfilled or undecided requirements and specifications, and requirements and specifications that need further explanation from the users. Inference knowledge is the result communicated to user interface for validation. User reply is then sent back to the data processing module and the system decides whether the requirements have been fulfilled or if there is the need of a new requirement to be given by users. The process is iterative and each component of the system architecture interacts one another to complete the task. User Interface Initial requirements

User validation

New requirements

New specification registration

Data Processing Module Tasks New requirement analysis

Knowledge base mapping

Inference Knowledge ¾ Fulfilled requirements ¾ Conflicting requirements/specifications ¾ Still-undecided requirements/specifications ¾ Requirements for elaborations

Trade-off analysis

New specification registration

Domain Knowledge

¾ Product Design Specifications ¾ Question lists ¾ Customer needs

Figure 3. Support System Architecture

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2.3

77

Program Approach

Figure 4 shows the proposed approach for the decision making support system. The requirement capturing process starts with an interactive market survey and finishes with a product design specification report for design engineers to use as a guideline in producing a conceptual design. Requirements from users

Elicitation of requirements from users

List of pre-stored requirements that match user inputs

Analysis of requirements to map with the pre-stored data

Users either agree or disagree with the results

Communicating results to users for validation

A library of customer requirements from previous projects and experts

Knowledge base analysis using random word match

Validated requirements go as inputs to next stage; else users are required to enter more words to expand the search

No

Validation by users

A library of product design specifications that match user requirements from previous projects and experts

Yes Elicitation of validated requirement as input for product specification mapping

List of pre-stored product specifications that match user requirements

Users either agree or disagree with the results

Validated specifications saved for reference; else users can choose to register new specifications or expand the search.

Knowledge base analysis using random word match Analysis of validated requirements to map with product specifications

No

Communicating results to users for validation

No

Validation by users

Register new specifications Yes

Yes New temporary specifications registered in database for designers to review

Evolvement of new specification

To design engineering

Legends: Flow of requirement mapping

Input/Output

Flow of input/output

Process stage

Flow of information from database/knowledge

Resource

Figure 4. Customer Requirement Capturing Approach

As a user enters a requirement, the system task will analyse whether it has any record of the same requirement by matching keywords of the requirement. It is possible that the search results in one or few records. Therefore, the user has to validate the search result to go to the next stage. Validation is required in this

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program just to make sure the system is capturing the real problem. However, if the search produces no result, then the user has to enter few more words to re-search. The validated requirement is then sent to knowledge processing of information in the database. Information kept as domain knowledge in database obtained earlier by consulting expert experience and extracting previous design records. Input from requirement engineering process will be analysed and mapped with the domain knowledge and communicated to the user for validation. The system will try to match the requirement with product specifications available by key words, but if the database has no records that match the requirement, then the user will have to choose either to restart the process or explain with few words of the specific requirement so that the system will register a new product specification for the design engineer to consider. 2.4

Support System Software

The proposed system architecture and approach will be implemented in a prototype software designed in Microsoft Access environment. This software could facilitate the requirement capturing process and generation of design specifications by design engineers. Because it constitutes the previous design information, a novice engineer will have the knowledge of experienced design engineers to help him or her in making the design decision. Once this is implemented, an existing working prototpe system entitled DeCoSolver [30] will also be used to use the technical constraints generated from this system. This combined system will enable a designer to capture precisely the customer requirements and convert them into technical specifications, and eventually used in a constraint based design problem solving.

3.

Conclusion

A decision support system can be developed to support design engineers in capturing, processing and understanding customer requirements of a certain product in order to solve the real needs of the customer. The program also stores design information from experienced design engineers and previous design records for the engineers to compare before making a design decision. This is very useful for engineers to learn from the past to avoid making a mistake that waste money, time and effort. The database may be expanded to including product competitors and design standard data

4.

References

[1] Suh, N.P., The Principles of Design. Oxford Series on Advanced Manufacturing. 1990, Oxford: Oxford University. [2] Pugh, S., Total Design. 1991, Essex: Addison-Wesley. [3] Roozenburg, N.F.M. and J. Eekels, Product Design: Fundamental and Methods. 1995, West Sussex: John Wiley and Sons.

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[4] Pahl, G. and W. Beitz, Engineering Design: A Systematic Approach. Second ed. 2003, London: Springer-Verlag. [5] Cooper, R., A.B. Wootton, and M. Bruce, "Requirement capture": theory and practice. Technovation, 1998. 18(8): p. 497-511. [6] Darlington, M.J. and S.J. Culley, A model of factors influencing the design requirement. Design Studies, 2004. 25(4): p. 329-350. [7] Globerson, S., Discrepancies between customer expectations and product configuration. International Journal of Project Management, 1997. 15(4): p. 199-203. [8] Zhu, H. and L.Jin, Scenario analysis in an automated tool for requirement engineering. Requirements Engineering, 2000. 5: p. 2-22. [9] Chen, Y.-J., et al., Developing a multi-layer reference design retrieval technology for knowledge management in engineering design. Expert Systems with Applications, 2005. 29(4): p. 839-866. [10] Chen, L.-C. and L. Lin, Optimization of product configuration design using functional requirements and constraints. Research in Engineering Design, 2002. 13: p. 167-182. [11] Corbridge, C., et al., Laddering: technique and tool use in knowledge acquisition. Knowledge Acquisition, 1994. 6(3): p. 315-341. [12] Rehman, F. and X.-T. Yan, Product design elements as means to realise functions in mechanical conceptual design, in International Conference on Engineering Design. 2003: Stockholm, Sweden. [13] Rehman, F. and X.-T. Yan, A prototype system to support conceptual design synthesis for Multi-X, in International Conference on Engineering Design. 2005: Melbourne, Australia. [14] Jiao, J. and M.M. Tseng, Fuzzy Ranking for Concept Evaluation in Configuration Design for Mass Customization. CONCURRENT ENGINEERING: Research and Application, 1998. 6(3): p. 189-206. [15] Jiao, J. and Y. Zhang, Product portfolio identification based on association rule mining. Computer-Aided Design, 2005. 37: p. 149-172. [16] Gonzalez-Zugasti, J.P., K.N. Otto, and J.D. Baker, Assessing value in platformed product family design. Research in Engineering Design, 2001. 13: p. 30-41. [17] Krishnapillai, R. and A. Zeid, Mapping Product Design Specification for Mass Customisation. Journal of Intelligent Manufacturing, 2006. 17: p. 29-43. [18] Yan, W., C.-H. Chen, and L. Pheng Khoo, An integrated approach to the elicitation of customer requirements for engineering design using picture sorts and fuzzy evaluation. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2002. 16: p. 59-71. [19] Ratchev, S., et al., Knowledge based requirement engineering for one-of-a-kind complex systems. Knowledge-Based Systems, 2003. 16(1): p. 1-5. [20] Court, A.W., Issues for integrating knowledge in new product development: reflections from an empirical study. Knowledge-Based Systems, 1998. 11(7-8): p. 391-398. [21] Harding, J.A., et al., An Intelligent Information Framework Relating Customer Requirements and Products Characteristics. Computers in Industry, 2001. 44: p. 51-65. [22] McKay, A., A. de Pennington, and J. Baxter, Requirements management: a representation scheme for product specifications. Computer-Aided Design, 2001. 33(7): p. 511-520. [23] Court, A.W., S.J. Culley, and C.A. McMahon, Information Access Diagrams: A Technique for Analyzing the Usage of Design Information Journal of Engineering Design, 1996. 7(1): p. 55-75. [24] Kroll, E., S.S. Condoor, and D.G. Jansson, Innovative Conceptual Design: Theory and Application of Parameter Analysis. 2001, Cambrige: Cambridge University Press. [25] Daugulis, A., Time Aspects in Requirements Engineering: Or 'Every Cloud Has A Silver Lining'. Requirements Engineering, 2000. 5(3): p. 137-143.

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[26] Finlay, C., Product Design Project Final Report: Domestic Cooker Fire Suppression System. 2001, University of Strathclyde: Glasgow. [27] McCall, J., Product Design Project 1: Design A Bicycle Learning/Assisting Device. 2005, University of Strathclyde: Glasgow. [28] Spears, A.J., Electronic Shelf Edge Label, in Appendices. 2001, University of Strathclyde: Glasgow. [29] Brockett, A., The Use of Product Specifications in Industry 2007, University of Strathclyde: Glasgow. [30] Yan, X. T. and Sawada, H A Framework For Supporting Multidisciplinary Engineering Design Exploration And Life-Cycle Design Using Under-Constrained Problem Solving, in Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Cambridge University Press, 2006, Vol. 20, Issue 4, pp 329-350.

Comparison About Design Methods of Tonpilz Type Transducer Duo Teng , Hang Chen, Ning Zhu, Guolei Zhu, Yanni Gou Marine College of Northwestern Polytechnical University, Xi’an, 710072, China

Abstract A Tonpilz type piezoelectric ceramic ultrasonic transducer is investigated through the methods of equivalent circuit and finite element analysis(FEA). The emphasis of this paper lies in the difference between the two methods. Essentially, the piezoelectric constitutive equation is the common law of them. Derived from this equation, the Mason’s equivalent circuit and the frequency equation of the piezoelectric transducer is obtained, and then the finite element control equation is obtained. A mason’s equivalent circuit model and a 1/4 symmetry finite element model of the Tonpilz type piezoelectric ceramic ultrasonic transducer are both constructed. A comparison about the frequency performance and the admittance performance which are respectively obtained from the two methods and the corresponding test shows that, the method of FEA is more quickly and accurately, and its analysis error is controlled within 5%. What is worth to mention is that some performance and the vibration of the transducer have been predicted distinctly through FEA. So FEA is suitable to the piezoelectric transducer. A transducer prototype which is made according to the analysis result has a good performance and satisfying applied requirements. Keywords: transducer, piezoelectric ceramic, ultrasonic, equivalent circuit, finite element

1. Introduction The piezoelectric ceramic ultrasonic transducer is an electroacoustic device, which utilizes both the piezoelectric and reverse piezoelectric effect to transform energy between ultrasonic and electrical. Such devices have broad applications in ultrasonic medicine, non-destructive testing, oil prospecting well and ocean military[1]. The sensitive element of piezoelectric transducer is some special smart material like piezoelectric ceramics which can translate electrical to mechanical energy and mechanical to electrical energy[2]. Piezoelectric ceramics have the piezoelectric and reverse piezoelectric effect only after polarization processing. The piezoelectric effect causes a crystal to produce an electrical potential when it is subjected to mechanical vibration. In contrast, the reverse piezoelectric effect causes the crystal to produce vibration when it is placed in an electric field. In present, there exist many theory models to design such piezoelectric devices. Here,

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a Tonpilz type piezoelectric ceramic ultrasonic transducer is investigated. The design methods of Mason’s equivalent circuit and finite element analysis (FEA) are described in the following. A comparison of the analysis results shows that the method of FEA is more efficient.

2. Equivalent Circuit Theory of Tonpilz Type Piezoelectric Ceramic Ultrasonic Transducer Tonpilz means mushroom in German. A so-called Tonpilz type transducer has the structure like a mushroom, which is also called as compound bar transducer. Generally, it is made of a piezoceramic ring stack between a head mass and a tail mass, prestressed by a central bolt. Traditionally, piezoceramic has been used as the active material and the head mass has been used to transmit or receive acoustic energy. A schematic diagram is shown in Figure 1.

Figure 1. A Schematic Diagram of the Tonpilz Type Piezoelectric Ultrasonic Transducer

The piezoelectric constitutive equation is used to model piezoelectric materials mathematically. It describes the relationships of the material's properties, such as mechanical problem (elasticity), the electrical problem(dielectric) and piezoelectricity [3]. There are four possible forms for piezoelectric constitutive equations according to the different boundary conditions[4]. The following is the second one which is suitable to the condition of mechanically clamped(S=0,c᧷ T0,c) and short circuit(E=0,c᧷D0,c).

T ªc E º S e c E °> @ ¬ ¼ > @ > @ > @ ® ª sº ¯° > D @ > e@ > S @ ¬H ¼ > E @ where [S]=strain vector, [T]=stress vector,

(1)

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[E]=electric field vector, [D]=electric displacement vector᧷ [cE]=stiffness coefficients matrix, a symmetric matrix. The superscript E means that the data is measured at constant electric field, i.e. short circuit(E=0,c; D0,c). [İS]=dielectric matrix. The superscript S means that the data is measured at constant strain field, i.e. mechanically clamped(S=0,c; T0,c). [e]=piezoelectric stress matrix Derived from the piezoelectric constitutive equation and the wave equations under certain boundary conditions, the equivalent circuit for the piezoelectric transducer is obtained. The result is show in Figure 2.

Figure 2. the Mason’s Equivalent Circuit of the Tonpilz Type Piezoelectric Ultrasonic Transducer

where C0=Static Capacitance, ĳ=mechanical-electrical conversion factor, ȡ=density, c=velocity of sound, k=wavenumber, S=area of cross section, l=length, The subscript f means the head mass, the subscript c means the piezoceramic ring stack, and the subscript b means the tail mass, respectively. When an electric field excitation is applied to drive transducer to vibrate, there exists a so-called non-moving plane (shown in Figure 1) someplace in the piezoelectric ceramics stack. The vibration velocity on this plane is zero. Separated by the plane, two parts are appeared, and then the acoustic energy is transmitted through two contrary ways. Derived from the equivalent circuit, each part has itself frequency equation:

tg (kc lc1 )

Uc cc Sc ctg (k f l f ) U f cf S f

(2.1)

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tg (kc lc 2 )

lc

Uc cc Sc ctg (kb lb ) Ub cb Sb

lc1 lc 2

(2.2)

(2.3)

The above frequency equation can determine the operation frequency of the transducer, and some other important performance parameters also can be obtained from the equivalent circuit [5].

3. Finite Element Analysis of Tonpilz Type Piezoelectric Ceramic Ultrasonic Transducer The finite element method (FEM) is effective to design piezoelectric transducer. It is a numerical method by discretizing the whole system into finite elements. The program implements equations, which govern the behavior of these elements, and solves them all, and then creates a comprehensive explanation of how the system acts as a whole. FEM is typically used for the design and optimization of a system which is too complex due to their geometry, scale, or governing equations to analyze by hand. Compared with the other theory models of piezoelectric transducer, the large-scale assumption is not necessary for FEM. No matter how complex the transducer is, or no matter what its boundary condition is, the FEM is more effective both in computation speed and in computation accuracy. ANSYS is one of the most famous commercial finite element software. A piezoelectric analysis in ANSYS need to handles the interaction between the structural and electric fields. Some coupled field element type with piezoelectric capabilities which can activate the necessary piezoelectric degrees of freedom, displacements and VOLT, are offered in ANSYS, such as PLANE13, SOLID5, SOLID98. The procedure of coupling is handled by calculating element matrices or element load vectors that contain all necessary terms. Such piezoelectric analysis is only available in the ANSYS Multiphysics or ANSYS Mechanical products. The possible analysis types are static, modal, prestressed modal, harmonic, prestressed harmonic, and transient. Static analysis can be used to determine the stresses and strains in transducer with prestressed bolt. Modal analysis can be used to determine the operation frequencies and mode shapes of a transducer, also applied on a prestressed structure. Harmonic response analysis gives us the graph of some response quantity versus frequency near the resonance frequency of transducer, i.e., admittance, bandwidth, efficiency, and even acoustic radiated field can be obtained, where the admittance curve is the most significant performance to determine the transducer. The control equation for linear material behavior in ANSYS is the following:

>M @ >ut @ >C @ >u t @ >K @ >u t @ >F t @

(3)

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where [u(t)]= nodal displacements vector, [M]= mass matrix [C]= damping matrix, [K]= stiffness matrix [F(t)]= nodal force vector, it determines the analysis types [6]. Equation 1 is selected by ANSYS to solve the coupled-field analysis on the structural and electrical fields. After the application of finite element discretization, the coupled finite element matrix equation derived for a one element model is given as the following:

>K @º ª>u@º ª>F@º > @ > @ >K @»¼ «¬>V @»¼ «¬>L@»¼

ª>M @ >0@º ª>u@º ª>C@ >0@º ª>u@º ª >K @ « >0@ >0@» « V » « >0@ >0@» « V » « Z T ¬ ¼ ¬ ¼ ¬ ¼ ¬ ¼ ¬K

>@

Z d

(4)

where [u]=vector of nodal displacements, [V] =vector of nodal electrical potential, [KZ]=piezoelectric coupling matrix, [Kd] =dielectric conductivity, [L]=electrical load vector.

Figure 3. 1/4 symmetry model of the Tonpilz Type piezoelectric ceramic ultrasonic transducer

The 1/4 symmetry finite element model of a Tonpilz type piezoelectric ceramic ultrasonic transducer is shown in Figure 3. The piezoelectric ceramic component of transducer is defined as SOLID5 element by setting Keyopt(1)=3 to active the piezoelectric degrees of freedom, ux, uy, uz and volt. When modeling, we should input the right material properties to define the polarization direction aligned along the z axis. Noticeably, the input order must follows the ANSYS standards[7], which is different from IEEE standards[8]. The other components such as

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prestressed bolt, radiating head, tail mass are also defined as SOLID5 element by setting Keyopt(1)=2 to only active the displacement degrees of freedom, ux, uy and uz. The adhesive layer will be ignored in this model.

4.

Experiment and Comparison

The analysis on Tonpilz type piezoelectric ceramic ultrasonic transducer has been finished through the methods of equivalent circuit and FEM. The admittance curves in air obtained from equivalent circuit and ANSYS are shown in Figure 4 and Figure 5 respectively, while the experimental curve illustrated in Figure 6 is obtained from Agilent4294A(a precision impedance analyzer which can immediately give some electric parameters within the certain frequency range, i.e., impedance, admittance, and capacitance). We can find that the Figure 4 and 5 have the similar shape to the Figure 6, and the magnitude and the resonance frequency of the above 3 curves are in approximately agreement. When analyzing the admittance curve in ANSYS, a damping ratio assigned to the components of transducer is important. Figure 7 gives a displacement vector plot at resonance frequency, which shows that the transducer is a longitudinal vibrator (Tonpilz type). A comparison of the frequency performance obtained from the methods of equivalent circuit and ANSYS with the one obtained from the test is listed in Table 1. The error about the method of equivalent circuit is controlled within 10%, while the finite element analysis error is only within 5%. Some transducer prototypes have been made according to the design result. The maximum size of radial direction is within (9 h 9)mm, and the maximum size of longitudinal direction is within 11mm. The photo is shown in Figure 8.

Figure 4. Admittance Circle Curve Obtained from equivalent circuit in Air (resonance frequency: 132.4kHz)

Comparison About Design Methods of Tonpilz Type Transducer

Figure 5. Admittance Circle Curve Obtained from ANSYS in Air (resonance frequency: 146.3kHz)

Figure 6. Admittance Circle Curve Obtained from Test in Air (resonance frequency: 141.6kHz)

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Figure 7. Displacement Vector Plot at resonance frequency(obtained from ANSYS)

Figure 8. Photo of Piezoelectric Ceramic Ultrasonic Transducer Prototype Table 1. A comparison of the analysis results with the results obtained from the test Frequency(kHz)

Test

Equivalent Circuit

Ratio1

ANSYS

Ratio2

resonance

141.6

132.4

0.935

146.334

1.033

anti-resonance

159.0

173.6

1.092

166.652

1.048

Note: Ratio1

ANSYS Equivalent Circuit , Ratio2= Test Test

Comparison About Design Methods of Tonpilz Type Transducer

5.

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Conclusion

A Tonpilz type piezoelectric ceramic ultrasonic transducer has been designed through the method of equivalent circuit and finite element analysis. Its performance and vibration have been predicted. A comparison about the frequency performance and the admittance performance which are respectively obtained from the two methods and the corresponding test shows that, the method of FEA is more quickly and accurately, and its analysis error is controlled within 5%. What is worth to mention is that some performance and the vibration of the transducer have been predicted distinctly through FEA. So FEA is suitable to the piezoelectric transducer. A transducer prototype which is made according to the analysis result has a good performance and satisfying applied requirements.

6.

Acknowledgement

This project is supported by Marine Industry Foundation for National Defense of China (No.05J5.8.2)

7.

References

[1] JIA Baoxian, BIAN Wenfeng. Application and Development of Piezoelectric Ultrasonic Transducers. PIEZOELECTRIC AND ACOUSTOOPTICS, 2005.8, 27 (2): 131–135. [2] Ernard Jaffe,William R Cook,Hans Jaffe. Piezoelectric Ceramics: Principles and Applications. APC International Ltd. 2000. Chapter 1 [3] B. Jaffe, W. R. Cook Jr and H. Jaffe. Piezoelectric Ceramics. Science Press, 1979.6: 6– 19. [4] LIN Shuyu. Theory and Design about Ultrasonic Transducer. Science Press, 2004.6: 17–20. [5] ZHOU Fuhong. Underwater Transducer and Array. National Defence Industry Press, 1984.12: 72–82. [6] Peter Koh ke. ANSYS Coupled-Field Analysis Guide, Release 5.5. ANSYS, Inc., September, 1998. [7] Sheldon Imaoka, Conversion of Piezoelectric Material Data. Collaborative Solutions Inc. November 12, 1999. [8] ANSI/IEEE Std 176-1987, An American National Standard IEEE Standard on Piezoelectricity, 1987. [9] Gilder Nader, Emilio C. N. Silva and Julio C. Adamowski. Determination of Piezoelectric Transducers Damping by Using Experimental and Finite Element Simulations. Smart Structures and Materials 2003: Damping and Isolation, 2003, Proc. of SPIE Vol.5052: 116–127.

Effect for Functional Design Guozhong Cao1, Haixia Guo2, Runhua Tan1 1

School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300130, P.R. China 2 Library of Hebei University of Technology, Tianjin, 300130, P.R. China

Abstract Functional design plays the central role in ensuring design quality and product innovation. This paper proposes a functional design approach which is supported by effects in TRIZ (Theory of Inventive Problem Solving). The relationship among function, flow and behavior are discussed. Based on six effect-chain modes and three reasoning methods, multiple effect chains that produce the same output can be generated by effects, which can help engineers achieve breakthrough innovation by proposing new and unexpected variations in producing a specific output. A design example for functional design of a Chinese medicine mechanism is presented to demonstrate the proposed functional design methodology. Keywords: TRIZ, Effect, Functional Design

1.

Introduction

Functional design in engineering design research theory is a well-researched and active field of engineering study. All functional design begins by formulating the overall product function. By breaking the overall function of the device into small, easily solved sub-function, the form of the device follows from the assembly of all sub-function solutions [1]. Functional design plays the central role in ensuring design quality and product innovation. There are various, often conflicting, definitions of function in the literature; no universally accepted definition is currently known, such as, designer’s purpose [2, 3], intended behavior [4], an effect on the environment of the product [5], a description of behavior recognised by a human through abstraction in order to utilize it [6] or a relationship between inputs and outputs, aiming to achieve the designer’s purpose [7]. Clearly, each of these definitions has some aspects of worth, yet none are comprehensive enough to capture the fullness of definition that is desired. Researchers have recognised the importance of a common vocabulary for broader issues of design. Pahl and Beitz [7] list five generally valid functions and three types of flows. Collins et al. [8] develop a list of 105 unique descriptions of mechanical function. Hundal [9] formulates six function classes with more specific

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functions in each class. Stone et al. [1] lists over 130 functions and over 100 flows. TRIZ describes all mechanical design with a set of 30 functional descriptions [10]. One of the most well-known functional design frameworks is that of Pahl & Beitz [7], i.e., systematic approach, which model the overall function and decompose it into sub-functions operating on the flows of energy, material, and signals. Umeda et al. [6] proposed a Function-Behavior-State (FBS) modeler that reasons about function by means of two approaches: causal decomposition and task decomposition. Deng et al. [11] devised a dual-step function-environmentbehaviour-structure (FEBS) model. There are other similar approaches for functional models, for example, Qian and Gero’s [2] FBS Path, and Prabhakar and Goel’s [3] ESBF model. The lack of a precise definition for functions and different functional models of product generated by different designers cast doubt on the effectiveness of prescriptive design methodologies. During functional design the design knowledge in multiple different domains may be employed, and complicated developing activities may be also involved. At the present, a unifying model of functional design has not yet arrived. TRIZ is a problem solving methodology based on a systematic logic approach that was developed from reviewing thousands of patents and analysis of technology evolution. TRIZ can be used as a powerful intellectual instrument to solve simple and difficult technical and technological problems more quickly and with better results. According to Altshuller’s patent search, for any given problem, there is more than a 90% of chance that a similar problem has already been addressed somewhere, at some time [10]. Effect is one of the knowledge base tools in TRIZ. By the analysis of hundreds of thousands patents, effects are emerged from the relevance between behaviors delivered by a design product described in a patent and a principle used in the product [10]. To push functional design into the realm of repeatable and computational, this paper proposes an automated functional design tool that utilizes six effect modes and the existing effect knowledge base to generate functional model. This tool can produce numerous feasible principle solutions in conceptual design process.

2.

Function and Behavior

Function is a statement to describe the transformation of input/output flows, aiming to achieve the designer’s purpose. Function is expressed as verb. Malmqvist et al. [12] compare TRIZ with the Pahl and Beitz methodology and note that the detailed vocabulary of TRIZ would benefit from a more carefully structured class hierarchy using the Pahl and Beitz functions at the highest level. The 30 functions in TRIZ are expanded and reclassified and the standard set of functions is presented, which is a list of functions, sub-functions and synonymies, as shown in Table 1. The object moving between functions is called a flow, which is divided into matter, energy and information flows based upon the work by Pahl and Beitz [2]. These three flows are considered basic concepts in any design problem. Matter is better represented as material. Information is more concretely expressed as parameters

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because they are the contents of information. Flow is expressed as noun. The flows, sub-flows and complements are shown in Table 2. The input and output of one system associate with other technical system, person or natural system, and each flow is identified by its source and destination systems. In order to distinguish different flows, each flow contains a set of attributes to describe its state, which belongs to an attribute domain. The attribute of flow can be divided into physical, chemical and geometrical attribute, etc. Based on the attributes, two flows are said to be different if their attributes are not the same. Table 1. Short list of function set Function

Sub-function

Create

Synthesize, Produce

Change

Increase, Decrease, Convert, Form, Control

Combine

Mix, Embed, Assemble, connect

Separate

Disassemble, Decompose, Dry, Clean

Accumulate Absorb, Store, Concentrate Move

Move, Transfer, Rotate, Vibrate, Lift, Orient

Measure

Determine, Detect, Measure

Preserve

Preserve, Prevent, Stabilize

Eliminate

Destroy, Remove Table 2. Short list of flow set

Flow

Sub-flow

material

Solid, Liquid, Gas, Geometric objects, Loose Substances, Porous Substances, Particles, Plasma, Chemical Compounds

energy

Forces, Motion, Deformation, Thermal Energy, Mechanical and Sound Waves, Electric Field, Magnetic Field, Nuclear Energy, Electromagnetic Waves or Light

Parameters

Solids Parameters, Surfaces Parameters, Geometric Parameters, Deformation Parameters, Fluids Parameters, Concentration Parameters, Chemical Parameters, Forces Parameters, Motion and Vibration Parameters, Process Parameters, Thermal Parameters, Mechanical and Sound Waves Parameters, Electric field Parameters, Magnetic field Parameters, Radioactivity Parameters

Behavior is a causal relationship between input and output flow. Input flow, transformation and output flow are three primary elements of a behavior.

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Function is an abstracted and subjective representation of behavior, and behavior is a physical interpretation of function. The difference in function and behavior only lies in the identification of their input and output. The overall function can be decomposed into sub-functions operating on the flows of energy, material, and parameters. The functions are classified by input and output flows. The function types derived from the relationship between input/output flows identify the behavior. The behavior, which characterizes the implementation of function, is called external behavior. As with most complex system, it is generally good to break large external behavior down into smaller and more easily sub-behaviors. An internal behavior is a sequence of alternating subbehaviors and sub-behaviors transitions, which represents the achievement way of external behavior.

3.

Effect and Effect Chain

3.1

Effect

Effects are the laws of science including physics, mathematics, chemistry and geometry, and their corresponding engineering applications, which helps to bridge the gap between science and engineering. Effects can be characterized by its input, output relations [13]. Generally speaking, an effect has an input and output flow, which is called as basic effect, thus the effect model has two poles, as shown in Figure 1(a). Most transitions from input to output with effect are controlled by auxiliary flow, so the controllable effect should be denoted with three poles, as shown in Figure 1(b). The control flow specifies the factors that can be manipulated to change the output intensity of an effect. Thereby, an effect may have multiple input poles, output poles or control poles. Effect (a) Effect model with two poles

Effect (b) Effect model with three poles

Effect Input Flow Output Flow Control Flow

Figure 1. Effect model

3.2

Effect Mode (EM)

Effects can fulfill transition from inputs to output, namely, the happening of subbehaviors depends upon effects. Effects can be connected to one another through its input or output ports and compatible relationships among adjacent effects, which confirm causal relation and structural relation of sub-behaviors. The internal behavior can be achieved by the following effect modes, in which the directed link represents one or several flows.

Effect for Functional Design

x x x x x x

95

Single effect mode: achieve an internal behavior by an effect, as shown in Figure 1(a). An effect can fulfill several behaviors. A behavior can be fulfilled by several effects respectively. Serial effect mode: achieve an internal behavior by a set of effects occurring in sequence, as shown in Figure 2(a). Parallel effect mode: achieve an internal behavior by a set of effects occurring at same time, as shown in Figure 2(b). Ring effect mode: achieve an internal behavior by a set of effects, and the output of later effect is transported to the former effect, as shown in Figure 2(c). Control effect mode: the internal characteristic of an effect can be controlled by other effects in order to control the achievement mode of internal behavior, as shown in Figure 2(d). Combined effect mode: achieve an internal behavior by several above effects modes.

Figure 2. Effect modes

3.3

Effect Chain

The effects can be linked into an effect chain by using effect mode. Multiple effect chains that produce the same output can be generated, allowing you to then select the chain that best fits your available resources and interrelated constraints. To generate an effect chain, only those effects where the output flow matches the input flow of the next one can be linked. The consistency between output flow of the first effect and input flow of the next one can be denoted by Dc (Degree of consistency). Supposed there are m attributes in required output flow, and there are n attributes in produced output flow which satisfy the attributes in budget output flow (nm). Dc can be shown as: Dc

n u 100% m

(1)

The effects chosen for an effect chain must be compatible with each other, that is, the name of output flows of the first effect must be same as that of input flow of the next one and Dc =100%.

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During the transformation from input flow to out flow by effect mode, there are three methods, namely, method of exhaustion, method of minimal path length and method of consistent degree. x Method of exhaustion If times of transformation from input flow to out flow are unlimited, there will be theoretically uncountable effect chains which produce the same output. Figure 3 shows two reasoning model for effect chain: forward direction reasoning model and backward direction reasoning model. tr

fi

1

Name: fpo = fq fpo1 Effect

fi

fi 3

xxx

P 1

fpo1 Effect

2

Dc =100%

fpo2 Effect

fpo1

2 fpo2

Effect

Effect

3 xxx

xxxxxx

(a) Forward direction search reasoning model Name: fpi = fi

tr

Dc =100% fpi1

fq Effect

1 fpi2

fpi2

fpi3 Effect

fq Effect

2

fpi1 Effect

P 1

fpi1 Effect

2

3

fp3 Effect

fq Effect

3 xxxxxx

xxx

xxx

(b) Backward direction search reasoning model fi fpi p

input flow fq producted iutput flow fpo path length tr

required output flow producted output flow reasoning times

Figure 3. Reasoning model for effect chain

Method of exhaustion can produce multiple effect chains in large-scale effects, which offer various potential principle solutions and are helpful for product innovative design, but the computational of method of exhaustion is complex and inefficient.

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x Method of minimal path length In principle, the numbers of effects that consist of effects chains can be chosen according to user discretion. But the effects chains should be as short as possible in order to obtain a simple system. The path of between two flows can be identified by method of exhaustion. The minimal path length (pm) is the minimum value of path length of transformation between two flows. The knowledge of minimal path length (kp) is presented by input flow (fi), output flow (fo) and minimal path length (pm), as shown in the following:

kp

{ f i , f o , pm }

(2) For example, {E, ǻl, 1} denotes that the minimal path length from electric field (E) to length change (ǻl) is one (by electrostriction effect). Designers can rapidly achieve transformation from input flow to required output flow by the knowledge of minimal path length (kp). The method is high performance, but maybe the effect chain couldn’t satisfy the requirement. x Method of consistent degree In the method of exhaustion, every reasoning produces various effects. If degree of consistency (Dc) between produced output flow of an effect and required output flow or between produced input flow of an effect and input flow is figured out, the produced output/input flow whose Dc is maximum can be identified and used as new input/output flow and carry through the next reasoning. Thus the method of consistent degree is more effective than the method of exhaustion.

4.

Functional Design Based on Behavior and Effect

By analogy-based design (ABD) [14], one existing but appropriate design can be introduced into the current design, and the former successful effects and structures in examples can be transferred to the new design. The process of functional design can be seen as transforming a functional representation to a design description or physical representation through behavior, effect and Structure, as shown in Equation (3). Design begins with the analysis of functional requirements (Q), and then determines the product function (f) in standardized set of functions. The behavior can be identified by function type (FT). The relations among input flow, transformation and output flow imply the external behavior (be), and the causal relationship (r) among sub-behaviors (bs) based on effect (e) and effect modes (EM) is to support functional realization. Structures (S) exist according as effects (e) and structures are physical entities of effects. The mapping from function to structure is realized based on effect. Based on the functional design process, the Computer-Aided Innovation Software (InnovationTool 3.0) is developed [15], which will help the designer create new concepts by combining one or more effects to accomplish design objectives and improve the original effect’s performance. Given Q Q f = IdentifyForm (Q), f F

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B= IdentifyForm (FT) be B, be o f R = IdentifyForm (EM), R B×B r = (bsi×bsj)R S = IdentifyForm (e) o bs bi = < bs, r >, bi o be, such that Sof

5.

(3)

Case Study

Pill is a kind of good form of Chinese traditional medicine, but it can not be produced by Western medicine facility for its process and physics characteristic. The present condition is long process and high energy consumes and great labor intensions, so it is important to develop continue forming and shorten process to meet the need of modern times. The granulator system can be initially modeled as a black-box in Figure 4, whose inputs are powder (medicinal powder) and liquid (cementing liquid), and whose outputs are sphericity and particle (pill). Powder Liquid

Overall Function

Sphericity Particle

Figure 4. Black-box model of granulator system

According to the known inputs and outputs, search for the effects by forward direction reasoning model or backward direction reasoning model. In order to shorten manufacturing process of pill, the reasoning times is set as three (tr =3). The effects can be automatically linked into effect chains by using effect modes. Figure 5 shows the part of effect chains of granulator system, which are mainly based on fluidized bed effect, vibration effect, plastic deformation effect, shear effect, friction effect and Pascal’s effect. Figure 6 shows the corresponding principle solutions. The principle solution d2 is identified by forming of the comparison matrix of AHP. The solution structure of granulator system is shown in Figure 7.

Effect for Functional Design

Sphericity

Powder Liquid

Fluidized Bed Effect

Powder Liquid

(a)

Plastic Deformation Force Effect

Ointment Vibration Effect

Powder Liquid

Particle Ointment

Vibration Effect

Powder Liquid

99

Force

Ointment Vibration Effect

Force

Plastic Deformation Effect Plastic Deformation Effect

Medicinal strip Force

Sphericity Shear Effect

Medicinal strip Force

(b)

Cylinder Shear Effect

Medicinal strip Force

Particle

Particle

Sphericity Pascal’s Effect

Cylinder Shear Effect

Particle

Particle

(c)

Sphericity Friction Effect

Particle

Figure 5. Effect chains of granulator system

(a)

(b, c, d)

(b)

(c)

(d1)

Figure 6. Principle solutions based on effect chains

(d2)

(d)

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Figure 7. Principle solutions of granulator system

6.

Conclusion

Functional design is a process in conceptual design that impacts the key features of the design result. How to map from function to structure and how to describe completely and reason effectively design concepts are crucial issues in conceptual design phase. This paper proposes an automated functional design approach which provides good support for product functional design by the followings: x Effect chains can be generated by effects based on six effect modes; x Many principle solutions are identified through method of exhaustion, method of minimal path length and method of consistent degree; x Based on effect modes, the Effect Module in computer-aided innovation design software InventionTool 3.0 has been developed, and the existing effect knowledge base is established. A design example for functional design of a Chinese medicine mechanism is presented to demonstrate the proposed functional design methodology and prove that the method is feasible.

7.

Acknowledgments

This research is supported in part by the Natural Science Foundation of China under Grant Numbers 50675059 and the National High Technology Research and Development Program of China under Grant Numbers 2006AA042109.

8.

References

[1] Stone RB, Wood KL, (1998) Development of a functional basis for design, Transactions of the ASME, Journal of Mechanical Design, 122(4):359-370 [2] Qian L, Gero JS, (1996) Function-Behavior-Structure Paths and their Role in Analogybased Design, AIEDAM, 10:289-312 [3] Prabhakar G, Goel A, (1998) A functional modeling for adaptive design of devices in new environments, Artificial Intelligence in Engineering Journal (Special Issue), 12(4): 417-444

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[4] Shimomura Y, Takeda H, et al., (1995) Representation of Design Object based on the Functional Evolution Process Model. DTM’95-ASME [5] Chandrasekaran B, Kaindl H, (1996) Representing Functional Requirements and Usersystem Interactions. AAAI Workshop on Modeling and Reasoning about Function, pp.78-84 [6] Umeda Y, Ishii M, Yoshioka M, et al., (1996) Supporting Conceptual Design Based on the Function-Behavior-State Modeler, Artificial Intelligence for Engineering Design, Analysis and Manufacturing: Aiedam, 10(4): 275-288 [7] Pahl G, Beitz W, (1996) Engineering Design – A Systematic approach, The 2nd Edition, Springer-Verlag, London [8] Collins J, Hagan B, Bratt H, (1976) The Failure-Experience Matrix - a Useful Design Tool, Transactions of the ASME, Series B, Journal of Engineering in Industry, 98:1074-1079 [9] Hundal M, (1990) A Systematic Method for Developing Function Structures, Solutions and Concept Variants, Mech. Mach. Theory, 25(3):243-256 [10] Altshuller G, (1999) The Innovation Algorithm, TRIZ, Systematic Innovation and Technical Creativity, Technical Innovation Center, INC, Worcester [11] Deng YM, Tor SB, Britton GA, (2000) Abstracting and exploring functional design information for conceptual product design, Engineering with Computers, 16:36-52 [12] Malmqvist J, Axelsson R, Johansson M, (1996) Comparative Analysis of the Theory of Inventive Problem Solving and the Systematic Approach of Pahl and Beitz, The 1996 ASME Design Engineering Technical Conference and Computers in Engineering Conference, Irvine, CA [13] Runhua Tan, (2002) Innovation Design—TRIZ: Theory of Innovative Problem Solving, China Mechanic Press. (In Chinese) [14] Goel K, (1997) Design, analogy, and creativity”, IEEE Expert, 62-70 [15] Runhua Tan, Jianhong Ma, Guozhong Cao, (2006) Computer-aided innovation software system: InventionTool 3.0, Software Registration Number: 2006SR13729

Quality Control of Artistic Scenes in Processes of Design and Development of Digital-Game Products P.S. Pa, Tzu-Pin Su Graduate School of Toy and Game Design, National Taipei University of Education, Taipei, Taiwan, ROC, No.134, Sec. 2, Heping E. Rd., Taipei City 106, Taiwan, (R.O.C.), [email protected], [email protected]

Abstract A new force on the scene discovered a huge business opportunity in the Internet world and has received much attention – the online game publishing industry. Therefore, numerous papers discussing the realm of games have been published in recent years, but the scope of this research is mainly on the marketing development of game titles, the performance of program design and the discussion of educational value. The number of papers dwelling on the evaluation of key points to take note of the sophisticated and numerous procedures in the processes of digital-game product development is still very limited. However, with the advancement of technology, the scale of game development projects has been growing rapidly in recent years. A huge increase in the artwork required means increased difficulty in the relevant quality management. In light of this, the bulk content of this research is focused on the production quality and evaluation of artistic objects over the course of game development. Sheets of evaluation and validation that have been put to use in actual processes are the subjects of study and they are used in our analysis. By introducing the proposed work processes into actual developmental work, we have proven that the proposed model can offer effective quality management and increase effective production capacity by more than 40%. The proposed model of process in the study will help to improve the efficiency of R&D work for the entire video game industry. Keywords: Quality Control, Design and Development, Online Game, DigitalGame Products, Artistic Object

1.

Introduction

Since the year 2000, the entire world has suffered from when the economic bubble of the Internet burst, leaving a significant impact on Internet ecology. However, a new force on the scene has discovered a huge business opportunity in the world of the Internet and received much attention – the online game publishing industry. In light of this, an increasing number of papers discussing the realm of games have been published in recent years. Nonetheless, most of them were focused on either product marketing/development or elaborated on the educational value of games

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[1-2]. However, the game publishing industry is a highly paradoxical compound domain [3]; it requires the gathering of diverse talents, knowledge and techniques, together with minute and complex processes along with a mixture of rational and irrational elements to create an outstanding game title [4]. Along the process, there exist many conflicting minor details [5] that are usually difficult to solve by following standard software development processes. For example, if a commercial software application is chosen as the main development tool, then software efficiency and performance are given top priority [6]; software with good efficiency is considered good software. But when it comes to developing game software, many other extra factors need to be taken into account, such as aesthetic perspective. For an object in a game, its producer, programmer, artist and even the end user may have similar and yet varying artistic expectations [7]. This is not a strange phenomenon in the video game industry and it is difficult to come to an argument that is considered to be most accurate because a clearly defined standard for passing good/poor judgment is non-existent. When such problems arise, usually the decision maker at the end, i.e. the supervisor of the art division or chief producer of the project makes the final call. The type of decision made is usually dependant on the resources available; and in this case, it often refers to the hardware limitation of the game platforms. In the developmental process of an online game, reaching a compromise with reality is often the answer to solve irrational questions [8] because creating the perfect game can only be thought of as a spiritual accomplishment or an ideal that may not meet practical cost-effective requirements. This is why spreading out clearly defined items at the beginning phase of any development plan in preparation for the potential conflicts that may arise later on has become one of the essential tasks [9]. The construction and development of information systems have become tremendously difficult due to factors such as scale, resources, manpower, experience, etc. Therefore, even in the United States, only 32% of all IT projects were able to close unhindered. Small and medium sized companies with dated project construction technologies suffer from an even lower success rate due to the lack of strict and well-structured construction methods [10]. The knowledge and technological level involved in game development have long progressed beyond the scope of pure “playing”; the most emblematic example would be online games. Having participated in the development of major titles like Meridian 59 and Ultima Online 2. Damion Schubert said, “Today, pretty much all online games have big budgets. But when you review your budget, you have to make sure that your budget is focused on content; be it artwork or construction of the world in the game. To create a realistic world, you need to deal with a massive amount of content in your game. Even if you have a big budget, if you are not focused on the content of the game, then your programmers may be creating high-risk products that are overcomplicated and difficult to be released for open Beta tests [11]. When a game design project is forced to restrict the imaginative creativity with effective management approaches, elements that are difficult to be normalized [12] (referring to all the artistic objects), the commonly adopted Waterfall Model in the development of common software projects can only offer basic planning and management capabilities but is unable to respond to the variables that may spring up at any time during the course of game development [13]. The Waterfall Model

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is suited for commercial software that only requires each unit to complete the required tasks on schedule to ensure the whole project can go smoothly, but this model is far from being practical in the video game industry. In fact, developers tend to rely on the Spiral Model [14] more in game development to ensure better results. The addition of every new object and new function may become an extra load on the program in terms of software and hardware, and it takes experience on the developers’ part to avoid these negative effects. Therefore, numerous small and medium game developers have been working towards this goal over the repeated process of production, testing and modifications. With regards to the Software Development Life Cycle Model (SDLC) and the descriptions for the required key documentation, IBM has provided a structuralized descriptive framework in the 80s: the ETVX (Entry/Task/Verification/Exit) model. It is used to describe the life cycle model of the entire software development process and the corresponding procedures and tasks at every stage so that developers will be able to have a very good grasp of the software development framework for the entire project. The ETVX model can be said to be a framework that takes quality as the basic premise to establish all the processes in the later stages. The model has incorporated the “Plan-Do-Check–Action” concepts for quality in all work procedures. The “Verification” step within this model deals with the actual application in the art management of a game’s developmental processes. It is a delicate matter because defining a clear management standard for artwork is difficult, and that will be the content discussed in this study.

2.

Research Methods

The ETVX framework includes the six following steps of actual implementations: Inputs: this represents all the entries that can be inputted at this phase, including requirement specifications, contracts, PEP and so forth. Entry or Entry Criteria: the necessary conditions that must be met before any procedures can begin at this phase, such as the approval of contracts, RFP approved by supervisor, the standards for evaluation, etc. Task: the tasks that need to be executed or completed at this phase. For instance, planning the SOW (Statement of Work), the requirement specifications, recommendations and so forth. Validation: the methods of validation for tasks that have been completed, i.e. the evaluation of documentations, the examination of contracts, the testing of software, etc. Exit or Exit Criteria: the necessary conditions that must be met at this phase, such as the signing and filing of contracts, the examination and publishing of specifications, the testing and release of software, etc. Outputs: the possible output items at this phase, such as contracts, recommendations, specifications, reports, etc. In the processes of game products development for any title, a complete Game Design Document (GDD) will usually come along with an Art Design Document (ADD). If the development is of a smaller scale, the ADD may simply be presented in brevity within the GDD itself. For a larger scaled development project, such as

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an online game, then an independent and comprehensive ADD is absolutely necessary. The complete ADD contents should include the following as illustrated in Table 1. In this research, authors will discuss the contents of model regulations and scenario regulations. The principle behind these regulations works in the following scheme (see Figure 1). Table 1. ADD Contents

Art Design Document

(1) Overall style description: the establishment of the main artistic style of the entire game (2) Character design sketch: the appearance, race, costume for characters in game (3) Object design sketch: the appearance of significant objects and items in game (4) Scene design sketch: the design sketches of all stages in game (5) Color setting document: the actual value or serial number for designated skin tones, transparent colors and other colours (6) Model regulation: the limitations in character and object model design (7) Scenario regulation: the limitations in the creation of in-game stage models (8) Outsourcing regulation: the limitations in the outsourcing of works related to artistic contents (9) Special effects regulation: the limitations in the examinations of special effects (10)Action regulation: the limitations in the examinations of character or object motion

Figure 1. Flow of basic art work

Every artistic object must go through the entire process, and it is only considered to be complete after its Maker, the Art Director, the Producer and the Keeper have reached consensus and unanimously approve. Any artistic object is only finalized after it has passed the final acceptance test with the personnel in charge providing his/her signature. No further alterations will be made to finalize artistic objects.

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Including the final acceptance test, all artistic objects must go through three tests over the course of the process: Check 1 Formal test of game platform In the game design, the “Render Ware” cross-platform development software has been chosen. When objects are constructed for the first time, they must go through the first test in the Render Ware environment to make sure object details like appearance and mapping colors are correct. This step in the process can prevent and correct the minute mistakes made by artistic creation personnel due to differences in their work habits. Check 2 Overall test After this test, the completed artistic objects will be inserted to the actual game stage for an actual test run to observe their level of completion in the game. This is also an opportunity to spot and correct any post-production mistakes that may be present. Check 3 Final acceptance testing After all the processes have been completed, all personnel related to the specific object, including the Art Director, the Maker, the 2D Designer of the original script, the Game Designer who has participated in the creation of the object and the Programmer must all be present for the final acceptance test to make sure everything is correct before the final acceptance test can be concluded. By implementing the process, the developers will be able to ensure that every completed artistic object will have the same specification and can be used normally without any problems in other game platforms with the same settings. This process eliminates the need for alterations on numerous semi-finished products in the postproduction phase that would normally be required to make up for the mistakes made over the course of artistic management.

3.

Results and Discussions

For game planning, the supported game platform is the XBOX produced by Microsoft. RenderWare created by Criterion Software has been chosen as the development software in the study. The game content is a full 3D, third person perspective network adventure game for one to four players. The game can be played as a single player game or as a multiplayer game through XBOX Live services. Due to the involvement of network usage and the restrictions of XBOX console’s graphic processing speed and RAM limitations, we have to ensure that the addition of every object to the game must be acceptable within the hardware capabilities. Therefore, the processes presented in this research may not be entirely applicable for game development projects that are targeted for PCs because of the discrepancies in the hardware involved. The discussion and analysis of quality management for artistic objects over the course of game development is purely based on the case of game development processes presented in this study.

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3.1

Certain of Character Models and Validation Process

3.1.1

Model Setting, Model Specification

Derived from the GDD, the model specification documentation should include the description of the characters’ appearance, equipment, nature, behavior, personality, race and social structure, together with 2D artistic sketches of the characters’ portraits from the front, side, back (including detailed character’s facial expressions and close-up shots). In addition, every character must have at least one artistic portrait in full color, with the color settings used clearly indicated on the portrait. 3.1.2

3D Model Creation

The relevant personnel will conduct a meeting to make sure that the designs stated in step 1 conform to what has been stated in the specification, and then create lowpolygon 3D character models based on the descriptive draft and the original sketch of artistic designs. The character models need to be checked for consistency and artistic style against the scenarios. 3.1.3

Normal Map Creation

In order to improve efficiency and lighten the load on the hardware, high-polygon models need to be created for the existing character models by using Normal and Bump mapping. High-polygon models will then be mapped back to the original low-polygon models so that characters will still look great even at lower frame rates. 3.1.4

Character Motion and Sound Effects Creation

After the completion of character models, the next step is to begin the postproduction process for motion and sound effects. Movement should be based on the descriptive documentation stated in step 1; the sound effects will be handled by game designers and the sound effects production crew (or outsourced crew) with the emphasis of staying true to the original sketch. 3.1.5

Overall Test

The completed character models must pass the final game play test to make sure everything is consistent with design requirements. The coordination and interaction between movement, sound and effects must be integrated seamlessly. Figure 2 shows the flow of character building and verification.

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Figure 2. Flow of character building and verify

3.2

Scenario Creations and the Validation Process

3.2.1

Scenario Setting, Scenario Specification

The scene concept description derived from the story setting must include features like scene visuals, scene topography and situation, history, and cultural background, with the addition of important scene locations, objects, event listing and descriptions. Furthermore, 2D drafts of scenes, scene setting diagrams, a complete scenario layout and a flow chart of the game’s progression should also be present in the documentation. This is what makes a scenario specification document and it is mainly an account of the game’s progression and the gaming experience. 3.2.2

Scenario Creation (Art)

The construction of 3D scenario models based on the scenario settings must be checked for artistic style consistency with the appearance of the scenes, the atmospheres, along with the coordination with the characters and monster models. Important scenario locations and events must also be checked to see if they were consistent with the designs. All items and objects that are not under the scope of the scenario editor must be created here and observed to see if they fit well in the actual game.

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Polishing (Scenario Editor)

When the 3D scenarios have been completed, the quest and interactive items must be added to the scenarios by using the scenario editor so that the artistic crew can perform final touch-ups and polishing of visuals. The tasks at this phase are generally done with the quest editor and the scenario editor. 3.2.4

Sound Effects and Music Post-Production (Scenario Editor)

After integration of the scenarios is complete, the final adjustments to sound effects must be made. Sound effects such as the whistling of the wind, ambient sounds such as flowing waters of rivers and background music will be added to the game at this stage. This portion is processed with the scenario editor after having all the necessary sound files ready. 3.2.5

Overall Test

The scenarios must pass through various in-game testing at the final stage to ensure that everything is consistent with the design requirements. Each quest and special effect also has to be tested and any problems found must be corrected. Figure 3 shows the flow of scene/stage building and verify. 3.3

Scenario Objects Creation and the Validation Process

3.3.1

Object Setting, Object Specification

Scenario objects are derived from the scenario setting documentation. This documentation has to include: descriptions of object dimensions, appearances, styles, materials used and functions, with additional images for reference whenever possible. For interactive objects, detailed descriptions on the methods of operation must also be included. This sums up the draft for scenario object description, and can be turned into the original draft for object design after artistic drawings. 3.3.2

D Model Creation

Based on the draft for scenario object description and the draft of artistic design, the 3D scenario model can be constructed. However, the model needs to be checked against the constructed scenarios to see if the artistic style remains consistent and uniform throughout.

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Figure 3. Flow of scene/stage building and verify

3.3.3

Object Post-Production

After the 3D object construction has been completed, editing has to be done to the motion command depending on the requirements. The motion command needs to be timed with high precision for the post-production of sound effects. 3.3.4

Testing

The completed scenario objects must pass the final test in the game to make sure everything is consistent with the design requirements. The coordination between motion, sound, and effects of interaction must be seamlessly integrated. Figure 4 shows the flow of object building and verification.

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Figure 4. Flow of object building and verify

On the whole, as far as artists are concerned, the incorporation of the proposed process will not make them draw faster; but the much of the time lost on the relay of opinions and cross-corrections can definitely be prevented. The introduction of this process will ensure that artists can spend less time on communication and corrections, and the process can serve as a guideline and reference for solutions when things become hectic and out of control.

4.

Conclusions

Though purely theoretical processes have certain values as references, they are hardly practical and feasible in actual applications. The contents and examples of references provided in this study can be used as a source of further reference for construction and validation purposes after gaining a good grasp of pure theoretical contents. However, due to the limitations of the research, the scope of this study only covers fields related to art production processes without touching on the implementation details on other levels. In the realm of game products development, due to a lack of an effective learning system that can pass down the related knowledge and experience in planning, the fields of game design validation process and program validation process still have much room for further research. We would like to recommend researchers interested in the related fields to make their attempts in the two areas we have pointed out here.

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Acknowledgement

The current study is supported by National Science Council, contract 96-2411-H152-003.

6.

References

[1] Tuzun Hakan, (2004) Ph.D., Motivating learners in educational computer games. Indiana University. [2] Moser Robert Breck, (2002), Ph.D., A methodology for the design of educational computer adventure games. University of New South Wales (Australia). [3] Dickey Michele D.Girl gamers, (2006) the controversy of girl games and the relevance of female-oriented game design for instructional design. British Journal of Educational Technology, 37 (5):785-793 [4] Waugh Rachel, (2006), Meet a video game designer. (cover story) Scholastic Scope, 55(3): 14-15 [5] Barendregt W, Bekker M.M., (2006), Bouwhuis, D.G.; Baauw, E., Identifying usability and fun problems in a computer game during first use and after some practice. International Journal of Human-Computer Studies, 64(9): 830-846 [6] Hesseldahl Arik., (2006), Desktops for the Power Player. Business Week, Issue 3997: 72-72 [7] Joynt Patrick, (2006), The Oblivion of RPGs. PC Magazine, 25(12):164-165 [8] Warden James, M.Arch. Senses, (2005), perception, and video gaming: Design of a college for video game design and production. University of Cincinnati. [9] Joseph Dolly Rebecca Doran, (2005), Ph.D., Middle school children's game playing preferences: Case studies of children's experiences playing and critiquing sciencerelated educational games. University of Virginia. [10] Andrew Rollings, Ernest Adams., (2003), Game Design. Pearson Education, Inc., 1225 [11] Jessica Mulligan, Bridgette Patrovsky, (2003), Developing Online Game: An insider’s guide. Pearson Education, Inc. [12] Flanagan Mary, (2006), Making games for social change. AI & Society, 20 (4): 493505 [13] Fisher John W., (2003), II, M.A., Methods and considerations in online game design. Michigan State University. [14] Chang Carl K., (1993), IS EXISTING SOFTWARE ENGINEERING OBSOLETE? IEEE Software, 10 (5): 4.

Chapter 2 Engineering Knowledge Management and Design for X

Integration of Design for Assembly into a PLM Environment...................... 117 Samuel Gomes, Frédéric Demoly, Morad Mahdjoub, Jean-Claude Sagot Design Knowledge for Decision-Making Process in a DFX Product Design Approach ................................................................ 127 Keqin Wang, Lionel Roucoules, Shurong Tong, Benoît Eynard, Nada Matta Mobile Knowledge Management for Product Life-Cycle Design.................. 137 Christopher L. Spiteri, Jonathan C. Borg Research on Application of Ontological Information Coding in Information Integration................................................................................ 147 Junbiao Wang, Bailing Wang, Jianjun Jiang and Shichao Zhang RoHS Compliance Declaration Based on RCP and XML Database............. 157 Chuan Hong Zhou, Benoît Eynard, Lionel Roucoules, Guillaume Ducellier Research on the Optimization Model of Aircraft Structure Design for Cost ............................................................................................................... 167 Shanshan Yao, Fajie Wei Research on the Management of Knowledge in Product Development ........ 177 Qian-Wang Deng, De-Jie Yu Representing Design Intents for Design Thinking Process Modelling.......... 187 Jihong Liu, Zhaoyang Sun Application of Axiomatic Design Method to Manufacturing Issues Solving Process for Auto-body ......................................................................... 199 Jiangqi Zhou, Chaochun Lian, ZuopingYao, WenfengZhu, ZhongqinLin Port-Based Ontology for Scheme Generation of Mechanical System ........... 211 Dongxing Cao, Jian Xu, Ge Yang, Chunxiang Cui Specification of an Information Capture System to Support Distributed Engineering Design Teams ............................................................................... 221 A. P. Conway, A. J. Wodehouse, W. J. Ion and A. Lynn Collaborative Product Design Process Integration Technology Based on Webservice......................................................................................... 231 Shiyun Li, Tiefeng Cai Information Modelling Framework for Knowledge Emergence in Product Design .............................................................................................. 241 Muriel Lombard, Pascal Lhoste

Flexible Workflow Autonomic Object Intelligence Algorithm Based on Extensible Mamdani Fuzzy Reasoning System .............................. 251 Run-Xiao Wang, Xiu-Tian Yan, Dong-Bo Wang, Qian Zhao DSM based Multi-view Process Modelling Method for Concurrent Product Development ............................................................. 261 Peisi Zhong, Hongmei Cheng, Mei Liu, Shuhui Ding Using Blogs to Manage Quality Control Knowledge in the Context of Machining Processes ..................................................................................... 273 Yingfeng Zhang, Pingyu Jiang and Limei Sun Analysis on Engineering Change Management Based on Information Systems ......................................................................... 283 Qi Gao, Zongzhan Du, Yaning Qu Research and Realization of Standard Part Library for 3D Parametric and Autonomic Modeling.................................................................................. 293 Xufeng Tong, Dongbo Wang, Huicai Wang Products to Learn or Products to Be Used? .................................................... 303 Stéphane Brunel, Marc Zolghadri, Philippe Girard Archival Initiatives in the Engineering Context ............................................. 313 Khaled Bahloul, Laurent Buzon, Abdelaziz Bouras Design Information Revealed by CAE Simulation for Casting Product Development.................................................................... 323 M.W. Fu An Ontology-based Knowledge Management System for Industry Clusters......................................................................................... 333 Pradorn Sureephong, Nopasit Chakpitak, Yacine Ouzrout, Abdelaziz Bouras

Integration of Design for Assembly into a PLM Environment Samuel Gomes, Frédéric Demoly, Morad Mahdjoub, Jean-Claude Sagot SeT laboratory – Belfort-Montbéliard University of Technology 90010 Belfort cedex, France, Phone: +33 384 583 006, Fax: +33 384 583 013, e-mail: [email protected]

Abstract This paper presents a methodology in the field of Design for Assembly (DFA) related to the generation of assembly sequences and information systems in the PLM area. This method has been designed to develop assembly methods in our own PLM tool, taking into consideration assembly constraints in the early phases of the design process in order to be in coherence with concurrent engineering concepts. An experimental case study, a racing car ground-link system, is presented to illustrate the methodology developed. Keywords: PLM, Design for Assembly, Assembly Sequences, collaborative Engineering, knowledge management.

1.

Introduction

In a context of competitiveness with increasing constraints in terms of QualityCost-Time, companies must set up a collaborative engineering approach facilitating co-operation and coordination between their various departments and project teams, using, for example, PLM tools (Product Lifecycle Management). According to the Aberdeen Group report [1], companies that became aware of PLM potential, have seen their performances increase considerably, with a rise in sales of 19% and a fall in product development costs of 17%. There are, however, various directions to consider in order to achieve competitive and profits within company design processes. It requires , for example, accumulating information and re-using expertise on various product-process design activities. While it is based on professional processes integrated into technical data management tools like PLM or PDM (Product Data Management), our research activity is aimed at assembly engineering and focused on the early phases of the product design process. Indeed, the assembly engineering competence, traditionally considered at the end of the product development cycle, can benefit from the use of constraints resulting from upstream design phases to generate optimal assembly process sequences. Moreover, designers who define the product must be able to consider expert rules related to assembly in order to avoid many

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iterations, which would result in a reduced level of effectiveness and therefore of productivity in design. Thus the objective of our research activity is to allow a better collaboration between product designers and production engineers through a methodology integrating PLM, CAD tools and assembly know-how. This paper first describes our methodology of semi-automatic generation of assembly sequences, from product data stored in a PLM system, and particularly kinematics links, geometrical constraints and also specific expert rules. The aim here is to enhance our own PLM tool: ACSP (in French: Atelier Coopératif de Suivi de Projet), by proposing to integrate product-process design domains into it, using our DFA approach [2]. Then, in a second step, we present and discuss our results, coming from an experimental case study, performing collaborative design processes, Product Data Management (PDM) and Product Lifecycle Management (PLM) concepts and tools, in terms of Design for Assembly (DFA) methods, and particularly semiautomatic assembly sequence generation in a CAD environment. Finally, conclusions and perspectives are defined to prepare future work.

2.

Our Methodology of Integrated Product-Process Design

Our global methodology takes into account a concurrent design process represented by Gomes’ model [3], and a matrix-based traceability analysis approach, considering our work as a frame of reference for accumulation and reuse of expert rules resulting from product design and assembly activities. The analysis performed on theses matrices uses simple mathematical functions including summation of rows and columns and sorting. These methods, similar to Axiomatic design [4] and the Design Matrix System, provide useful insights to product-process integrated design, by focusing attention on system requirements, functionality, components and finally assembly sequences. This design process model, linked with the MD-MV model (Multi-Domains and Multi-Viewpoints) [3], constitutes the framework of the ACSP PLM tool and has the objective of designing, identifying, selecting, evaluating, accumulating and reusing information, and thus knowledge. Jared et al. indicate that 72% of DFA criteria and assembly process sequence generation can thus be solved through the geometrical CAD model [5] and consequently, by the PDM system. Our approach consists to use PLM data, combined with CAD models and specific filters considering DFA rules. This method favors assembly process generation by matrices analysis [6] and operations in order to reduce problem complexity and to define the “Parts-Workplaces” matrix (PW= (pwij), 1 ืi ืk, 1 ืj ืv). This matrix specifies the workplaces where each part is assembled at several steps of the assembly process. Thus, this methodology, integrated in a PLM environment, can be braked down in the following way: x

Definition of product structure and strategic parameters in the PLM, applied to the Parts connection square matrix (“Parts-Parts” matrix: PP=(ppij), 1 İi İk, 1 İj İk,),

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Constraints modelling between product components in a matrix form, based on the CAD model analysis, Automatic generation of feasible assembly process sequences, by means of specific algorithms (detailed in next paragraphs). These assembly sequences are then created and stored in the process domain of the PLM system, Assembly process sequences representation in CAD tools, generated directly from the PLM, using Visual Basic scripts, in order to validate the assembly proposals, Workplace design by selecting relevant process sequence, considering the time required for each assembly operation and the assembly process reference time.

Experimentation

In order to illustrate our proposals, an experimental design case is chosen. Every year, our mechanical engineering and design department has to develop and prototype an entire new racing vehicle, involved in the SIA car competition (French Automotive Engineers Society). This racing car design project is used as an experimental of our methodology. To simplify the demonstration, we choose to limit the experimental case study to a sub-product of the racing car: the groundlink suspension system. This sub-product of the racing car includes many mechanical parts linking the wheel to the chassis. All these data are stored in the PLM system. After an analysis of the CAD model of our racing car suspension triangle (Figure 1), we extract the strategic constraints (constraints due to direct interferences and precedence constraints between components) for the assembly process.

Figure 1. Suspension triangle concept considered for our design for assembly experience

3.1

Product Structure And Constraints Modelling

Designers and manufacturers must verify that a given designed product can be assembled, without interference between parts, before the product is manufactured. Currently, most PLM tools do not have the capability to directly analyze the

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feasibility of a given assembly plan for a product or to generate an optimal or nearoptimal assembly plan. As a result, a great deal of prior research exists on developing external assembly analysis tool for automatic assembly sequence planning and optimization. We focus our approach on automatic generation of assembly process sequences starting from product structure data stored in the PLM system. We chose to represent the precedence knowledge of an assembly in a directed graph form (Figure 2) where each node represents an elementary component and each bond between nodes indicates the presence of a connection between two elementary components. Among the connections, this graph identifies two types: contact connection (in solid line) and dummy connection (in dashed line) bringing an assembly order constraint if no-contact between two components. Kneecap A2

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The directed graph describes the precedence properties of an assembly that can be represented in our own PLM tool ACSP (Figure 3). This tool enables to assign the type of connection between two elements like component-component, componentsub-assembly, and sub-assembly-sub-assembly. Besides, each connection will be affected of an order constraint. ACSP tool helps experts to exploit the precedence knowledge described previously and generate automatically a connection matrix adjacent to the directed graph.

Figure 3. Example of connections between Foam A and others elements in PLM tool ACSP

As illustrated in Figure 4, we can map into the previously described PP (“PartsParts”) dissymmetric square connection matrix PP = R = [rij] the relationships showed in the directed graph, applied to the previously described suspension triangle example, and detailed in our PLM tool.

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Figure 4. The connection matrix of a suspension triangle concept

3.2

Detection of Sub-Assemblies and Sub-Assembly Layers

Starting from a product of n components, a sub-assembly is a set of components p1, p2, p3, …, pm, with 2<m 1 x For a parallel assembly matrix, all other components are connected only to the base component i: | ri, i | = 0, and if | rij | = 1 then (for kj and k i rj k = 0), Two examples of sub-assemblies formed by three elements “Foam A, Tube A, Sleeve A2, Kneecap A2” and “Foam B, Tube B, Sleeve B2, Kneecap B” (Figure 6) are detected in the connection matrix and represented by sub-matrices by extraction of rows and columns corresponding to elements given previously. For each sub-matrices detected, a companion matrix is generated. The detection of candidate’s sub-assemblies is performed via an algorithm computed in Matlab mathematical tool.

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Figure 6. Serial sub-matrices SA1 and SA2 with respectively the Companion matrices SAC1 and SAC2 to define possibility of sub-assemblies

For a product composed of many components, assembly expert must take into account sub-assembly layers. It is necessary to use another matrix: the contracted matrix R* considering each sub-assembly detected from the connection matrix R as a single component. Thus, others sub-assemblies can also be detected in another layer. This matrix R* depends of the detected sub-assembly matrices (m*m), then the size of matrix R* will be: n-m+1. Hence, to build R*, several rules must be performed (Figure 7). In our case, as illustrated at Figure 7, with the subassemblies detected SA1 and SA2, the contracted matrix has a size 7, while considering each sub-assembly SA1 and SA2 as a single component.

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IF (all elements in the kth columns of companion matrix SAC =0) THEN (rsa,k = 0); IF (all non zero elements in the kth columns of companion matrix SAC) are (>0 and =Ȝ) THEN (rsa,k= Ȝ) ELSE (rsa,k = 1); IF (all non zero elements in the kth columns of companion matrix SAC) are (<0 and =-Ȝ) THEN (rsa,k= -Ȝ) ELSE (rsa,k = -1).

Figure 7. The contracted matrix considering SA1 as a single component

3.3 Interference Analysis Between Each Detected Set and Other Parts of the Product Starting from these types of assembly configurations, two kinds of matrices will be generated for each sub-assembly: the Boolean square matrix SA and the companion matrix SAC. The SAC companion matrix is used to detect if the potential sub-assembly interferes with the set selected and other individual components. Thus, to determine if the sub-assembly is feasible, several rules must be applied with the associated companion matrix. So if the signs of non zero elements in kth column are neither all positive nor all negative, there are interference between the SA matrices set and other individual components, then this set can not be considered as a sub-assembly. In our example, concerning the potential sub-assemblies detected, each non zero elements in the kth column of each companion matrix are either all positive or all negative, then these two sets can be considered as serial sub-assemblies. Using this method, 3 assembly layers can be generated:

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Assembly layer 1 from R Serial sub-assemblies: SA1 = {Foam A, Tube A, Sleeve A2, Kneecap A2} SA2 = {Foam B, Tube B, Sleeve B2, Kneecap B} Individual components : {Sleeve A1, Plate, Kneecap A1, Sleeve B1, Screw}

Assembly layer 2 from R* (1) Serial sub-assembly: SA3 = {SA1, Sleeve A1, Plate} Individual components : {Kneecap A1, Sleeve B1, Screw}

Assembly layer 3 from R* (2) Serial sub-assembly: SA4 = {SA2,, Sleeve B1, SA3} Individual components : {Kneecap A2, Screw}

Assembly layer 4 from R* (3) Parallel sub-assembly: SA5 = {SA4, Kneecap A1, Screw}

Figure 8. Assembly layers

3.4

Sub-Assemblies Layers Management

ª 0 «

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SA4 =

ª 0 1 « 1 0 « «¬1 0

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1º 1»» 0»¼

0 0 0 0 0 1 0 1 0 0 0 1

SA1 Sleeve A1 Plate

ª 0 0 « 0 0 « «¬ 0 1

Sleeve B1 SA2 SA3

ª 0 0 « 0 0 « ¬« 0 1

0º 0»» 1» » 0¼

Foam A Tube A Sleeve A2 Kneecap A2 Foam A Tube A Sleeve A2 Kneecap A2

ª « « « « ¬

0

0

0

0

0

0

0

0

0

0

0 1

0º 0»» 1» » 0¼

Foam A Tube A Sleeve A2 Kneecap A2

0º 1»» 0»¼

SA1 = {Foam 1, Tube A, Sleeve A2, Kneecap A2}

SA1 Sleeve A1 Plate

SA 3 = {SA1, Sleeve A1, Plate}

SA2 Sleeve B1 SA3

SA 4 = {SA2, Sleeve B1, SA3}

SA2 Sleeve B1 SA3

Sleeve B1 SA2 SA3

SA3 =

ª « « « « ¬

SA1 Sleeve A1 Plate

SA1 Sleeve A1 Plate

SA1 = «1

Foam A Tube A Sleeve A2 Kneecap A2

Foam A Tube A Sleeve A2 Kneecap A2

Detected and verified sub-assemblies must have their components organized in a defined way in order to restrict the generation of feasible assembly sequences. To reach this objective, an assembly order will be defined for each layer of subassemblies by permutations. Concerning the first sub-assembly SA1, the base component will be the component where the signs of non zero elements of its row are all positive. In this case, all elements of its row and its column are set as zero, besides the base component will be placed in first position (Figure 9).

0º 1»» 0¼»

Figure 9. Examples of a permutation with the sub-assemblies SA1, SA3, SA4

Integration of Design for Assembly into a PLM Environment

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This same method must be performed for the other sub-assemblies (SA2 for instance) until having the part assembly order in the sub-assembly. In our example, as shown in Figure 9, two assembly sequences are detected: x x

3.5

Assembly sequence 1: [({Foam Sleeve B1; ({ Foam A, Tube A, Plate)); Kneecap A1; Screw], Assembly sequence 2: [({Foam Sleeve B1; ({ Foam A, Tube A, Plate)); Screw; Kneecap A1].

B, Tube B, Sleeve B2, Kneecap B}; Sleeve A2, Kneecap A2}; Sleeve A1; B, Tube B, Sleeve B2, Kneecap B}; Sleeve A2, Kneecap A2}; Sleeve A1;

PLM and CAD Link

Starting from the previously generated assembly sequences, next objective consists in generating through our own PLM tool a Visual Basic script to be executed in a CAD tool in order to visualize assembly simulations (Figure 10).

Figure 10. Simulation of assembly sequences of suspension Triangle concept in CATIA v5

These scripts take into account positions of components in relationship of assembly layers. For example, with one assembly, two positions can be used such as the position where components are assembled and the position where components are fragmented. Thus, starting from detected assembly sequence, components can move in a predefined order: from an initial position (fragmented view) to the final position (components assembled) for each assembly layer. At the end of this experimentation, it is possible to define the “Parts-Workplaces” matrix (PW=(pwij)), combining the previously defined assembly sequences and the time per assembly operation, and considering time values, as close as possible to multiples of the reference time of the assembly process.

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Conclusion and Perspectives

To be competitive, companies must implement a design process and methodologies suited to their needs and constraints. We chose to examine here our methodology through several modules: CAD and PDM tools have enabled us to achieve our aim of incorporating tasks earlier , particularly assembly processes, which are situated downstream of the design phase. Our experimentation has been limited to semiautomated production of assembly process sequences. However, this method is our first research experiment and will be springboard for our future work. It will be interesting to open up perspectives for PDM tool development integrating professional knowledge, and which should result in a tool which can carry out the definition of the product-process couple throughout its lifecycle and which will be able to exploit design information for assembly and vice-versa. This tool will have to take into account the professional aspects (Design For Assembly - DFA, Design For Manufacturing - DFM, etc.), systemic aspects (economic, information, production, etc.), disciplinary aspects (mechanical, electronics, computer sciences, etc.) and technological, epistemological and ontological, while at the same time managing professional processes. We will place importance on drawing up a methodology which can be used for product families in order to provide a complete solution to a defined context. This paper represents a first leap towards a method of semi-automatic process sequence generation based on information coming from CAD but also from professional rules (DFA) which will have to be evaluated. This approach will be necessary in order to be able to select automatically and simulate in a CAD environment, the relevant and optimal assembly sequence.

5.

References

[1] Aberdeen Group, Inc., (2006) Report on: The PLM for Small Mid-size Manufacturers [2] Gao J.X., Bowland N.W., (2002) A Product Data Management Product Configuration and Assembly Process Planning environment, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol.216, Nb.3, p.407–418, 2002. [3] Gomes S. and Sagot J-C., (2002) A concurrent engineering experience based on a cooperative and object oriented design methodology. Best papers book. 3rd International Conference on Integrated Design and Manufacturing in Mechanical Engineering, Kluwer Academics Publisher, p. 11–18. [4] Suh N.P., (2001) Axiomatic design: advances and applications, Oxford Univ. Press. [5] Jared G., Limage M., Sherrin I., Swift K., (1994) Geometric Reasoning and Design For Manufacture, Computer Aided Design, vol.7, p. 528–536. [6] Zhang Y.Z., Ni J., Lin Z.Q., Lai X.M., (2002) Automated sequencing and subassembly detection in automobile body assembly planning, Journal of Materials Processing Technology, vol. 129, p. 490–494.

Design Knowledge for Decision-Making Process in a DFX Product Design Approach Keqin Wang1, Lionel Roucoules2, Shurong Tong1, Benoît Eynard2, Nada Matta2 1

Northwestern Polytechnical University - China University of Technology of Troyes - France

2

Abstract Product design is a knowledge-intensive process and involves large quantities of decisions. The efficiency and effectiveness of these decisions depend on the provision of many kinds of related knowledge to designers from different sources throughout the product lifecycle. First, this paper makes a literature review about the related works on product design knowledge and classifies the product design knowledge into three categories, namely product, process and product support knowledge. Secondly, the knowledge needs of product design decisions are analyzed. The decisions made during the design process have a critical impact both on the design solution obtained but also on the design process itself. These decisions are of many different types and made by different kinds of engineers and managers. This work illustrates decision-making in product design and some related works are reviewed. The decision-making during the product design process is analyzed and classified into two main categories, namely organizational and technical decisions, which are illustrated in a three dimensional figure. Finally, some conclusions and future works are discussed. Keywords: DFX, product design, knowledge management, decision making process 1.

Introduction

The activity of engineering design can be defined to encompass a variety of activities (i.e. DFX concept) and is also a knowledge-intensive activity. The process of engineering design is an analytic step used to improve the quality of the final product and to reduce the time and resources needed for the final production [1]. The role and importance of knowledge within engineering and in product design in particular has become a major factor to ensuring that competitive advantage is gained by a company. Within forward looking organizations information transfer and knowledge usage by people in design team has become crucial to the ultimate success of a product’s introduction to the market and a fundamental paradigm is that of the relationship among the design team members. It has been seen that the supply of information is a continually growing domain in its own right [2].

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Thus there is an overwhelming need to provide design decision with enough knowledge support throughout the design process. The knowledge used comes from a variety of sources, from within the company as well as from outside, from work related as well as non-work related events and may exist in many areas including ergonomics, packaging, management, manufacturing processes and so on [3]. As products become more complex and competition intensifies, it is essential to make the maximum use of the available product design knowledge and to deliver that knowledge in the appropriate form to the right point at the right time during the product development process. The efficient delivery of information to design team members is therefore of vital importance to the overall success of a product design [4]. Although there have been some research on the product design knowledge, such as some empirical study on the knowledge needs (or request), knowledge search, knowledge flow etc. However, how many kinds of knowledge and who use this knowledge are not clear yet. This work tries to understand the different kinds of knowledge and make clear the different knowledge needs of different people in product design and needs for decision making process. This paper is organized as follows. Section 2 makes a literature review about the related works on product design knowledge and classifies the product design knowledge into several categories. Section 3 analyzes the knowledge needs of product design decisions. Section 4 introduces a proposal for acquiring manufacturing knowledge and retrieving the right knowledge during decision making process via a specific DFM design process and product modelling. Section 5 concludes with discussion and further research directions.

2.

Product Design Knowledge

2.1

Design Knowledge Identification

Design knowledge can improve the quality of design decisions [5]. Increasing design knowledge and supporting designers to make right and intelligent decisions can achieve the improvement of the design efficiency. Many proposed classifications of engineering design knowledge can be found in the literature [7-9]. The classification by Vincenti [7] includes six categories such as fundamental design concepts, criteria & specification, theoretical tools, quantitative data, practical considerations and design instrumentalities. But it does not include the ‘design process’. The classification shown in Figure 1 by Zhang [8] reflects this concern. Design knowledge Knowledge involved in design process

Design activity knowledge

Current working knowledge Domain knowledge

General knowledge Past cases

Design process knowledge

Figure 1. Design Knowledge by Zhang [8]

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Ahmed [9] classified product design knowledge by two dimensions: In one dimension, the knowledge is divided into process-related and product-related knowledge. In another dimension, the knowledge is divided into Stored externally Information, Stored internally in human memory (including Explicit knowledge, Implicit knowledge, and Tacit knowledge). 2.2.

Classification of Product Design Knowledge

In this paper we group product design knowledge into three groups: Product Knowledge, Process Knowledge and Product Support Knowledge (see Figure 2). The first two only refer to the knowledge being generated and then utilized during the product design process. Product Support Knowledge Final Product

Product idea

Product Knowledge Process Knowledge Clarification of the task

Conceptual design

Embodiment design

Detail design

Product Support Knowledge

Figure 2. Classification of Design Knowledge

Product knowledge is all knowledge related to the product itself. This part of knowledge is most for product design engineers who focus their efforts on the product itself. As Aziz and Chassapis [10] pointed out, any product related knowledge could be grouped into four categories: Knowledge about components; Knowledge about relations between components; Constraints on properties of materials involving part formation; Relations between components and user preferences. Process knowledge is the knowledge about the design process. This part of knowledge is most for product design managers who focus their efforts on the product design process, and based on this knowledge, they have to decide what the work will be done, when it will be done, and who will do it. As in [11], Jung et al. defined process knowledge into three types of process knowledge such as process template knowledge, process instance knowledge, and process-related knowledge. The latter one, Product Support Knowledge, refer to the knowledge coming from many different sources which locating outside the product design process, for example, knowledge from marketing, manufacturing, packaging etc.

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3.

Decision-Making in Product Design

3.1.

Decision and Design Decision-Making

According to Simon [12], the work of managers, of scientists, of engineers, of lawyers is work of choosing issues that require attention, setting goals, finding or designing suitable courses of action, and evaluating and choosing among alternative actions. The first three of these activities--fixing agendas, setting goals, and designing actions--are usually called problem solving; the last, evaluating and choosing, is usually called decision making. Design activities involve decision-making [13]; however, we believe that not all design activities are decision activities. When the design task is extremely wellformulated, the design engineer’s decision-making process is the solution of an optimization problem. Here decision-making is problem-solving. In contrast, when the design task is ill-formulated, design engineers are less able to apply formulaic numerical techniques to “solve the design problem.” In these cases, the design engineer’s decision-making process is a collection of heuristics that generate and evaluate solutions until a satisfactory one is found [14]. 3.2.

Classification of Decisions in Design

The decisions made during the design process have a critical impact both on the design solution obtained but also on the design process itself [17]. Product development, indeed, includes many different types of decision-making by engineers and managers. Herrmann and Schmidt [14] divided these decisions into design decisions and development decisions. Design decisions determine the product form and specify the manufacturing processes to be used. Design decisions generate information about the product design itself and the requirements that it must satisfy. Development decisions, however, control the progress of the design process. They affect the resources, time, and technologies available to perform development activities. They define which activities should happen, their sequence, and who should perform them. Corresponding to the two types of decision named design decisions and development decisions [14]. We divide the decisions during the product design process into two types: Technical decision and organizational decision. Technical decisions focus on the product itself and determine the parameters about the product. Most of technical decisions are made by product design engineers. Organizational decisions, however, control the progress of the design process. They define what will be done, when it will be done, and who will do it. Most of organizational decisions are made by design managers or people in other company management levels (e.g. the project leader judges the results obtained so far compared to the resources spend, and determines what to do next, how to do it, and who has to do it, the company management at project milestones judges the results obtained compared to the expected business opportunity, and determines the future of design project in a go/no-go decision [16]). Here we analyze design decisions in three dimensions as shown in Figure 3. Axe X indicates a design process consisting of four phases: Clarification of the task,

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conceptual design, embodiment design, and detail design [15]. Axe Y indicates different types of decision-makers including design engineer, design supervisor, design manager and company-level management. Axe Z indicates organizational decision and technical decision. Hierarchical Position of Decision-maker Company management Design manager Design supervisor Clarification Conceptual Embodiment Detail of the task design design design

Product Design Process

Organizational decision

Technical decision

Ty

pe

so fD ec isi

on s

Design engineer

Figure 3. A characterization of decisions during the product design process

4. Support for Knowledge Acquisition and Retrieval in a Design Decision-Making Process Contemporary design process becomes increasingly knowledge-intensive and collaborative. Knowledge-intensive support becomes more critical in the design process and has been recognized as a key solution towards future competitive advantages in product development. To improve the design process, it is imperative to provide knowledge support and share design knowledge among distributed designers. Marsh [18] found the proportion of designers’ time absorbed by information acquisition activities to be 20-30%. Marsh also found that the majority of information is obtained from personal contacts, who in 78% of cases retrieved it from memory. Production line Machining n Machining ...

Machining 2 Machining 1

Mfg. database

DM-based knowledge discovery Process Problem definition Target data selection Data cleaning Data transformation DM implementation Interpretation & Evaluation

Domain Product expert designer

Mfg.-related Knowledge base

Figure 4. Framework of Knowledge Support for Technical Design Decision-making

However, with the increasing flow of experts in manufacturing companies, knowledge base have to established to store more and more knowledge to meet the needs of product designers, especially for those novice designers. Here we propose one framework which could acquire and extract knowledge to support technical decisions for product designers, which is one part of our research project.

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The ultimate objective of our work is the development and implementation of a Design Decision Support System (DDSS), which acts as an aid tool for support design decisions concerning manufacturing aspect. Figure 4 represents the conceptual framework of the DDSS. In this framework, large quantities of manufacturing data are recorded in database, through our DM-based knowledge discovery approach (cf. 4.1), manufacturing-related knowledge are discovered and stored into the knowledge base after evaluation and interpretation. Then the right knowledge could be delivered to the right product designers at the right time during the product development process (cf. 4.2). 4.1

Manufacturing Knowledge Acquisition Approach

Acquisition of manufacturing knowledge (specifically in our work Manufacturing Quality Information – MQI) is a bottleneck in the proposed system framework. Presently most research on knowledge acquisition is about acquisition of illstructured knowledge such as experience of experts. Most knowledge acquisition tools and methods depend on the experts, knowledge engineers, and man-machine interactive systems. Concerning manufacturing knowledge, first of all the distribution and source should be clear. In fact most of them exist in different information systems all over the enterprise which are structured information, but the fact is that this manufacturing knowledge often has different structure in different information systems. So firstly it is important to acquire the knowledge from different sources, and secondly it has to be structured into one unified structure by some suitable methods such as Semantic Network in order to find knowledge to support product design. MQI acquisition in production process is complicated. Concerning the source of MQI, some of them are from production line and some are the records of quality inspection (cf. Figure 5). Quality information from production line should be reorganized according to different inspection methods and then will be sent to different information systems. Acquisition of quality information depends on different methods of quality information detection. According to the degree of automatization, quality detection can be divided into three categories such as automatic detection, semi-automatic detection, and manual detection. Automatic detection system can collect quality information and transport the analysis result to control equipment. Semi-automatic detection is done manually but the transportation and processing is automatic. In manual detection, all the detection equipments are operated by hand, data processing and transportation of analysis results are also done manually. Quality data acquisition can also be divided into two categories such as online and offline quality data acquisition respectively: x

Online quality data acquisition. It is controlled by computers. Quality data is gathered from the production line and then be pre-processed and transferred to the central control computer [19]. Control computer analyze the data and send adjustment order to the production line. All the online quality control is operated by computer automatically.

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x

Offline quality data acquisition. Quality data is not gathered from the production line. It is most about inspection on finished products offline, and by the inspection results orders are sent to adjust the production line. In practice, the two kinds of quality data acquisition are used concurrently. Often in mechanical manufacturing enterprises, some quality data are acquired by computers automatically and some have to be acquired manually. What we should do is to collect MQI and integrate them, and then the MQI collected can be represented in order to structure knowledge using data mining and other methods.

Figure 5. Framework for MQI acquisition

4.2

Knowledge Retrieval in a DFM Product Design Process

Once the acquisition done in the DSS respect to the above Data-Mining process, the knowledge has then to be used in product design process. As already mentioned the right knowledge has to be provided at the right time to the right person. The initial work done by some of the authors has then been to propose a specific DFM product design process (cf. Figure 6). That knowledge-intensive process describe with IDEFØ and IDEF3 meta-model strongly links a UML manufacturing knowledge modelling that supports product modelling. It is then easy to know which “right” knowledge has to be provided to the “right” designer and when (“right time”) respect to this activity modelling.

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Design Process Processes selection according to manufacturable skins A111 Skin and skeleton features

Final knowledge display

Materials information

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Figure 6. Information retrieval support

The first implementation of that retrieval system has been based on the following three concepts and related internet-based software technologies (cf. Figure 6): x

To structure the information according to the IDEF and UML modelling which represent the DFM activity. SQL database coupled to DTD (Document Type Definition) mark-ups provided in the XML language are then used. x To edit information through filters. Currently several filters have been identified : to filter the knowledge with respect to the activity (“right time”) and to filter the knowledge with respect to the designer (“right person”). PHP requests and XSL (Extensible StyleSheet Language) have been used to filer part of the DTD when editing the XML files (cf. figure 6). This XSL language can also provide different display formats filter (html or PDF formats). x To have the information evolved (modify, add, delete information). This concepts is tightly linked to the DM module presented in the section 4.1. in order to continuously update the knowledge. For further information, all details of the DFM process and product modelling are presented in [20]. Those on the knowledge retrieval application are in [21].

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5.

135

Conclusion and Recommendations for Future Works

Product design is knowledge-intensive process and involves large quantities of decisions. The efficiency and effectiveness of these decisions depends on the provision of many kinds of related knowledge to designers from different sources throughout the lifecycle. This work analyzed and classified design knowledge into three categories, namely, product-related, process-related and product support knowledge. Knowledge needs of different kinds of decisions during different product design stages should be analyzed in-depth. One knowledge database need to be established to store product design knowledge, especially to store the product support knowledge. And then the design decision support system should be developed to support design decisions based on product design knowledge.

6.

Acknowledgments

This paper has been supported by National Natural Science Foundation of China (NSFC, Grant 70462066) and the Youth for NPU teachers Scientific and Technological Innovation Foundation.

7.

References

[1] Mili F., Shen W., Martinez I., Noel P., Ram M., Zouras E., (2001) Knowledge modeling for design decisions. Artificial Intelligence in Engineering, Volume 15, Number 2, pp. 153-164. [2] Harrison S.R. and Minneman S.L., (1993) Tools, communication, and the nature of design. In Proceedings of the 9th International Conference on Engineering Design (ICED’93). The Hague, The Netherlands, pp. 351-354. [3] Blessing L.T.M. and Wallace K.M., (1998) Supporting the knowledge life-cycle. In Knowledge-Intensive CAD, KIC3 Workshop, Tokyo, Japan. [4] Court A W, Ullman D G and Culley S J. A., (1998) Comparison Between the Provision of Information to Engineering Designers in the UK and the USA. International Journal of Information Management, 18(6), pp. 409-425. [5] Beheshti R., (1993) Design decisions and uncertainty. Design Studies, 14(1), pp. 85-95. [6] Frise P.R., Rohrauer G.L., Minaker B.P. and Latenhof W.J, (2003) Identifying the design engineering body of knowledge. In International Conference on Engineering Design (ICED 03), Stockholm, August 19-21. [7] Vincenti W.G., (1990) What Engineers Know and How They Know It? (The Johns Hopkins University Press, Baltimore). [8] Zhang Y., (1998) Computer-Based Modelling and Management for Current Working Knowledge Evolution Support, PhD Thesis, Strathclyde University, UK. [9] Ahmed S., Bracewell R. and Kim S., (2005) Engineering knowledge management. In A Symposium in Honour of Ken Wallace. Cambridge, UK, pp. 1-7. [10] Aziz E.-S.S. and Chassapis C., (2005) A decision-making framework model for design and manufacturing of mechanical transmission system development. Engineering with Computers, 21, pp. 164-176.

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[11] Jung J., Choi I. and Song M., (2007) An integration architecture for knowledge management systems and business process management systems. Computers in Industry, 58, pp. 21-34. [12] Simon H.A. and Associates, (1986) Decision Making and Problem Solving. Report of the Research Briefing Panel on Decision Making and Problem Solving, (National Academy Press, Washington, D.C.). [13] Eekels J., (2000) On the fundamentals of engineering design science: the geography of engineering design science-Part 1. Journal of Engineering Design, 11(4), 377-397. [14] Herrmann J.W. and Schmidt L.C., (2002) Viewing product development as a decision production system. In ASME 2002 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2002, Montreal. [15] Pahl G. and Beitz W., (1996) Engineering Design - A Systematic Approach, (SpringerVerlag, London). [16] Hansen C.T. and Andreasen M.M., (2004) A mapping of design decision-making, in 8th International Design Conference, DESIGN 2004, Vol.3, pp.1409-1418. [17] García-Melón M., Aragonés P., Poveda R. and Zabala J., (2005) Analysis of the decision making processes in NPD projects within innovative companies-an empirical study in the Valencian region (Spain), in International Conference on Engineering Design, ICED 05, Melbourne, August 15-18. [18] Marsh, J.R., (1997) The Capture and Untilisation of Experience in Engineering Design, PhD Thesis, Cambridge University. [19] Yin C. Y., (1998) In: Quality Engineering Introduction, 100-109. China metrology publishing house, Beijing. [20] Skander A, Roucoules L., Klein Meyer JS, (2007) Design and manufacturing interface modelling for manufacturing processes selection and knowledge synthesis in design, in International Journal of Advanced Manufacturing Technology, DOI10.1007/s00170007-1003-2. [21] Roucoules L.,Skander A., Eynard B., (2004) XML-based knowledge management for DFM, in International Journal of Agile Manufacturing, vol 7, n°1, pp 71-76.

Mobile Knowledge Management for Product Life-Cycle Design Christopher L. Spiteri, Jonathan C. Borg Department of Industrial and Manufacturing Engineering, University of Malta

Abstract As products become more complex, a significant amount of design knowledge support is required by designers during the design process. However, given that the design process is not only confined within a design office, knowledge support must be provided to designers even when they are away from their usual workplace. This provision of knowledge is essential for designers to take sound decisions that span through the whole product life-cycle, from the conceptual design stage to the disposal phase. Hence, designers require design tools that support them at considering the consequences based on these decisions. With the ever-increasing popularity of mobile devices (such as PDAs, smartphones and pocket PCs), access to such knowledge can be greatly facilitated. The contribution of this paper consists in the presentation of a mobile Knowledge Management (mKM) system architecture that provides distributed engineering designers situated in mobile work settings with design knowledge support in the form of ‘life-cycle consequences’ during the design process. Keywords: mobile knowledge management, distributed environment, product lifecycle

1.

Introduction

Engineering design is considered to be a knowledge-intensive activity [1], and managing it is an important concern for the engineering design industry [2]. This can be achieved by adopting a knowledge management (KM) approach to systematically structure expertise and make it more accessible and easily shared. However, the engineering design environment is highly distributed and mobile in nature [3], and as a result engineering designers are frequently outside the design office to carry out other tasks and/or activities away from their usual working place [4-6]. This mobility is seen as a detriment to engineering designers as they occasionally find themselves without the knowledge support required to take the necessary decisions. On the other hand, companies are expected to deliver high quality products at shorter lead times and lower costs, so designers require adequate support even when away from their usual workplace. With the everincreasing popularity and computational power of mobile devices (such as PDAs,

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smart phones and pocket PCs), sharing and access to knowledge can be greatly facilitated. This paper presents a mobile Knowledge Management (mKM) system architecture that provides product Life-Cycle Consequence (LCC) [7] knowledge support to designers engaged in mobile work. The paper is organized as follows. Section 2 describes the mobility aspect in design, and examines how decision commitments during the design process can lead to unintended consequences. Section 3 presents a life-cycle consequence knowledge approach framework that describes how such life-cycle consequence knowledge is generated during a design solution. Section 4 describes the mKM system architecture and prototype tool developed, whilst in section 5 a small design scenario is given to demonstrate the application of such a mKM tool in design. Section 6 discusses the current benefits and limitations of the prototype, whilst conclusions and future improvements are presented in section 7.

2.

Supporting Mobility in Engineering Design

Engineering design is a complex activity, and designers need to be proficient in generating and evaluating various candidate solutions to a design problem [8], even when engaged in mobile work scenarios. This research focuses on the mobility aspect of design, where designers are away from the design office and require knowledge support to take correct design decisions to solve a particular (sub)problem. Depending on the design situation, designers may either be: x x x

Co-located: performing design activities face-to-face; Mobile: mainly either travelling, wandering or visiting [5], e.g. visiting laboratories, the shopfloor, testing departments, other buildings, or to participate in meetings with other designers or with customers; Distributed: there are different scales of distribution, from designers being separated by different floors in a building to different countries and different time-zones.

In recent years product development has experienced a significant paradigm shift and the design process is becoming more distributed and collaborative in nature [8]. Moreover, designers are finding themselves in mobile situations more than ever. From a number of empirical research studies on mobile work, it is evident that most members of a product design team very often are away from their usual workplace [4-6], i.e. they are mobile. Mobility implies that a designer is away from the usual workplace and is constantly moving from place to place. Therefore, being distributed does not imply being mobile; however it is possible to be mobile whilst making part of a design team in a distributed environment. Mobile Knowledge Management (mKM) systems have been developed in various fields [9] to support such mobile workers, regardless of temporal and spatial constraints. However, engineering designers still lack such a tool, and this research work aims at developing a prototype mKM tool that supports designers to take sound decisions even when engaged in mobile work scenarios.

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2.1 Life-Cycle Oriented Design Decision Making A decision maker has to make a choice between a number of alternatives related to a domain, as explained in [7]. These decisions have to be taken irrespective of the design stage (conceptual vs. detail) or of the synthesis viewpoint (e.g. functional or constructional). The selected alternatives, termed decision commitments [7] in this research, are a result of the synthesis decision process. A decision is made to intentionally achieve a desired consequence. However, decision-makers do not always know all the consequences of their alternatives [10]. That is, decision commitments can also result in unintended consequences that have a propagation effect across various product life-phases (such as manufacturing, use and disposal) [11]. Therefore, knowledge pertaining to the whole life-cycle should be provided to designers as from the conceptual design stage, since most of the characteristics of a product depend on decisions taken during the early design stages [12]. This research work aims to provide such knowledge to designers even when these are away from their design office.

3.

A ‘LCC Knowledge’ Approach Framework

This research considers mechanical components, which are considered as a decomposable system consisting of a number of reusable elements (i.e. sub elements), which in turn are composed of simpler elements such as form features, assembly features, material and surface texture. These elements are termed Product Design Elements (PDEs) [7]. Similarly, life phases (e.g. design, realization, use, and recycle) forming a mechanical artefact’s life, involve the re-use of technical systems (e.g. manufacturing or maintenance systems) that realize the relevant transformation effects of that phase. Models of these systems (e.g. milling machine) can also be decomposed of sub-systems (e.g. a work piece holding device), these termed Life-Cycle Phase Elements (LCPEs) [7]. A ‘Life-Cycle Consequence Knowledge’ approach framework has been adopted from [7] as the basis for the development of the mKM system architecture. The approach framework is based on these fundamental goals: x x

x

Predict consequences that are generated during synthesis, based on the commitments made; Provide solution synthesis guidance by proving a means to search for design elements that need to be committed to result in an intended consequence; (e.g. what assembly feature results in a sub-assembly that is easy to dis-assemble in the disposal phase?); Provide pro-active awareness of Life-Cycle Consequences (LCCs) and their source commitments.

The framework is presented in Figure 1, and is based on the following four frames:

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2. Synthesis Elements Frame Life synthesis element Library Assembly Features

1. Operational Frame

Materials

Sub-problem

LCPEs PDEs

•Intentions •Circumstances

3. Life Modelling Frame

Component

Knowledge of consequences and their source

Life-Phase System

Product Design Elements

Life Cycle Phase Elements

– – – Requires internet access

•Preferences

FORESEE KICAD system

LifeLife-cycle Consequence Knowledge Consequence Action Knowledge

Consequence Inference Knowledge

4. LCC Knowledge Frame

Figure 1. A LCC Knowledge Approach Framework

Operational frame: The fundamental operating principle of this frame is that a designer is mobile (i.e. away from his design office) and is working on a design sub-problem. This frame assumes that the designer is in possession of a mobile device with wireless access (such as a PDA with wireless access to a Wi-Fi hotspot). Mobile devices considered in this research are mainly Personal Digital Assistants (PDAs), smart phones and pocket PCs, because of their small physical size yet high processing speeds compared to other portable devices such as a tablet PC. In this frame the designer encounters a sub-problem and interacts with a synthesis element library (in the Synthesis Elements Frame) for a set of suitable elements. Synthesis Elements Frame: This frame consists of a synthesis element library from which the designer can search for a set of suitable elements directly from the mobile device. These elements can be Product Design Elements (PDEs), such as form features, assembly features, and material, or Life-Cycle Phase Elements (LCPEs), such as fabrication and assembly systems, encountered during the life of an artefact and that can be reused during synthesis.

Mobile Knowledge Management for Product Life-Cycle Design 141

Life Modelling Frame: Based on the designer’s intentions, preferences and circumstances, the designer commits such PDEs and LCPEs to evolve the artefact life model. LCC Knowledge Frame: The artefact model, made up of a number of elements, is submitted to a remote KICAD system (an already existing KICAD model named Foresee [7] is used in this research), which analyses the artefact model and LCCs are inferred from consequence inference knowledge. Furthermore, relevant consequence action knowledge infers actions that need to be carried out, such as changes in performance measures of appropriate life-phase metrics to allow designers to reconsider the artefact life behaviour. This knowledge of consequences and their sources is then made available ‘online’ to the designer, and this inferred knowledge is utilised for exploring such LCCs.

4.

A Mobile Knowledge Management System Architecture

This section proposes a mobile knowledge management (mKM) system architecture for supporting engineering designers engaged in mobile work. The main purpose of a KM system is to provide support for knowledge management activities [13] and provide the designer with highly valued knowledge [14]. The reasons for using KM by using collaborative technology include technology advancement, increased professional specialization, and workforce mobility [15]. The domain selected concerns the conceptual design of thermoplastic components as these provide a suitable case for artefact life exploration due to alternative PDEs and LCPEs such as form, assembly features and fabrication systems. The first module is the “Current Working Solution” module, where the model is built from reusable synthesis elements. The Model Manipulator allows the designer to add, detail and refine elements to the model that is concurrently synthesised with PDEs and LCPEs. The designer can also view a compositional hierarchy of the evolving life model on the User Interface through the Model Viewer. The second module is a “KICAD system” module [7], which provides a means of how captured knowledge can be reused in new design situations. The KICAD system was developed in wxCLIPS® [16], and it consists of a Knowledge Base with structured LCC knowledge using kind_of taxonomies. This structured knowledge base allows relevant knowledge to be revealed and utilised at the right time, with synthesis decision commitments. This module consists also of an Inference Engine which employs LCC inference knowledge to reveal LCCs associated with the solution and LCC action knowledge to enable the KICAD tool to take a proactive role in the component design. The detected LCCs are displayed on the Consequence Viewer, where individual LCC consequences can be viewed independently to represent details about its meaning, source, commitment(s) and guidance to its avoidance. Performance measures, that vary as a result of the consequences inferred, can also be seen on the Consequence Viewer. These are estimated through performance mapping knowledge employed by the Multi-X behaviour function. The two sub-modules interacting with the KICAD system are the Library Access, through which the designer can search for synthesis elements

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that result in intended consequences, and the Knowledge Manager, which provides utilities to add/modify classes/instances of synthesis elements stored in the library. The third module is the “User Interface”, through which the designer interacts with the other two modules. The user interface is mainly a web-based interface which is made up of a number of hypertext pages designed specifically to be viewed on mobile web browsers by using suitable CSS for mobile devices. The user interface also incorporates a cross-platform server-sided HTML embedded scripting language (PHP Hypertext Pre-processor) necessary for producing a dynamic web interface and also to interact with a database that temporarily stores the synthesized model. The user interface also incorporates a client-sided scripting (JavaScript) that adds functionality and interactivity to the web pages. The user interface is platform-independent, enabling access from different mobile web browsers. The automated process of generating the LCC knowledge from the committed decisions and to provide this LCC knowledge back to the designer was realized using the Visual Studio .NET® Windows Services.

Figure 2. The mobile knowledge management (mKM) system architecture

5.

Design Scenario

To demonstrate the effectiveness and applicability of the mobile Knowledge Managament system architecture, this section considers a small design scenario involved during component synthesis. The scenario considers a designer away from the design office engaged in the conceptual design of a component that is intended to act as a cover for an electronic circuitry housed in an enclosure to act as a case of a radio remote control. The requirements known at this early design stage are that 9000 such covers are required. The cover needs to be non-corrosive,

Mobile Knowledge Management for Product Life-Cycle Design 143

lightweight and to allow the case to be opened for servicing if the need arises. This scenario concerns qualitative commitments, but as the design progresses, quantitative commitments can also be made, such as the specification of parameter values, which through more specific knowledge can evolve further consequences. To satisfy the servicing requirements the designer uses the library access submodule to search for PDEs that result in a non-permanent bond, this giving rise to a decision proposal with a set of feasible options: fastener, screw, snap-fit, pop-rivet or nuts and bolts. The designer also searches for materials that have a low density and are non-corrosive. This gives rise to a decision proposal concerning various feasible alternatives: STYRON, ABS, Bakalite or Aluminium. The designer wants to explore committing ‘STYRON’, and searches for compatible processes related to this material. The system provides a set of technical process compatible with the selected STYRON material: injection moulding or milling or twist drilling or blow moulding. The designer then starts building the model by making a series of commitments: x x x

a Styron material with a screw assembly feature; an injection moulding process; and a quantity of 9000 components.

EASY DISASSEMBLY FASTENER SNAP-FIT CANTILEVER_SNAP ANNULAR_SNAP BOLT SCREW FORMED THREAD INTERNAL_THREAD EXTERNAL_THREAD

Figure 3. mKM Life Synthesis Element Library and proposed set of feasible options

These commitments are submitted to the KICAD system in the form of facts and the inference engine infers LCC inference knowledge that reveals facts associated with these commitments. In this example the LCC consequences are the following: x x x

Styron is a non-magnetic material, so there will be difficulties in separating the material during the disposal phase; A screw assembly feature results in a slow assembly, and this in turn influences the ‘use phase’ and ‘realization phase’ performance measures; The screw assembly feature also introduces the requirement of an additional hole (with parameters that include hole diameter, depth, angle, x-centre and y-centre that are still not defined);

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x x x

The injection moulding process results in a the requirement of a mould, which in turn generates its own LCCs, such as parting line defects introduced. Also, a core-pin is also added to the mould tool; The minimum economic quantity for injection moulding is 10,000, so the quantity defined earlier of 9,000 is not feasible. If the use quantity is increased to 10,000, assembly automation will be recommended by the system.

Figure 4. Decision commitments for the material and manufacturing process

The designer can select different PDEs, such as a snap-fit instead of a screw as an assembly feature, and such commitments will introduce new LCCs which can be viewed on the consequence viewer. This alternative partial solution will avoid certain consequences (such as a hole required, mould requires core, vibratory bowl required, and weld line defect) but generates others e.g. snap-fit bad for repetitive assembly, weak bond, mould requires split cavity. The designer can then compare the partial solutions and the better alternative can be chosen. The decision of which partial solution to select and proceed with is still entirely controlled by the designer.

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Figure 5. List of LCCs generated and the Performance Measures matrix

6.

Discussion

Engineering Design is a knowledge intensive activity, and designers require knowledge support even when carrying out design activities away from the design workplace. It is pointed out that although various mobile Knowledge Management systems have been developed, none have so far been specifically dedicated to support engineering designers. This paper has addressed this issue by presenting a mKM system architecture and a design scenario implemented with a prototype tool. The design scenario has demonstrated how designers can be provided with life-cycle consequence knowledge support for decision making in a mobile work settings.

7.

Conclusions and Future Work

This paper reported on the development of a mobile knowledge management system architecture. Its application during synthesis at component level from a constructional viewpoint is seen as a promising way to proactively assist designers forecast intended and unintended consequences that span the total product lifecycle when away from a knowledge base, such as the design office. Design engineers in possession of a mobile device and connected through Internet can utilise the developed mKM tool to timely obtain life-cycle consequence knowledge for a solution and be supported with ‘life-oriented’ component design solutions. Furthermore, the system allows for adding/removing of classes/instances of the stored synthesis elements of the library. However, further work needs to be carried out on the prototype tool to enhance the knowledge management aspect of the system so that dynamic management of classes, instances and parameters will be possible by the distributed/mobile actors. Also, dynamic updating and customisation of the LCC knowledge are another important future concern. Future

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work also involves the evaluation of such a prototype with practicing engineering designers.

8.

References

[1] Blessing L., Wallace K. Supporting the Knowledge Life-Cycle, in Third Workshop on Knowledge Intensive CAD, 1998, Japan: Kluwer Academic Publishers, pp. 21-38. [2] Ahmed S., Hacker P., Wallace K. The Role of Knowledge and Experience in Engineering Design, in 15th International Conference on Engineering Design (ICED '05), 2005, Melbourne, Australia, [3] Crowder R., Bracewell R., Hughes G., Kerr M., Knott D., Moss M., Clegg C., Hall W., Wallace K., Waterson P. A future vision for the engineering design environment: a future sociotechnical scenario, in International Design Conference on Engineering Design ICED 03, 2003, Stockholm, [4] Bellotti V., Bly S. Walking away from the desktop computer: distributed collaboration and mobility in a product design team, in Proceedings of ACM Conference on Computer Supported Cooperative Work, 1996: Cambridge, MA: ACM Press, pp. 209218. [5] Kristoffersen S., Ljungberg F., Mobility: From Stationary to Mobile Work, in Planet Internet, K. Braa et al., Editor. 2000, Studentlitteratur: Lunnd, Sweden. pp. 137-156. [6] Spiteri C.L., Borg J.C. Investigating mobile Knowledge Management support in Engineering Design - an empirical study, in NordDesign 2006, 2006, Reykjavik, Iceland, pp. 148-157. [7] Borg J.C., Design Synthesis for Multi-X - A 'Life-Cycle Consequences Knowledge' Approach, Ph.D., 1999, University of Strathclyde, Glasgow, Scotland. [8] Zdrahal Z., Mulholland P., Domingue J., Hatala M., Sharing engineering design knowledge in a distributed environment, Behaviour and Information Technology, 2000, 19(3): pp. 189-200. [9] Spiteri C.L., Borg J.C., Cachia C., Vella M. Requirements for a mobile knowledge management system in engineering design, in 16th International Conference on Engineering Design, ICED 07, 2007, Paris, France, [10] March J.G., A Primer on Decision Making: How Decisions Happen. 1994, New York: Free Press. [11] Borg J.C., Giannini F. Exploiting Integrated 'Product' and 'Life-Phase' Features, in Conference on Feature Modelling and Advanced Design-for-the-Life-Cycle Systems (FEATS 2001), 2001, Valenciennes, France: Kluwer Academic Publishers, [12] Andreasen M., Duffy A.B., MacCallum K.J., Bowen J. The Design Coordination Framework: key elements for effective product development, in Proceedings 1st International Engineering Design Debate, 1997, University of Strathclyde, Glasgow, UK: London, Springer-Verlag, pp. 151-172. [13] Deng Q., Yu D., An Approach To Integrating Knowledge management Into The Product Development Process, J. of Knowledge Management Practice, 2006, 7(2). [14] Fu Q.Y., Chui Y.P., Helander M.G., Knowledge identification and management in product design, Journal of Knowledge Management, 2006, 10(6): pp. 50-63. [15] Abdullah R., Selamat M., Sahibudin S, and Alias R., A Framework for Knowledge management System Implementation in Collaborative Environment for Higher Learning Institution, Jounal of Knowledge Management Practice, 2005, 6. [16] Giarratano J., Riley G., Expert Systems: Principles and Programming. 4th edition ed. 2005, USA: Thomson Course Technology.

Research on Application of Ontological Information Coding in Information Integration Junbiao Wang, Bailing Wang, Jianjun Jiang and Shichao Zhang Northwestern Polytechnical University 710072, China

Abstract A technology of ontological information coding was researched to be applied to information integration of manufacturing enterprises. The information resource was organized by classification of "information domains", and the hierarchical structure of ontological information coding system was constructed by analyzing relationship of sub-domains and information objects. Relationships between key attributes and accessorial attributes were organized by ontology, and a model of ontological information coding, which was validated by example of “Material” was formed. At last, a frame of information integration based on ontological information coding was designed with its actualizing mechanism expatiated. Keywords: Information coding; Ontology; Ontological Information Coding; Information integration

1.

Introduction

The main issues of information integration are data information model discrepancy and semantic discrepancy. As the enterprise data basic standardization, information code has supported the information standardization work commendably. The coherence and unification of information can be solved through an actual unified code system in enterprises. But how to use code in information integration and how to solve the problem of phraseological model and semantic description are a valuable study issue. There are many researches on code and ontology at home and abroad. At abroad there are BUOCS parts coding system of American Boeing Company, Germanic OPTIZ coding system,KC,KK-1,KK-2,KK-3 coding systems of Japan and so on; At home, Jiang Jian-jun [1] of NWPU has excogitated OO- flexible coding system, the OO-coding system of Pi Chang-de of Nan-jing University of Aeronautics and Astronautic, and the coding method based on object characteristic of Qian Xiaoming, all of these are researches on coding method, and none of them aim at coding system applied in integration application. And the most research investigations on ontology applied in integration focus on using the technology of WordNet and HowNet in semantic description of web net. For example, the bilingual semantic wordnet of Li Sheng [2] of Harbin institute of technology. But

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information integration technology based on ontology of manufacture enterprise is mainly designing a semantic contrasted form for the local ontology [3,4]. Indeed, an ontology is the explicit specification of the conceptualisation of a domain [5]. So in this paper, a technology combining coding and ontology has been introduced. It uses standardization of codes to figure out ontology and uses ontology to describe semantic codes, furthermore the Ontological Information Coding technology can be well used in the area of information integration.

2.

Analysis of Ontological Coding Object

Information coding, part of information standardization system, is the base of information integration.The contents of information coding standardization of manufacture enterprise are as follows: First, organizing and modeling enterprise resource system. Second, coding definite information objects. Synthesizing both of them, the definition of enterprise information code system can be got. Definition 1. Enterprise information classification coding system is a basic standardization system which contains enterprise information classification and coding identification. It describes the structure model of enterprise resource and the constitutions of enterprise information coding standardization. The enterprise resource is programmed with the information objects and attributes classified and organized in this enterprise unified coding standardization system. (1)

Constructing principles of the system There are four principles during the constructing process: Integrality, Harmony, Opening and Expansibility. “Integrality” means the enterprise information classification coding system can fully collect and coordinate information resource; “Harmony” means “information domain” is logical and compensatory, and the entire structure is harmonious; “Opening” indicates resources of the coding system is extensile; And “Expansibility” means that the whole system can be updated without overthrow.

(2)

Constituent elements of the system Information coding system contains four parts: ԘInformation sub-domains; ԙInformation objects; ԚInformation attributes; ԛInformation codes. The information sub-domains are information class domains divided by management logic in whole lifecycle of operations of manufacture enterprises; The information objects are organized by information in product line ,they are the basic of the information system; The information attributes are qualities or characters ascribed to or be inherent in a specific information, they are used in the production management process; Information codes are ascertained by key attributes, they are the ID numbers of information. The coding fundamental must be unified, compatible, steady, extensible, and abbreviated.

Application of Ontological Information Coding in Information Integration

3.

149

Technology of Ontological Information Coding

Ontological Information Coding is using the specialty that “a formal specification of a shared conceptualization” and its descriptive technique of hierarchy of notion and its support of logic ratiocination, to build the model of all parts of the information coding system, and makes a corporate cognition in the enterprise information domain. Definition 1. According to the description of Ontological Information Coding, we can get the formal definition of it as follows: OntoCode ^^C` , ^ N ` , ^ R` , ^ KA` , ^ AA`` where: C

^c1 , c2 , c3 ,...cn ` is a set of information codes˗

˄1˅

N

^n1 , n2 , n3 ,...nn ` is a set of information objects ˗

˄2˅

R

^^CR` , ^ AR`` is a set of the relationship of information and attributes.

Information relation is CR ˗Attribute relation is AR ;

˄3˅

^ka1 , ka2 , ka3 ,...kan ` is a set of the key attributes which ascertain the information codes; ˄4˅ KA

^aa1 , aa2 , aa3 ,...aan ` is a set of accessorial attributes. All of them make up of the Ontological Information Coding. AA

3.1

˄5˅

Project of Ontological Information Coding

Through the analysis of the ontological coding objects, we know the three main components as following, ԘDescription of the relationship of the resource system structure; ԙDescription of the relationship of information objects; ԚDescription of the relationship of the attributes. As shown in Fig. 1. (1)

Description of sub-domains relationship As a part of the resource, the sub-domains are the classification of every kind of information objects. Owing to the cooperation of manufacturing and management among different departments, sub-domains need specific relationship description. We mark off the concrete sub-domains and build up the organization model of the information objects, according to the characteristic of the information objects organization and the technique of “information domains” organization. And then we analyze the relationship of sub-domains to form a relationship sheet.

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Figure 1. Overview of Ontological Information Coding (2)

Information objects relationship There are two kinds of relationships of information objects. One is for information objects in the same sub-domain, which is called direct relation ( DCR ), the other is for information objects in different sub-domains, we call it as indirect relation ( ICR ).

(3)

Attribute relationship Key attributes ( KA ) and accessorial attributes ( AA ) are the characterization of information. The relationship of the attributes is showed as AR . In a word, for an aeronautic manufacture enterprise, we mark out eight sub-domains such as Product, Manufacturing Technology, Product Quality Guarantee, Resource, Production Management, Manufacture Management, Scientific Research Management, Environment and Safety. The sub-domains relationship and information objects relationship have been studied adequately. In this paper, we take the sub-domain of “Resource” for example. We design the “Material” information model and analyze the attributes relationship of material, finally form the ontological information coding model of “Material”.

3.2

Model of Ontological Information Coding

Ontological Information Coding describes the organization models of information resource and information objects. In the process, we should pay more attention on the relationship description, which must be based on professional knowledge. Take “Material” for example: Step 1: As “Material” is from “Resource” sub-domain, we analyze the information objects relationship based on professional knowledge, then we can get the relationship sheet of “Material”, as shown in Table 1.

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Table 1. Information relationship sheet of “Material” Information Object

Relationship

Material/Supplier

Be supplied/Supply

Material/Product

Form/Be formed

Material/Frock Material/Equipment Material/Stock

Be processed/Process Use/Be used Deposit in/Deposit

Step 2: After analyzing key attributes and accessorial attributes, code the information by key attribute. For example “Material”is coded by Class, Sign, State, Technic-condition and Shape; its accessorial attributes are: Use, Supplier, StoveNo, Spec and Character, as Fig. 2 shows.

Figure 2. Material code structure

Step 3: Analyze the relationship of attributes. For “Material”, “Shape” parallel to “Class”, “Spec” parallel to “Class”, “Character” lie on “Spec”, “Sign” lie on “Class”, “Technic-condition” lie on “Sign”, “State” lie on “Sign”, “State” lie on “Sign”, “Technic-condition” parallel to “State”, as Table 2 shows. Table 2. The relationship of material attributes Attribute

Relationship

Sign/Class

Lie on

State/Sign

Lie on

State/Technic-condition

Parallel to

Technic-condition/Sign

Lie on

Spec/Shape

Lie on

Character/Spec

Lie on

Technic-condition/State

Parallel to

Shape/Class

Parallel to

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Step 4: Protégé-2000 is an integrated software tool used by system developers and domain experts to develop knowledge-based systems. Applications developed with protégé-2000 are used in problem-solving and decision-making in a particular domain [6]. Furthermore it offers the API interface, so it is popular in developing ontology for many authoritative institution [7,8]. In this paper the ontology model of material developed by the tool of protégé, and its OWL [9,10] segment is the following: ...

...

4. Application of Ontological Information Coding Technology in Integration The distributed information resource management model determines that the multiattribute query of information must integrate several databases resource. An increasing trend in developing (web) information portals in the usage of ontology as a semantic means for describing the information content [11]. The simplest and most basic part of ontology-based information retrieval is concept-based information retrieval [12,13].For the model of Ontological Information Coding, we design an integration frame and a query mechanism, and then actualize the information query and integration application based on middleware. (1)

Model of integration frame In the information integration frame based on middleware, the ontology drives codes circulating in the distributed databases and in the level of ontology. The codes index information to respond to the query and return accurately. The entire integration frame has three levels, as Fig. 3 illustrates.

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Figure 3. Ontological information coding integration frame

The application system submits a query, and then the processor makes the query into a format discriminating for the ontology affirming it; ĸ The ontology matches the query and registered information to get the keyword or the code, and submits to the wrapper to transform it into the local keyword, and then accesses the databases involved;ĹThe database retrievals the getting local key words or codes, and returns the optimum result. After the three steps, the information needed can be comprehended well, and can be queried accurately. (2)

Actualizing mechanism of the integration frame For the area of a special manufacture enterprise, the integrated information is different from Internet. First, the structure of integrated information is simplex in this profession area, and it doesn’t need profound ratiocination; Secondly, the information during the lifecycle of product can be got from every department nearly. Especially after information codes bring into effect, the key attributes of information are uniform, and the difference is the accessorial attributes they used. So it is a good base for the information integration. In the premise of information code actualizing in the enterprise, the Ontological Information Coding can work well in the information integration frame, as Fig. 4 shows:

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Figure 4. Query mechanism of Ontological Information Coding

In the Ontological Information Coding integration frame, the pivotal work is the reorganization and disassembly of the query by the ontology. The following illustrations are for the designing of ontology to satisfy the individuation query of uses. x x

x

5.

The query processor matches the local key words and search words through recognizing key words input. According to the information input, the ontology model orients the source of the information, and queries the attributes in the database with analyzing of the relationship of the key attributes and accessorial attributes and the ratiocination of the ontology, and then catches the exact instance data from the databases by wrapper. The processor returns queried results after transforming their format, and arranges them in priority.

Conclusions

In this paper, the Ontological Information Coding was researched for the aeronautic manufacture enterprises. Through the definition of the Information Coding System and the description of the Ontological Information Coding, we took “Material” for example. After the analysis of attributes and the designing of ontological information coding model, the model was actualized into the integration frame. The conclusions of our work are following: x x x

It introduced a new idea of application of information coding and ontology. It took the example of material, designed the process of the ontological information coding, and modeled it with protégé. It designed an integration frame of ontological information coding model, and expatiated on the actualizing mechanism.

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As the practice showing, this technology can actualize the normative organization and representation of information resource very well. It affords an effective means of information integration in the production lifecycle. Compared with other manufacturing enterprises, the manufacturing processes and product units of aeronautic enterprises are much more complicate, which determines the difficulty of the information integration. The successful application in the area of aeronautic manufacturing of this model proves its feasibility in other domains.

6.

References

[1] JiangJianjun.An Effective Method Based on Granularity-Structure for Organizing and Utilizing Manufacturing Information Resource. Journal of northwestern polytechnical university, 2007.25 (2), 245-250 [2] LiSheng.Building Bi-lingual Semantic Lexicons Based on WordNet and HowNet.High Technology Letters, 2001 [3] Cf. T. R. Gruber. A translation approach to portable ontologies. Knowledge Acquisition, 1993,5(2):199-220. [4] Thomas R. Gruber. Toward Principles for the Design of Ontologies Used for Knowledge Sharing, Revision: August 23, 1993. [5] N.Guarino,P.Giaretta,Ontologies and knowledge bases:towards a terminological clarification,in:N.Mars(Ed.),Towards Very Large Knowledge Bases: Knowledge Building and Konwledge Sharing, IOS Press, Amsterdam, 1995, 25-32 [6] http://protege.stanford.edu, 2007.08 [7] R. F. Neches, R.; Finin, T.; Gruber, T.; Patil, R.; Senator, T.; Swartout, W.R., Enabling Technology for Knowledge Sharing. AI Magazine, 1991, 36-56 [8] http://bbs.w3china.org/index.asp, 2007.08 [9] http://www.ontoweb.org/, 2007.08 [10] Grigoris Antoniou,Frank van Harmelen.Web ontology language:OWL.In:Steffen Staab,Rudi Studer eds..Handbook on Ontologies in Information Systems.SpringerVerlag, 2003, 67-92 [11] N.Guarino,C.Masolo,G.Vetere,OntoSeek: content-based access to the web, IEEE Intell.Syst.14(3), 1999, 70-80 [12] Y. Tzitzikas, Collaborative Ontology-based Information Indexing and Retrieval, Doctoral Dissertation, Department of Computer Science, University of Crete, Heraklion, 2002 [13] H. Stuckenschmidt, F. Van Harmelen, Information Sharing on the Semantic Web, Springer, 2004.

RoHS Compliance Declaration Based on RCP and XML Database Chuan Hong Zhou1, Benoît Eynard2, Lionel Roucoules3, Guillaume Ducellier3 1

Université de Technologie de Troyes, Laboratory of Mechanical Systems and Concurrent Engineering, BP2060, F.10010 Troyes Cedex, France; and formerly, Associate Professor, CIMS & Robot Center of Shanghai University, Shanghai, China, 200072 2 Université de Technologie de Compiègne, Department of Mechanical Systems Engineering, BP 60319, F.60203 Compiègne Cedex, France 3 Université de Technologie de Troyes, Laboratory of Mechanical Systems and Concurrent Engineering, BP2060, F.10010 Troyes Cedex, France

Abstract At present, more companies are going to adapt themselves to RoHS compliance and enforcement by IT technology. This paper has presented an integration framework that utilizes RoHS Compliance Declaration based on RCP (Rich Client Platform) and XML database, which uses SOAP technology to have the flexibility to complicated network environments and multiple operating systems, makes use of XML technology ,XUL (XML User Interface Language) and XML database to acquire reuse and robustness. Keywords: RoHS Compliance Declaration, RCP, XUL, XML, XML database, SOAP

1.

Introduction

Raising awareness and understanding of harmful effects of specific substancesˈ it’s necessary to control and reduce the amounts of waste generated by used and discarded products. So laws have been made to limit the hazardous substances contained in products, in which RoHS is very famous in electrical and electronic equipment [1-4]. RoHS is intended to limit the use of substances such as lead and cadmium and is one of several rules that are forcing manufacturers to take more environmental responsibility. Similar codes in China and South Korea are also created [5]. For manufacturers, detailed data on the material composition of each component will become increasingly important. Additional changes from new legislation and from RoHS directive in other regions will force manufacturers to closely monitor the substances contained in each part. Nevertheless, many manufacturers are still far from complying with RoHS, with collecting and managing the data efficiently still remaining as the biggest hurdles. On the basis of investigation by famous

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consulting corporations, it is an important fact that collecting and managing component and materials data are proving to be the stumbling blocks for large manufacturers [6].

Figure 1. RoHS compliance Process

An overall RoHS compliance Process [6-8] is summarized in Figure 1. RoHS compliance Process has centered on materials databases. Firstly, suppliers submit material information, which must be validated before storing in materials databases. Secondly, extracting the product BOM information from PLM system, it’s necessary to build a new BOM- Compliance BOM through joining materials information from material databases. Finally, it is general to optimize the RoHS compliance process by Life Cycle Assessment (LCA) and other correlation technology. In this paper, we focus on dealing with a solution for RoHS Compliance Declaration (Figure 1. dashed rectangle) Recently, there are two main problems in RoHS Compliance Declaration [6] [9]: x

There is difficulty in finding and verifying data for thousands of parts from suppliers across the world. x Reporting to various states, countries, and legislative bodies requires multiple languages and formats. Information technology has evolved over the last few decades at an extremely rapid pace. In this paper, we present an intelligent, scalable framework for RoHS Compliance Declaration based on the development of synergistic technologies, such as RCP[10], XML, XUL[11], SOAP[12] and XML database[13], which can deal with above problems.

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The remainder of the paper is organized as follows. First, we review some of the related work. This is followed by a brief background of several key impacts of RoHS Compliance in Section 2. In Section 3, we present an overview of the integration framework, followed by RCP, XUL, SOAP, and XML database. In Section 4, we describe our prototype implementation and summarize our ongoing evaluation of the framework in the context of a case study. Finally, Concluding remarks along with future research directions are given in Section 5.

2.

Background

To the best of our knowledge, RoHS Compliance Declaration has not been previously studied in literature. However, some methods to integrate based on XML and the selection of hazardous substance and recyclable content specifications for components have been discussed. From RoHS compliance analysis aspect, Nikhil Joshi and Debasish Dutta have presented a new approach to account for regulatory requirements early in the design phase, with the aim of reducing downstream costs of compliance [7]. IPC 1752 [14] is the standard for the exchange of materials declaration data, which developed by a group of OEMs, EMS providers, component manufacturers, circuit board manufacturers, materials suppliers, information technology solution providers, and the National Institute of Standards and Technology. Though IPC 1752 is free and it is in an easy to use standard forms-PDF format, it is lacking as a total solution for RoHS Compliance Declaration. XML, due to its structured, platform and language independent, highly extensible and Web-enabled nature, has rapidly become an emerging standard to represent data between diverse applications [15]. By the way, IPC 1752 is based on XML schema to allow electronic data exchange across the web by xml file [16]. An XML database is a data persistence software system that allows data to be imported, accessed and exported in the XML format. XML databases serve in a complementary role to traditional databases especially as XML becomes prevalent [17].

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3.

RoHS Compliance Declaration

3.1

Framework

Figure 2. Information framework architecture

In this Section, we present a framework that realizes RoHS Compliance Declaration based on RCP and XML database. The information framework has a complicated structure illustrated in Figure 2. (where numbers indicate the sequence of steps). These steps are explained below: 1.

2. 3. 4. 5.

Publish the RoHS Compliance Declaration RCP. RCP is a new technology used in software development, which will be discussed in Section 3.2. First, the IT administrator will publish a software package for the RoHS Compliance Declaration RCP in his enterprise’s website. As users, compliance engineers install the RoHS Compliance Declaration RCP and start to run it. Using XUL technology, a RoHS Compliance Declaration Form can be associated with a XUL file, which will be explained in Section 3.2. We utilize XML mapping features to connect this XUL and a XML file, which will be explained in detail in Section 3.2. Using SOAP protocol, RoHS Compliance Declaration XML will be transferred to XML database, which will be explained in Section 3.3.

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RCP and XUL

3.2.1

RCP

161

The Java is dominated by browser-based thin clients. For some applications, such as shopping carts, thin clients are quite adequate. For many applications, though, thin clients suffer from one of two problems: x Lack of user interface richness and responsiveness, or x Complex, unmanageable JavaScript and DHTML. Java rich clients have traditionally been built using the Swing widget library that comes packaged with the Java Development Kit (JDK). If used with Java Web Start technology, Swing applications can solve both of the shortcomings of thin clients. An alternative to building rich client applications in Swing is to use the open source Eclipse Rich Client Platform (RCP) [18]. Eclipse is an open-source software framework written primarily in Java. In its default form it is a Java (IDE), consisting of the Java Development Tools and compiler. Eclipse RCP is the technology that the industry standard Eclipse IDE is built with. This technology was donated by IBM to the non-profit Eclipse Foundation in 2004. Since then, the use of Eclipse RCP and its corresponding widget toolkit, SWT, has exploded. Powerful commercial, shrink-wrapped software is now being written with Eclipse RCP, as are rich, responsive custom business and scientific applications. Eclipse RCP offers several advantages over Swing for building rich client applications: x

x

x x

The Eclipse framework is plug-n-play. Eclipse applications consist of an assortment of plug-ins loaded and managed by the OSGI ˉ formerly known as the Open Services Gateway initiative - now an obsolete name,is an open standards organization founded in March 1999, The Alliance and its members have specified a Java-based service platform that can be remotely managed, kernel. This gives application administrators the power to push new functionality out to users in small deployment units or even to allow users to select what functionality they want installed. Eclipse is able to load new or updated plug-ins dynamically without even requiring an application restart. SWT (Standard Widget Toolkit) widgets are fast. Because most SWT widgets are thin wrappers around the host operating system's native widgets, Eclipse applications have responsiveness that is normally found in C/C++ applications. Eclipse RCP provides a rich user interface environment. Because the original Eclipse RCP application (Eclipse IDE) was built to satisfy the needs of a demanding user base (expert Java developers), it evolved a rich set of GUI components and forms.

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XUL

The XML User Interface Language (XUL) [11] is a markup language for creating user interfaces. It is a part of the Mozilla browser and related applications and is available as part of Gecko (Gecko is the open source, free software web browser layout engine used in all Mozilla-branded software and its derivatives, including later Netscape releases.). It is designed to be portable and is available on all versions of Windows, Macintosh as well as Linux and other Unix flavors. With XUL and other Gecko components, you can create sophisticated applications without special tools. XUL is an XML language and you can use numerous existing standards including XSLT, XPath and DOM functions to manipulate a user interface, all supported directly by Gecko. In fact, XUL is powerful enough that the entire user interface in the Mozilla application is implemented in XUL. WAZAABI [19] is an open source framework, which delivers significant benefits for building Eclipse RCP applications, as reducing development effort and costs. With Wazaabi, Eclipse RCP UIs are not anymore developed using SWT but described in XML files, using the XUL standard. Thus, it is easy for designers to create UIs and for developers to create rich client components linked to server-side business logic. In this paper, we choose WAZAABI to create Eclipse RCP application. 3.3

XML Database

In Software engineering, an XML database is a data persistence software system that allows data to be imported, accessed and exported in the XML format. Two major classes of XML database exist [20]: 1. XML-enabled database: In an XML-enabled database, the documents are stored in constituent fragments. Here the XML data is stored in object relational form and one can use an XML SQL Utility (XSU) or SQL functions and packages to generate the whole document from its object relational instances. There are some representative products, for example: SQL server 2000 (Microsoft), Oracle (Oracle), DB2 (IBM) and so on. 2. Native XML database: In a native XML database approach [21], XML is not fragmented but rather is stored as a whole in the native XML database. This means that documents are stored, indexed, and retrieved in their original format, with all their content, tags, attributes, entity references, and ordering preserved. There are some representative products, for example: eXist (Wolfgang Meier), Timber (University of Michigan), Berkeley DB XML (Oracle) and so on. eXist [22] is an open source database management system entirely built on XML technology, also called a native XML database. Unlike most relational database management systems, eXist uses XQuery, which is a W3C Recommendation, to manipulate its data. eXist allows software developers to persist XML data without writing extensive middleware. eXist follows and extends many W3C XML standards such as XQuery.

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In this paper, we choose eXist to store and manage the RoHS Compliance Declaration XML using new XML features in eXist: HTTP SOAP [23] and XQuery.

4.

Prototype Implementation

A prototype of the solution for RoHS Compliance Declaration has been implemented. The prototype runs on a PC under MS Windows and its software interface, which is based on RCP (see Figure 3.):

Figure 3. Form for RoHS Compliance Declaration

There are four functions-“Save to database”, “Quary by Part/Subpart name” , “Export XML to OS” and “Import XML from OS” in this RoHS compliance RCP prototype system as shown in Figure 3. According to “Part/Subpart name”, “Quary by Part/Subpart name” function will get XML content from eXist database and automatically fill in IPC 1752 Form. On the analogy of this, “Save to database” functions will export a XML file to the local PC, or import a xml file from the local PC.

5.

Conclusions and Future Work

Over the past several years, manufacturers have faced an increasing array of new environmental mandates from jurisdictions such as the EU, China, Japan, and some U.S. states. The RoHS directive is famous in these environmental mandates. Many companies are going to adapt themselves to RoHS compliance by leveraging IT technology. This paper has presented an integration framework that utilizes RoHS Compliance Declaration based on RCP and XML database. After the discussion and studying above case, the main conclusions are drawn as follows: x x

RCP make this integration framework with both benefits of a rich client application, a thin client application and Microsoft Office; Making use of XML technology and XUL, which validate the content of a RoHS Compliance Declaration XML document as well as its Form. XML database contributing to store the RoHS Compliance Declaration XML;

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x

Flexible application of SOAP and XML makes this integration framework obtain the property of reuse and robustness, which is available for multiple operating systems and complicated network environment. Future research works may focus on studying in a deepgoing way of RoHS compliance. It includes two aspects: to research integration between PLM system and RoHS compliance by leveraging PLM technology; to optimize the RoHS compliance process by Life Cycle Assessment (LCA) and other correlation technology.

6.

References

[1] OFFICIAL JOURNAL OF THE EUROPEAN COMMUNITIES, 2000. Directive 2000/53/EC of the European Parliament and of the Council of 18 September 2000 on end-of life vehicles, October. [2] OFFICIAL JOURNAL OF THE EUROPEAN UNION, 2002. Directive 2002/96/EC of the European Parliament and of the Council of 27 January 2003 on waste electrical and electronic equipment (WEEE), February. [3] OFFICIAL JOURNAL OF THE EUROPEAN UNION, 2003. Directive 2002/95/EC of the European Parliament and of the Council of 27 January 2003 on the restriction of the use of certain hazardous substances in electrical and electronic equipment, February. [4] U.S. ENVIRONMENTAL PROTECTION AGENCY. RCRA Online. http://www.epa. gov/rcraonline/. [5] National Weights & Measure Laboratory, http://www.rohs.gov.uk/Default.aspx. [6] Eric Karofsky, December 19, 2006. “RoHS—The Data Collection Problem” http://www.amrresearch.com/Content/View.asp?pmillid=19996. [7] Nikhil Joshi and Debasish Dutta. 2006. "Towards Regulatory Compliance through PL M." In Proceedings of the IDETC/CIE 2006 ASME 2006 International Design Engin eering Technical Conferences & Computers and Information in Engineering Conference, Philadelphia, PA, Sep. 10 - 13 2006. [8] Imag Asia Limited, 2005. “Gaining Competitive Advantage through WEEE/RoHS/EL V Regulatory Compliance,” matrixone innovation Seminar 2005. [9] Jim Brown, Environmental Compliance in Electronics: Creating a Successful Strategy. April, 2006. Aberdeen Group, Inc. [10] Paul Cornell, 2007, Microsoft Corporation. Smart Documents Development Overview. http://msdn2.microsoft.com/en-us/library/aa537169(office.11).aspx#odc_ smartdocovw 1. [11] Neil Deakin. XUL Tutorial. February 19, 2006. http://docs.huihoo.com/mozilla/xul/xult u/index.html. [12] Newcomer, E. Understanding Web Services: XML, WSDL, SOAP, and UDDI. Addison Wesley Professional, 2002. [13] S. Dekeyser, J. Hidders, A commit scheduler for XML databases, Proceedings of the fifth Asian-Pacific Web Conference, 2003, pp. 83–88. [14] ASSOCIATION CONNECTING ELECTRONICS INDUSTRIES (IPC), IPC 1752 for Materials Declaration. http://members.ipc.org/committee/drafts/2-18_d_MaterialsDecla rationRequest.asp. [15] W3C, XML Inclusions ~XInclude! 1.0, 2002, http://www.w3.org/TR/xinclude/. [16] ASSOCIATION CONNECTING ELECTRONICS INDUSTRIES (IPC), IPC-1751 Generic Requirements for Declaration Process Management Version 1.1. February 200 7, pp.4.

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[17] Masayuki Shoji and Akira Mita. Application of XML database to autonomous configur ation control and data transfer for sensor networks in buildings. Proceedings of SPIE -Volume 6529 Sensors and Smart Structures Technologies for Civil, Mechanical, and A erospace Systems 2007, Masayoshi Tomizuka, Chung-Bang Yun, Victor Giurgiutiu, Ed itors, 65291F (Apr. 18, 2007). [18] The Eclipse Foundation. Rich Client Platform. August 2007. http://wiki.eclipse.org/ind ex.php/Rich_Client_Platform. [19] Olivier Moises, Arnaud Buisine. WAZAABI OVERVIEW. 2007. http://wiki.wazaabi.o rg/index.php/Wazaabi:Overview [20] Ronald Bourret.2007. XML Database Products. http://www.rpbourret.com/xml/XML DatabaseProds.htm#categories. [21] Shalaka Natu and John Mendonca, “Digital Asset Management Using A Native XML Database Implementation”, CITC4’03, October 16–18, 2003, Lafayette, Indiana, USA [22] eXist Overview. 2007. http://exist.sourceforge.net/index.html [23] Nayef Abu-Ghazaleh, Michael J. Lewis. Differential Deserialization for Optimized SO AP Performance. Proceedings of the 2005 ACM/IEEE conference on Supercomputing SC ‘05 Publisher: IEEE Computer Society, November 2005. Conan C. Albrecht. “How clean is the future of SOAP?” Communications of the ACM, Volume 47 Issue 2.

Research on the Optimization Model of Aircraft Structure Design for Cost Shanshan Yao, Fajie Wei School of Economics and Management, Beijing University of Aeronautics and Astronautics Beijing 100083, China [email protected]

Abstract In the future aircraft development, cost will be one of the most important factors to be considered. The key technologies about aircraft design for cost include: cost estimation for aircraft, establishment of cost target and life cycle cost model, evaluation and tradeoff of the cost and performance, multidisciplinary design optimization. A methodology of the development of an optimization model of aircraft structures design for cost is presented. Cost is integrated into the product definition process as an engineering parameter at the early stage of design which has a major influence on the product life cycle cost. The methodology developed is generic and fundamental in developing causal predictions of manufacturing cost. Design optimization process can be achieved by linking manufacturing cost models with structural analysis models through shared design parameters. The optimization process, which consists of single-objective and multi-objective optimization, focuses on direct operation cost (DOC) as a function of acquisition cost and fuel burn. Through contrast and analysis, the trade-off between weight and DOC is considered more reasonable than either the traditional optimization for weight or for DOC, which is proposed to be adopted in airframe structural design. Keywords: DFC (design for cost); key technology; optimization; DOC (direct operation cost)

1.

Introduction

The paper presents the key technologies about aircraft Design For Cost (DFC) and a methodology of the development of an optimization model of aircraft structure design for cost. The early stage of design is vital for a new aircraft development and cost reduction, as it decides the ultimate configuration and layout on the whole and influences the 70%~80% overall cost. United States took the lead in putting forward CAIV (Cost as An Independent Variable) in the weapon development. Zhang Hengxi[1] put forward Active Control for cost in 1980’s. Since 1990’s weapons and equipments have developed technology- concentrated, multidisciplinary and complicated, and their costs have increased sharply. For a

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long term, a conventional mode (“Cost + Cost5%”) was being applied to fix the price of Government Issue (G.I.), which was invalid for market mechanism. Along to the reform of the Chinese economy system and the trend that the military expenditure is decreasing all of the world, the cost will become one of the most important factors to be considered in China’s future aircraft development.

2.

Design For Cost (DFC)

2.1

Main Contents of DFC

Design for Cost (DFC) is an embranchment of DFX(Design for X)in the concurrent engineering. The major idea of DFC is to reduce the cost as much as possible through the analysis and research on the cost drivers during the life cycle, including design, processing, manufacturing, assembly, checking, sale, using, maintenance, recycling and disuse, and modify the part which brings the excess cost, on the premise that the customer is satisfied with the product. Its essential is the establishment of the satisfactory solution that is based on the tradeoff between performance and cost [2][3]. DFC contains such contents as follows: 1) The objective of DFC is minimum cost, subject to the performance, with cost a coequal parameter as important as others, such as technology, performance, schedule and reliability. 2) DFC is driven by engineering. DFC estimates and evaluates the Life Cycle Cost (LCC) with the support of computer tools, aiming at successful product by only once design. 3) DFC considers the cost during life cycle of product, establishing the database of LCC and the store for cost estimation methodologies. DFC minimizes LCC by designing the high quality product to reduce the using and maintenance cost. 4) DFC must harmonize with other DFX tools, which needs principles and methodologies to harmonize the different evaluation criterions. 2.2

Key Technology About Aircraft DFC

DFC is an important part of DFX which supports the concurrent engineering. Aircraft DFC should be supported by several particular key technologies except for the features of ordinary machines because of its fairly complex system: 1) Estimation Methodology for Aircraft Cost. It is an important problem to choose proper estimation method. Normally, in concurrent engineering, different methods can be used in different design phases for the different levels of the information integrality. Furthermore, there are some other factors to be considered when choosing the estimation method, i.e., production batch, aircraft type and life. 2) Establishment of Cost Target. In China, there is not very precise method to establish the cost target. In practice the military office establishes the target, considering historic data, according to the performance target, manufacture

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technique, production batch and affordability. The process is rather rough, devoid of scientific methodology to control the target. 3) Life Cycle Cost Model. It can be applied to different phases to estimate corresponding cost. 4) Evaluation and Tradeoff of the Cost and Performance. A piece of reasonable design advice can be put forward with the support of other DFX, integrating not only cost drivers but also other evaluation aspects. 5) Multidisciplinary Design Optimization (MDO). It is one of the most active fields of aircraft design. MDO is a methodology which explores and uses the interaction of engineering system and designs complex system and subsystem [4]. Actually, it provides a theoretical basis and practical method for life cycle design with the optimization principle.

3.

Cost Model for Optimization of Aircraft Structure

In aerospace, life cycle analysis tends to be associated with military application while the commercial sector focus on Direct Operation cost (DOC). The optimization for the DOC of aircraft fuselage panels has shown that by coupling the cost analysis with a structural analysis. DOC is also considered in terms of the impact of weight on fuel burn, in addition to the acquisition cost to be born by the airline operator. In this particular study, the objective function is chosen to reflect both manufacturing cost (through acquisition cost) and weight penalty (through fuel burn) but other objective functions including maintenance costs or linked to pure profitability could also be defined. The global model comprises a manufacturing cost model, a structural model and an optimization model. 3.1

Manufacturing Cost Model

The manufacturing cost analysis is based on empirical data. The cost modeling methodology for the linkage between manufacturing and design imposes a breakdown of the cost into a number of elements, including material cost, fabrication cost and assembly cost, so that it can be formulated into semi-empirical equations to be linked to the same design variables as considered in the structural analysis. A typical aluminum stringer-skin panel is shown in Fig.1. The generic product families used on a typical stringer-skin panel are the skin panel, and the stringers and the frames that support the skin in the longitudinal and lateral directions respectively. In addition, there are cleats at every stringer-frame junction and rivets that are used to fasten the structures together.

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Figure 1. Sketch of the panel

For these families (skin, stringers, frames and cleats), the overall breakdown in the manufacturing cost analysis is summarized through: 5

C panel

¦C

i

Cskin Cstringers C frames Ccleats Crivets

(1)

i 1

where C panel is the total cost of the panel and Ci the total cost for the family i. For each of the part families defined in Eq. (1), semi-empirical equations are established, which include material cost corresponding to either fabrication cost

Cim and labor cost Cil ; the latter

Ci f or assembly cost Cia . Each factor of

Eq. (1) is then computed as follows:

Ci

Cim Cil

Cim Ci f Cia

(2)

The costing coefficients appearing in the equations are determined empirically on the basis of the drawings and WBS provided by the industrial partner (AVIC I Shenyang Aircraft Industry Co., LTD). Three types of coefficients are used in the equations: the material coefficient the wage rate per hour

cim (᪳/[unit]), the time factor cil (hr/[unit]) and

ril (᪳/hr).

Cim [᪳]᧹M im ( Li , Ai ,...)[mm, mm 2 ,...] cim [᪳ / mm, mm 2 ,...]

(3)

Ci f [᪳] ri f [᪳ / h] uif cif [h]

(4)

Cia [᪳] ri a [᪳ / h] uia cia [h]

(5)

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In Eq. (3), the dimension of the material cost coefficient changes according the dimension of the material cost function MC, which depends on various geometric variables such as, for example, the part length Li or cross section Ai . The most efficient way to measure a labor cost is to use a standard labor time c, which can then be multiplied by an utilization factor u and a rate (cost/unit time) r to obtain the final cost as illustrated by Eqs. (4) and (5).

Figure 2. Cross section of the frame

Fig. 2 shows an example of the frames used to strengthen the panel. The material cost for the frames is computed as a function of the volume. The frames are supposed to be straight and of a “C” cross-section. We suppose that they extend over the width of the panel so that their length corresponds to the panel width W. All frames dimensions are deduced from the drawings. If tf is the frame thickness, hf the frame height, lf the frame flange length, the volume Vf of one “C” shape frame is:

Vf Given

ª 2l f h f t f 2t 2f º W ¬ ¼

(6)

f n frames the number of frames, the material density and c frames (᪳/g) the

material cost coefficient, the material cost for the frames is computed by:

C mframes

n framesV f U c mframes

(7)

l

The frame labor coefficient c frames (hr/hole) is supposed to be directly proportional l

to the number of lightening holes in the frames nholes . If rframes is the frames labor cost per hour (᪳/hr), the total frames labor cost can be calculated as follows:

C lframes

l n frames nholes rframes c lframes

The other family parts’ costs can be calculated in the same way.

(8)

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Life Cycle Cost Model

The cost model can be extended to life cycle by computing the direct operation cost (DOC) that is associated with the cost of transporting a given weight of aircraft structure during the aircraft’s life span. For commercial transport applications, the DOC is a function of the acquisition cost, fuel burn, maintenance, crew and navigation, and ground services.

DOC

f ( acquisition, fuel burn, ma int enance, crew and navigation, ground services )

(9)

As this work is concerned with linking and trading off structural efficiency with manufacturing cost, all DOC drivers can be said to be fixed apart from the acquisition cost and fuel burn. Acquisition cost is driven by the cost of investing money to pay for the cost of the aircraft amortized unit manufacture, plus a profit margin. Fuel burn is a function of the Specific Fuel Consumption and the cost of fuel and therefore can be said to be a function of weight in the current context. The DOC function that is used for optimization purposes later in this paper is summarized by Eq. (10). Although profit is a more obvious objective function, DOC can be more readily assessed as one form of an objective goal. It is composed of two terms: the acquisition cost (AC) and the fuel burn (FB), the acquisition cost being the manufacturing cost (MFC) multiplied by a weight factor n.

DOC 3.3

FB AC

FB n MFC

(10)

Structural Model

The structural analysis was idealized as shown in Fig. 3, where b is the stringer pitch, h the stringer height, t the skin thickness and ts the stringer thickness. The panel could be loaded under uniform compression, with loading intensity p, or under compression combined with a uniform shear flow. The failure modes considered are flexural buckling, local buckling, inter-rivet buckling, and material failure based on the allowable stress of the aluminum alloy material.

Figure 3. Modeling of the panel for structural analysis

No local buckling was permitted, ruling out post-buckled designs.

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For flexural buckling the panel is assumed to be simply-supported at the frames, and wide enough to ensure that there is no interference between adjacent stringers. Euler’s formulae then give for the flexural buckling stress [5]:

VF

S 2 E / LF / qs

2

(11)

where E is the elastic modulus, LF is the frame pitch and qs the radius of gyration of the stringer with its attached skin.

qs

I s / As

(12) 4

where I s is the section moment of inertia with its effective skin ( mm ), As is the 2

section area of the stringer with its effective skin ( mm ). For local buckling, the buckling stress is given by:

VL KL

KL E t / b

2

(13)

2

2

S kc / [12(1 Q e )]

For the generic aluminum alloy, the coefficient

(14)

Qe

locates between 0.3~0.33.

K L can be expressed as an function of the ratios h/b and ts /t. For the inter-rivet buckling stress the usual empirical formula is used:

VR

K R E t / rp

2

(15)

in which K R =ҏ2.46 for conventional, round-head rivets and rp is the rivet pitch. In practice, it is not easy to make the flexural buckling take place; furthermore, in this paper, the panel is loaded at a relatively small value of compression which is far from fracturing the panel out of engineering experience. Compared to Eqs.(12) and (14), it is obvious and easy to estimate that the flexural buckling stress is largely greater than local buckling and inter-rivet buckling stress, so the structural restriction is based on the simultaneous local buckling and inter-rivet buckling. The rivet pitch makes a major contribution to the cost of manufacture while the formula for inter-rivet buckling stress V R contains the rivet pitch. Such arrangement is consistent with the importance of rivets in this model and considered to be more reasonable than R.Curran [6]. Link Eqs.(13) and (15), a trade-off buckling stress can be given:

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V*

Et

2

K L K R / brp

(16)

Therefore in the cost-weight optimization procedure, the applied stress is:

V

p/t

(17)

where t is the equivalent (smeared) thickness,

t

As / b

(18) *

In the optimization the applied stress is not permitted to be greater than V . 3.4

Optimization

The goal of the optimization process is to link together the structural analysis and the cost analysis in order to define the design configuration that meets the structural requirements while minimizing the cost to the airline operator. For Eq. (10) the acquisition cost contributes two to four times more than the cost of fuel burn to the DOC. It was shown that a 50% weighting for acquisition cost and 15% weighting for fuel burn is reasonable for the DOC split for an aircraft [7]. Consequently, the factor n was determined by fitting the cost results for a panel traditionally optimized for weight and the above mentioned percentage. The fuel burn was taken to be 800᪳/kg and a value of n =2~3.5 was obtained. The active design variables were chosen to be: stringer pitch b, stringer height h, skin thickness t, stringer thickness ts and rivet pitch rp. The frame pitch was not varied and the panel was loaded in pure compression. Two types of optimization for the panel were carried out. One was the singleobjective optimization, the other was multi-objective. Single-objective: the panel was optimized for minimum total weight, minimum material cost, minimum total manufacturing cost and minimum DOC. The total weight and the cost of the first optimization (traditionally optimized for weight) were used as the reference for the decrease or increase in corresponding items in the subsequent optimizations. It was found that the various criteria for optimization lead to widely differing panel dimensions (see Table 1). As a result of minimization of DOC, all dimensions are all largely greater than that of the first optimum (for weight). The key observation is that the optimization is tending to drive the design towards fewer stringers that are larger and with a greater rivet pitch, which is consistent with the impact of riveting on manufacturing cost. Savings according to the different objectives are given in Table 2 (compared with the optimization for weight). Positive values denote reductions relative to the reference panel and negative values indicate an increase. The minimization of material cost and total manufacturing cost don’t show improvements with regard to

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DOC. Optimization for DOC shows a substantial improvement of the total DOC. The actual saving of ᪳896.70/m2 would relate to a rough order of magnitude DOC saving of ᪳475000 for the complete barrel section of the fuselage. Table 1. Panel dimensions after single-objective optimization(W=weight, MC=material cost,MFC=manufacturing cost, DOC=direct operation cost. All dimensions in mm) b

h

t

ts

rp

min W

105.6

10.4

1.50

1.61

85.7

min MC

99.8

45.7

0.80

7.23

49.7

min MFC

238.2

16.8

2.05

4.09

166.3

min DOC

150.5

15.2

1.82

2.51

100.0

Objective

Table 2. Savings according to the choice of objective (W=weight, MC=material cost,MFC=manufacturing cost, DOC=direct operation cost. All cost savings are in ̞ per m2 of panel, weight in kg per m2. Negative value indicates an increase) Saving in Objective MC

MFC

DOC

min MC

12.22

19.22

-2658.96

min MFC

-12.20

512.60

-163.23

min DOC

-50.34

456.12

896.70

Multi-objective: because the weight is traditionally the most important indicator for aircraft structure, the optimization was carried out for minimum weight and material cost, minimum weight and manufacturing cost, minimum weight and DOC. Panel dimensions and savings (compared with optimization for weight) after multiobjective optimization were shown in Table 3. Table 3. Panel dimensions and savings after multi-objective optimization (W=weight, MC=material cost,MFC=manufacturing cost, DOC=direct operation cost. All dimensions in mm. All cost savings are in ̞ per m2 of panel, weight in kg per m2. Negative value indicates an increase) Dimensions

Saving in

Objective b

h

t

ts

rp

W

DOC

min W & MC

99.8

18.6

0.95

2.11

50.8

-1.88

-150.38

min W & MFC

120.6

14.3

2.02

3.63

152.3

-3.36

-172.54

min W & DOC

136.3

10.8

1.72

2.50

96.3

-0.88

613.66

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Dimensions and savings of optimization for minimum weight and DOC located between that of optimization for weight and DOC respectively, so were the other two. The single-objective optimization proved the optimization for minimum DOC might be considerably an appropriate choice for structure design. However, total weight is the vital influence factor for all performances of the aircraft. The tradeoff between weight and DOC would be more conservative than either objective respectively; nevertheless it keeps a relatively low level of weight all the same and saves a lot of direct operation cost. It can be considered to be the most moderate design.

4.

Conclusions

It is concluded that main finding of the paper is that several key technologies are put forward based on the trend of rapidly increasing cost of weapons and the great importance of the early design stage of aircraft, especially an optimization model of aircraft structures design for cost is established by linking manufacturing costs models with structural analysis models through shared design parameters. The optimization process, which consists of single-objective and multi-objective optimization, focuses on Direct Operation Cost (DOC) as a function of acquisition cost and fuel burn. The optimization for minimum weight and direct operation cost simultaneously brings a reasonable result that is more efficient and economical than that of either single-objective optimization. This might be considered a favorable result.

5.

References

[1] H.-X. Zhang, J.-Y. Zhu, J.-L Guo. “Warplane type development engineering guide”. Beijing: National Defense Industry Press, 2004, pp. 49. [2] X.-C. Chen. “Research on theories and methods of Design for Cost(DFC) in Concurrent Engineering”. Dalian University of Technology, 2000, pp. 67-85. [3] J. Zhan. “A project cost control model”. Cost Engineering, vol. 40, no. 12, pp. 31-34, 1998. [4] Z.-Q. ZhuˈX.-L. Wang. “Multi-disciplinary optimization and numerical simulation in civil aircraft design”. Acta Aeronautica et Astronautica Sinica, vol. 28, no. 1, pp. 1-13, 2007. [5] D.-H. Cui. “Handbook of structural stability”. Beijing: Aviation Industry Press, 1996, pp. 13-15. [6] Curran R., Rothwell A. and Castagne S., “A numerical method for cost-weight optimization of stringer-skin panels”, Proc. 45th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics & Materials Conference, AIAA 2004-2018, pp. 13-14, 2004. [7] Labro E., “The cost effect of component commonality: a literature review through a management-accounting lens”, Manufacturing & Service Operations Management, Vol. 6, No. 4, pp. 358-367, 2004.

Research on the Management of Knowledge in Product Development Qian-Wang Deng, De-Jie Yu College of Mechanical & Automotive Engineering, Hunan University, ChangSha, China, 410082

Abstract Knowledge has been recognized as one of the most important resources for the success of product development. An approach on integrating knowledge management into product development processes is proposed. In the approach, the product development process is analyzed through the state-process-resource modeling method. The product development process model provides the context for structuring knowledge and organizing designers. It leads to a user-oriented structure of knowledge produced and used in product development tasks and a process-based informal network of product developers. In addition, the integration between knowledge management processes and product development processes gives not only guidance for managing knowledge activities, but also an optimization for product development process modeling. Keywords: Knowledge Management; Process Modeling; Product Development

1.

Introduction

A product development process means the whole stage from product idea to production preparation, which consists of product planning, product design, and product production preparation sub-stages. Generally, it may be concluded that the product development process is a knowledge-intensive process. The support for knowledge handling is very important for product developers [1]. A popular definition of knowledge derived from computer science considers the premise that knowledge can be organized into a hierarchy of data, information, and knowledge. Data are facts, images, or sounds only, without contextual meaning. Information is formatted, filtered, and summarized data. When information is contextually applied in domains, it becomes into knowledge. Knowledge is instincts, ideas, rules, and procedures that guide actions and decisions. Two types of knowledge, explicit knowledge and tacit knowledge, are generally accepted in the field of knowledge management [2]. Explicit knowledge is that component of knowledge that can be codified. It can be found in the documents of an organization, e.g. reports, articles, manuals, patents, pictures, images, video, sound, software, etc. Tacit knowledge, however, is the internal knowledge that exists in

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people’s brains. It is subjective and experience based knowledge that is highly personal and hard to be expressed in words, sentences, numbers or formulas, making it difficult to communicate with others. In order to work successfully and to make the right decisions at the earliest time possible especially when applying computer support with its multiple simulation possibilities, product developers are looking for a knowledge assistant environment [3]. On one hand, novice designers need it to help learning all of the knowledge about processes, methods, tools, experience, skills, and design strategy in order to fasten their progress from novice to experienced designers. On the other hand, experienced designers also need it to quickly access information and knowledge from other experts. Knowledge management (KM) is such a multi-disciplinary infrastructure to provide product developers with knowledge about methods, instruments, and tools, in order to enhance the product development performance by providing the right knowledge at the right time to those who need it. Many literatures have been contributed into the research of KM [4]. For example, Literature [5] initiates the so-called GAMETH Framework, in order to locate crucial knowledge for business processes in enterprises. The main objective of this work is to propose an approach on integrating knowledge management into the product development process.

2. Steps of Integrating Knowledge Management into Product Development Knowledge embeds in the product development process, while knowledge management fosters the processes of knowledge creation and knowledge sharing in the product development process. An effective and efficient application of knowledge may improve the performance of product development and add additional value to products. Figure 1 depicts an approach on integrating knowledge management into product development. It consists of the following five steps. The first step is to analyze product development processes through process modeling. The product development process should be analyzed in order to identify knowledge existing in the domain of product development, and to examine what knowledge is needed in accordance with each activities of a product development process. The goal is to enable context-sensitive storage, more purposeful access to information, and better integration of the process-oriented, day-to-day work of the employee with the knowledge management system. The result of this step is a process model of product development. The second step is to identify and structure knowledge in product development through the process model. The result of this step is a structure of knowledge in product development. More details are discussed in section 2.2. The third step is to add people to each process elements of the product development process. The result of this step is an informal network of knowledge workers who share similar goals and interests in product development processes. For example, a network of knowledge workers can be organized according to knowledge domains. A knowledge domain is a common area of interest. Since the

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individual members of a given knowledge domain can be spread across different departments or locations, it is useful in facilitating knowledge sharing and knowledge creation within any organizations. The main objective of building knowledge worker networks is to cultivate and nurture the organization’s tacit knowledge and to support knowledge sharing between people who have same interests, not to replicate the existing departments and organizational structures.

Product Development Process Modelling

Structuring Knowledge

Organizing People

Integrating KM Process Models into Product Development Process Models

Analyzing Suitable Technologies

Figure 1. Steps of integrating knowledge management into product development

The fourth step is to integrate the knowledge management process model into the product development process model. A knowledge management process is a set of activities to make knowledge life cycle (e.g. knowledge identification, acquisition, access, use, creation, and storage) more effective as well as more efficient. The result of this step is an integration model of product development processes and knowledge management processes. The fifth step is to analyse and choose suitable technologies supporting the knowledge management activities in the product development process, e.g. groupware, yellow page, information retrieval tools, content management systems, and knowledge repositories, etc. Two main aspects have to be taken into account in developing knowledge management systems. The first is the provision of assistance for the direct, inter-human KM processes, e.g. communication and collaboration. The second is the management of generation, distribution, access and use of knowledge coded into artifacts (documents, training, and videos, etc), e.g. information management.

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2.1

Analyzing Product Development Processes through Process Modeling

Knowledge management and product development processes are interlinked. Therefore, a product development process can be viewed as the nexus around which knowledge is shared, used, and generated. Knowledge-oriented product development process modeling and analysis clarify what knowledge and information sources are required for, or created in the product development process, what knowledge and information flow happens within and between the knowledge-intensive product development process, and how processintrinsic parameters influence knowledge and information needs. Approaching knowledge-oriented product development process modeling is a foundational enabler for knowledge management, because it builds the basis for process-oriented knowledge archives and efficient access to such archives. In context of knowledge management, the purposes of analyzing product development processes through process modeling are x x x

To identify, classify and structure knowledge, To help understanding how product development processes, people, and knowledge are organized relating to each other together, and To reveal who needs what knowledge and who possesses what knowledge.

In this section, the state-process-resource modeling method is used to analyze the product development process. The detail of the state-process-resource models in product development has been discussed in literature [6]. According to the stateprocess-resource model, there exist three kinds of objects: product (state), process (element), and resource. Product development is considered as such a system that combines the product states, development processes, and resources. The product (state) objects define what a product is in a given state (knowledge of “know-what” and “know-why”), whereas objects of both process (element) and resources describe how the product is developed (knowledge of “know-how”). During a product development process, there are many results at the intermediatestages. The results of a product at the intermediate-stages are called product states. A product can be modeled as a set of product states, e.g. product requirements, product functions, product principles, product geometries, product structures, and manufacturing process, etc. Each product state is a sub-kind of a product. A product development process is a compilation of process elements that change a product from one state to another state, and the relationships between the process elements. A process element describes an activity in a product development process model. The process elements, consisting of some work-steps, are the basic component in a process model. In this work, approximately 67 generic process elements, which cover all of the stages of the product development process are collected and used as a dimension of knowledge classification criteria, in order to identify all of the tasks or activities in the product development process [6]. These generic process elements are independent on any products and corporations.

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2.2 Identifying and Structuring Knowledge in Product Development through Process Models In product development processes, knowledge has to be modeled, appropriately structured, and interlinked for supporting its flexible integration and its personalized presentation to product developers [7]. The product development process provides the context for knowledge. It leads to a user-oriented structure of knowledge produced and used in product development tasks [8]. Linking knowledge to the product development process elements helps: x x x x x

Analyzing or auditing previous company knowledge corresponding to each element of the product development process model; Judging whether the knowledge regarding to each element of the product development process are currently scattered around the company; Understanding where, when and what knowledge is needed within each element of the product development process; Assisting decision of the suitable format of knowledge representation respective to each element of the product development process; Guiding the index of the structure of knowledge in repository.

Knowledge in a product development process can be divided into the product knowledge and the process knowledge of product development. The product knowledge describes the states of a product, such as knowledge about product market, requirements, functions, behavior principles, structures, specification, service documents, and instruction manuals etc. The process knowledge of product development describes how a product is developed and why a product is so developed. Literature [8] gives a process-based structure of knowledge in product development. 2.3

Adding People to Elements of Product Development Processes

Employees are the bearers of knowledge and the users of knowledge management. Since knowledge is intrinsically linked to people, linking employees with each process element of a product development process model can help to identify people who use or create knowledge in each process element of the product development process, who possesses what knowledge and what knowledge is needed by whom in each process element of the product development process. It shows how people are connected to each process element and the knowledge content of the product development process. In another words, it helps auditing tacit knowledge in a product development process because that tacit knowledge exists in brains of people. In addition, adding people to each process element of the product development process is useful when constructing knowledge communities and expertise locating systems, the key ways to share and distribute tacit knowledge. The results of the link are some informal networks of people who are involved in the common process element of product development (see figure 2(b)). These informal networks of people are process element oriented. They are different from the traditional topographical focused (or department oriented) networks of people

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(see figure 2(a)). Figure 2(a)(b) depict a same organizational structure, but in two different forms. Location #1 (Department #1)

Location #2 (Department #2)

Process Element #1

Process Element #2 (Location #1, #3)

Location #3 (Department #3) Process Element #3 Employee (a)

Employee (b)

Figure 2. Two Types of Organization of People

2.4 Integrating the Knowledge Management Process into the Product Development Process In a product development process, there exist two major classes of behaviors. First, there are those behaviors directly associated with the overall product development process. Second, there are those behaviours that support the knowledge management process that enables and improves the product development process. Therefore, the integration of the knowledge management process into the product development process is a dominant recommendation and a pressing research issue [4]. A knowledge management process is a compilation of activities which enable and facilitate generation, sharing and use of knowledge for the benefit of product development. Although there have existed many models of a knowledge management process, these models have still at least two limitations: one is that they ignore to explicitly modeling the processors correspondent to the activities of knowledge management; the other is that they lack of an explicit integration of a knowledge management process model and a product development process model [6]. Literature [6] distinguishes four roles of knowledge workers. They are knowledge managers, knowledge engineers, knowledge analysts, and knowledge individuals. Therefore, a knowledge management process can be modeled from the four perspectives of knowledge managers, knowledge engineers, knowledge analysts, and knowledge individuals, respectively. The activities performed by knowledge managers include developing KM strategy, planning KM processes/methods, identifying the network of people, and measuring KM. It should be stated that these activities usually run in parallel, and are the center of all other activities (e.g. performed by other knowledge agents) that are initiated and controlled from here.

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Knowledge analysts, acted by selected qualified domain experts, are familiar with the tasks in product development. They know what knowledge is needed in the product development process, and clarify the need for knowledge in product development. Then, they structure the knowledge about product development. The results of the structuring constitute the fundamentals of knowledge maps (and/or) knowledge repositories. The structure of the knowledge in product development also guides knowledge engineers identifying what knowledge exists in knowledge resources. Then, knowledge engineers acquire knowledge from knowledge resources into knowledge management systems. Before being stored into knowledge repositories, the acquired knowledge should be evaluated by knowledge analysts, whether it is right and/or suitable for product developers to deal with tasks in product development. The knowledge, which has been evaluated as “positive”, is stored to knowledge repositories. These activities always run in cycles, and initiate the development of knowledge management systems. The knowledge stored in knowledge repositories can be re-used by knowledge individuals. During product development processes, knowledge individuals (product developers) identify the requirements of knowledge in tasks. Then, they search for (under assistance by knowledge management systems) appropriate knowledge, and apply it in the tasks of product development. If new knowledge is created, it can be published (codified). The published knowledge should also be sent to knowledge analysts for an evaluation. Then, the “passed” knowledge is stored into knowledge repositories for the re-use in the future. These activities form a cycle to support product development processes. To realize the integration between the knowledge management process model and the product development process model, there is a basic rule to be followed: considering the knowledge management process as a special kind of sub-process in product development processes. Therefore, similar to the definition of a product development process, a knowledge management process is a set of many KM process elements or sub-processes associated with KM. A sub-process associated with KM, called KM sub-process, is also a set of KM process elements or other KM sub-processes. The logical relationships between sub-processes and/or process elements can be grouped into sequence, parallel, alternative, couple, and loop. Figure 3 illustrates the place of the KM process elements in the product development process model. The knowledge management process is dealt with as such an accompanying sub-process of other “normal” sub-process (or process elements) in product development processes. The KM process elements (activities) in the knowledge management processes are also considered as such accompanying activities of other process elements in product development processes. Therefore, the KM process elements run parallel to the “normal” product development process elements or sub-processes. For example, the generic process element “search for principle” in product development processes is always accompanied with the KM process element “access knowledge” in knowledge management processes. These two activities run usually parallel to each other. The detail of the integration model can be found in literature [6].

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Product development processes sub-process (the KM process)

“normal” sub-process

process element

“normal” sub-process

sub-process (knowledge individual) sub-process (knowledge analyst) sub-process (knowledge engineer)

...

process element

process element

...

sub-process (knowledge manager)

Figure 3. An example showing the KM process as a sub-process of product development processes

2.5 Choosing Suitable Technologies Supporting the Knowledge Management Activities in the Product Development Process The two most dominant approaches to deploying KM services are codification and personalization [9]. In a general sense, the codification approach is more suited to situations where work tasks (e.g. tasks of variant design or adaptive design) are similar and existing knowledge assets can be adapted for reuse. The personalization approach is appropriate for situations where work tasks (e.g. tasks of new product development) are fairly unique, and it is difficult to reuse knowledge from task to task without significant modifications. 2.5.1

Codification-oriented Services

Codification-oriented KM services can also be called “people-to-knowledge” services. Theses services provide facilities for storing knowledge and accessing (including indexing and searching) the stored knowledge. Technologies that support for knowledge storage span from relational database management systems to document management systems. A technology-enabled knowledge storage is typically defined by the content and structure of knowledge. The content refers to the actual knowledge stored. The structure refers to how each “knowledge unit” is specified, the format in which it is represented, the indexing scheme and how each “knowledge unit” is linked to others. Indexing and classification services are usually facilitated by knowledge maps that define the channels and the mechanisms available for knowledge categorization.

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The keyword search that is provided by most Internet search engines offers a simple and easy way to retrieve documents in which knowledge embeds. One main problem with the keyword search is that not all documents (in which knowledge embeds) use the same words to refer to the same concept. Hence, metadata, that describes the concepts that the documents refer to in a controlled vocabulary, are assigned to documents. Therefore, metadata allow a transition from keyword searching to concept searching. Concept searching enables search terms to be expanded to cover a series of related terms. To improve precision in domain searching by reducing the ambiguity of ordinary words, technologies of taxonomy and ontology are used for searching. These technologies allow for the organization of concepts based on a schema of concepts and relations between concepts. They allow knowledge to be retrieved in a context, which helps users to assess their applicability to tasks in hand. 2.5.2

Personalization-oriented Services

Personalization-oriented KM services can also be called “people-to-people” services. These services provide rich, shared, virtual workspaces in which interactions occur between knowledge workers (people) who share a common goal. Theses services provide facilities for the communication and collaboration between knowledge workers. Groupware is a basic technology that offers a platform for communication and collaboration between knowledge workers. This is especially the case for distributed and virtual product development project teams, where team members are from multiple organizations and in dispersed locations. Examples of common features offered by groupware tools are e-mail communications, messaging, discussion groups, and information management tools (e.g. calendar, contact lists, and meeting agendas etc). Common platforms/groupware are Intranets, MS Exchange, Novel GroupWise, and Lotus Notes. Videoconference & visualization systems and computer-mediated collaboration provide tools for knowledge workers to communicate each other efficiently. They provide a closer approximation to the actual face-to-face interaction. This supports the process of knowledge sharing. Workflow management systems also provide collaborative services for knowledge workers. They bring controls to processes that require many people to work on a set of documents. 2.5.3

Some Other Services

Besides of the above-introduced KM services, there are also some other services. General information technologies (IT) provide knowledge workers with tools that improve personal efficiency, e.g. word-processing software, spreadsheets, and databases etc. For example, knowledge workers write reports by using word processing, spreadsheets, and presentation software etc, so that knowledge can be documentation, and the documents can be exchanged easily throughout a company.

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Specific application systems are optional customized and designed to solve engineering application tasks. Artificial intelligence (AI), e.g. expert systems, data mining, and knowledge discovery etc, can be applied in these systems.

3.

Conclusions

The product development process is a knowledge-intensive domain. Knowledge has been recognized as one of the most important resources for the success of product development. In this work, a five-step process modeling-based approach of integrating knowledge management into product development was suggested. In the approach, the product development process, the application domain of knowledge management, was analyzed through the state-process-resource process modeling method. The product development process model provides the context for knowledge. It could lead to a user-oriented structure of knowledge produced and used in product development tasks. The integration between knowledge management processes and product development processes gives not only guidance for managing knowledge activities, but also an optimization for product development process modeling.

References [1] Ahmed S, Wallace KM, Blessing LT, (2003) Understanding the differences between how novice and experienced designers approach design tasks. Research in Engineering Design, Volume 14, Issue 1, p.1-11. [2] Nonaka I, Takeuchi H, (1995) The knowledge-creating company: how Japanese companies create the dynamics of innovation. Oxford University Press, Oxford, UK. [3] Vajna S, (2006) Integrated Product Development. Vorlesung von Lehlstuhl Maschinenbauinformatic, Institute für MaschinenKonstruktion, Otto-von-Guericke Universität Magdeburg, Magdeburg [4] Mertins k, Heising P, Vorbeck J, (2003) Knowledge Management Concepts and Best Practices, 2nd ed. Springer, Berlin Heidelberg New York Hong Kong London Milan Paris Tokyo [5] Grundstein M, Rosenthal SC, (2005) Towards a Model for Global Knowledge Management Within the Enterprise (MGKME). In: Proceedings IRMA'2005 International Conference, Research in progress Managing Modern Organizations with Information Technology. San Diego, California, USA [6] Deng QW, (2007) A Contribution to the Integration of Knowledge Management into Product Development. PhD thesis. University Magdeburg, Magdeburg, Germany [7] Sure Y, Staab S, Studer R, (2004) On-To-Knowledge Methodology (OTKM). In: S. Staab and R. Studer (eds.), Handbook on Ontologies. Springer, Berlin, New York. [8] Deng QW, Yu DJ, (2006) Mapping Knowledge in Product Development through Process Modeling. Journal of Information and Knowledge Management, Vol.5, No. 3 [9] Tsui E, (2003) Tracking the Role and Evolution of Commercial Knowledge Management Software. In: Holsapple, C.W. (ed.) Handbook on Knowledge Management, Volume 2. Springer, Berlin Heidelberg New York Hong Kong London Milan Paris Tokyo

Representing Design Intents for Design Thinking Process Modelling Jihong Liu, Zhaoyang Sun School of Mechanical Engineering and Automation, Beihang University, Beijing 100083, China

Abstract Design is the process in which designers use their expertise and experience to acquire design solutions. Most design results can only exhibit what the design is, but cannot reveal how and why an artifact is designed the way it is. Design intent is the motivations, rules and reasons behind design activities, and the capture, representation and transmission of design intent are of great significance to externalization of tacit knowledge. This paper addresses the representation of design intent for design thinking process modeling. The design thinking process model (DTPM) is composed of design intents, process knowledge and operations. The basic elements and categories of design intents are discussed in detail and eight types of design thinking process segments are expressed by the relationship of design intents and design operations. The examples of an original design process and a routine design process are taken to embody and validate the model. Keywords: Design thinking process, Design process modeling, Design intent

1.

Introduction

Usually, the final outcomes of design processes are technical documents such as drawings, development reports and three-dimensional shape models. These results are not only the embodiments of the design, but also the technical information carriers or vehicles for communication among designers or between designers and manufacturing engineers. However, they do not record the design motivations, intermediary options and solutions, nor the reasons behind them. That is, they can only describe what the design is, and do not explicitly reflect how and why the design is done the way it is. Although the designers can write down what and why they think, or how they do by themselves in their engineering notebooks, the descriptions are too casual to be shared and reused. The lack of this information make it difficult for other users to understand and modify the design. The purpose of this paper is to capture and represent design intent, and to construct the design thinking process model (DTPM). Based on design experiments, elements and classification of the design intents are identified. The formalization of the DTPM is given.

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Related Work

Related work concerned with capture and representation of design intent can be divided into three categories: function, feature and design rationale. Artefact functions are the primary design intents and design intents are the reflection of functions in a design thinking process. In [1], design intents are defined as the functional requirements provided by customers. By translating the commands sequence, the designer’s intent can be implicitly translated. Gero[2] constructs situated fuction-behaviour-strcuture framework to represent design in a dynamic and open world. Although exploration of the function models helps capture and represent design intent, most of the results of these researches can only be applied in the conceptual design stage. Feature is taken as the carrier of design intent, and it is expected that design intent can be captured by feature cognition. Wang[3] develops a scheme for feature-based reference design retrieval to provide designers with easy access to relevant knowledge. Both assembly and joining intents are captured as the form of assembly and joint feature in [4]. In the design intent modeling system implemented by Arai et al.[5], the design thinking process is described by intents, operations and design flows. Feature formally represented is readable for computer and can easily be shared and communicated. However, because of the limitation of the form of feature, it can only present design intent indirectly and be applied in specific domains (such as CAD system). Design rationale is the reason for design thinking or activities, and it can be understood in three facets: argumentation, documentation and communication[6]. A argumentative model, QOC (Questions, Options, and Criteria) built by MacLean et al.[7] stresses the explication of the space of possible designs and the rationale for choosing the appropriate designs within the space. Ganeshan proposes a model to represent design intents from the perspective of documentation[8]. The design intents are captured by preserving all the objectives and their evolution tracks. ADD+ developed in [9] assigns intents and beliefs to the user model from heuristic rules applied to the combination of the design dependency graph and design history. Design rationale models can reflect the nature of design intents, however, they are too abstract to be formally described and understood by computers.

3.

Design Thinking Process Modelling

3.1

Design Experiment

Design experiment is an empirical approach to exploring design cognitive activities[10]. The experimenters in the design experiment are required to complete a design task with the method of thinking aloud (TA), i.e. speaking out their thought during a design process. Their verbal reports and all design operations are recorded by the audio-video equipment. The verbal data are coded and analyzed by the method of protocol analysis (PA). In this study, design experiments are carried out to investigate and clarify the elements of the design thinking process. The task

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is to design a cash deposit mechanism for an Automatic Teller Machine (ATM). The whole experiment process is recorded by an audio-video recorder. The detailed experiment procedure includes four steps: explanation of the design task and requirements, progress of design, visual and verbal recording, and code and analysis of the data. Based on analysis of the protocols, three categories of cognitive states are recognized as intent, option and solution. Intent reflects what the designer wants to do, e.g., ‘I want to design the sorting part at first’ shows that the designer’s intent was designing a machine of sorting. Option is the candidate design alternative for realizing the intent. Solution is the decision made by analyzing, comparing, evaluating and synthesizing the options. Along with the cognitive states, tacit knowledge as know-how in the design thinking process which is different from product knowledge is extracted. The process knowledge is classified into three categories, i.e., rules, criteria and reasons. Rule is the guideline that the experimenter refers to when generating an option. An example is ‘the idler wheel must be designed according to the size of the cash’, which indicates that the size of cash is the rule that designing of an idler wheel must obey. Design constraints are also rules. Criteria are knowledge the designer used to evaluate the options or solutions, which may belong to different abstract levels. For example, ‘aesthetics and economy’ and ‘the cash can’t be mangled’ are both criteria. Reasons will explain how and why the rules and criteria are applied by the designer in the design thinking process. 3.2

Model of Design Thinking Process

Based on results of design experiment, the design thinking process reflects the interaction of design intents, process knowledge and operations. Design intents specify the next objective of design, propose options for resolving problems and confirm the ultimate solutions for the design. Knowledge in design thinking process contributes the prerequisite conditions for design intents and operations. Operations achieve the solutions by several actions which make up of operation set. The model of the design thinking process is shown in Figure 1.

Figure 1. Design thinking process model

The basic design thinking process model consist of design intents, design process knowledge and design operations. Design intents include meta-intents, options and solutions. Design process knowledge is composed of rules, criteria and reasons. The definitions of these concepts are listed as follows (the character in the parenthesis is the code of the corresponding concept).

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Design intent (I) expresses all the mental activities of a designer when he/she is making efforts to solve a design task or problem. Design intent is composed of meta-intent, option and solution. Meta-intent (mI) refers to the goal that the designer wants to achieve at some stage of the design process. It represents the motivation of the designer’s activities. Meta-intent has different categories which will be described in section 3.3. Option (O) is the candidate solutions generated during the process that designer realizes the design intent. Option is always acquired based on some design rules, however, sometimes, Option is acquired from experience or assumption and not supported by explicit and justified evidence, and then it is called a weak option. When the weak option is valued and validated, it turns to a ‘strong’ one and can be used convincingly. Solution (S) is the ultimate decision that the designer makes after analyzing and comparing several options based on some criteria. Knowledge (K) is all the knowledge the designer refers to during the design thinking process, which includes rules, criteria and reasons. Rule (R) is the basis on which the designer depends to propose the options to achieve the design intent. Design rule has different categories and abstraction levels. It may be a physical principle, condition or constraint in the design requirement, and even a formula in the design handbook. Specially, design rule can be the assumptions of a designer according to the expertise and experience. Of course, the options proposed based on the assumption are weak options and must be validated subsequently and become strong ones as mentioned above. Criteria (Cr) are the standards that the designer refers to when he/she chooses a solution from the options. Just like the design rules, criteria have different categories and abstraction levels. They may be either abstract concepts such as aesthetics and economy, or concrete parameters requirements. Reason (Re) is provided by the designer to describe the causal relationship among different design states. For example, it can be why or how the options are derived according to the design rules. It can express the mapping relationship between the designer’s internal mental factors and the external objective environment. Just like the design rule, reason can be common sense or experience of designers. Operation (Op) is the action whose execution should result in the realization of the design intent in the design process, e.g., using a CAD system software to generate solid models of the products, searching for similar solutions or communication with other designers. Sometimes a series of operations are needed to realize the design intent. The collection of all the operations the designer performs during a period is called Operation Set. Operation expresses the interaction between the design intent and the external environment. Operation can be absent, which means that the corresponding design intent is unable to be or has not yet been achieved. 3.3

Categories of Design Intents

The meta-intents of design intents in the design thinking process model are classified into six categories.

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Objective Intent (OI) decides what to do next, which introduces another intent. As the design process proceeds, design intent is changed from one to another until the design requirements and constraints are satisfied. Generation Intent (GI) introduces a design operation to generate an option or solution for the current task. The option and solution generated can be at different abstract level, e.g., a physical principle or an artifact structure. Synthesis Intent (SI) introduces a design operation to combine the design options or solutions to obtain a complex design option or solution. Evaluation Intent (EI) introduces a design operation to evaluate the current option or solution itself, or to compare different design options for a solution. Planning Intent (PI) is the intent to plan a solution in an appropriate order. Communication Intent (CI) is the intent to exchange design methods or design results with the external environment or other cooperative partners. 3.4

Segments of Design Thinking Process

The design process is not only driven by different design intents, but also impelled by different design operations. Operations in the design thinking process model can be divided into three classes. The first one is the mental operation, which is a mental activity of the designer. The second is the actual operation, which is the real action that the designer executes. For example, selecting a parameter or solving a set of equations is one actual operation. The third class of design operations is either the mental or the actual operation. For example, optimization can be the idea of the designer and also can be the specific structural or shape optimization operation using a CAE tool. Pairs of design intents and design operations constitute the design thinking process. The pair of a design intent and a design operation is defined as a design thinking process segment. According to the categories of design intents and design operations, eight types of the design thinking process segments are considered. Intent to Intent (Focusing segment): This segment figures the reification of design intent, i.e., the extended design thinking. It induces new objectives or intents. For example, when there are several options to be analyzed, it deals with which option should be taken firstly. Intent to Option (Analysis segment): This segment generates options for the current intent by analyzing, decomposing and comparing similar intents. For instance, in the design experiment, the experimenter proposed ‘The cash can be transferred by a strap, or an idler wheel, or an machine that is used to transfer newspapers in the printing shop, which shows the intent of “cash transferring” can be achieved by three options such as a strap, or an idler wheel or an transfer machine in the printing shop. Intent to Solution (Generation segment): This segment generates solutions directly without considering any options, which always happens in the routine design following a fixed procedure. It also can be found in the design process of novices who have less experience and potential ideas than the experts. Intent to Operation (Communication segment): This segment reflects the communication between the designer and the external design environment. It can

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be either the sharing or exchange of design intents with the other designers or the documentation of the design thinking process. Option to Option (Option evaluation segment): This is the evaluation or optimization of the options. As the design proceeds, new conditions and constraints will be activated or discovered, so the proposed options must be regulated to satisfy the newly appearing constraints. Option to Solution (Synthesis segment): The solution of the design task is determined in this segment by selecting one option from the candidates or synthesizing several or all the options. This segment focuses on the evaluation and comparison of the options based on an amount of related information. For example, when the designer decides to use a pair of gears rather than a pair of worm and worm wheel to transfer power, information about gear design and worm-wheel design is needed. Solution to Solution (Solution evaluation segment): By comparing solutions to the design criteria, the solutions in this segment are evaluated and optimized. The final solution is determined. Solution to Option (Planning segment): That a solution is decided does not mean the design work is finished. There may be several plans to achieve the solution, so this segment is needed for generating the plan options for the solution. Table 1. BNF notation of design thinking process structure and model Elements of design thinking process ::= <Meta-Intent>|<Meta-Intent>