Design for Six Sigma ABOUT THE AUTHORS Kai Yang, Ph., is Professor of Industrial and Manufacturing Engineering at Wayne State University. He is also a consultant with extensive experience in all aspects of Design for Six Sigma, Six Sigma and Lean, Lean Healthcare, and quality and reliability engineering. Yang is the author of Multivariate Statistical Methods for Quality Management, Design for Six Sigma for Service, and Voice of the Customer Capturing and Analysis. El-Haik, Ph.
and Doctorate in Manufacturing Engineering, is the CEO and President of Six Sigma Professionals, Inc., in Canton, Michigan, United States, and an author of many bestseller books on the subject of Design For Six Sigma and Six Sigma. His wealth of experience encompasses 20 years in contemporary design and quality engineering methods. Throughout his career Dr. El-Haik has trained, certified, coached, and mentored over 600 belts (green belts, black belts, and master black belts) in DFSS and Six Sigma in both tracks: product and service (transactional).
Copyright © 2009, 2003 by The McGraw-Hill Companies, Inc. Click here for terms of use. Design for Six Sigma A Roadmap for Product Development Kai Yang Basem S. El-Haik Second Edition New York Chicago San Francisco Lisbon London Madrid Mexico City Milan New Delhi San Juan Seoul Singapore Sydney Toronto Copyright © 2009, 2003 by The McGraw-Hill Companies, Inc.
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This limitation of liability shall apply to any claim or cause whatsoever whether such claim or cause arises in contract, tort or otherwise.1036/0071547673 Professional Want to learn more? We hope you enjoy this McGraw-Hill eBook! If you’d like more information about this book, its author, or related books and websites, please click here. To our parents, families, and friends for their continuous support This page intentionally left blank For more information about this title, click here Contents Preface xiii Preface to the First Edition xv Chapter 1.1 What Is Quality? 1 1.2 Quality Assurance and Product/Service Life Cycle 3 1.3 Development of Quality Methods 8 1.4 Business Excellence, Whole Quality, and Other Metrics in Business Operations 17 1. Six Sigma and Lean Fundamentals 21 2.1 What Is Six Sigma? 21 2.2 Process: The Basic Unit for the Six Sigma Improvement Project 22 2.3 Process Capability and Six Sigma 28 2.4 Overview of Six Sigma Process Improvement 34 2.5 Lean Operation Principles 39 2.6 Process Mapping, Value Stream Mapping, and Process Management 45 2.7 Six Sigma Goes Upstream: Design for Six Sigma (DFSS) 54 2. Product Development Process and Design for Six Sigma 57 3.2 More on the Product Development Process 59 3.3 Lean Principles in Product Development 71 3.4 Lean Product Development Approaches 74 3.5 What Is Design for Six Sigma? 86 3.6 Why “Design for Six Sigma”? 89 3.7 Design for Six Sigma (DFSS) Phases 91 3.8 More on Design Process and Design Vulnerabilities 95 3.9 Differences between Six Sigma and DFSS 97 3.10 What Kinds of Problems Can Be Solved by DFSS? 99 3.11 Design for a Six Sigma (DFSS) Company 101 vii viii Contents 3.12 Features of a Sound DFSS Strategy 101 Appendix: Historical Development in Design 103 Chapter 4.
Design for Six Sigma Deployment 107 4.2 Black Belt–DFSS Team: Cultural Change 107 4.3 DFSS Deployment Prerequisites 110 4.4 DFSS Deployment Strategy 112 4.5 DFSS Deployment Strategy Goals 115 4.6 Six Sigma Project Financial Management 122 4.8 Elements Critical to Sustain DFSS Deployment 123 4.9 DFSS Sustainability Factors 124 Chapter 5. Design for Six Sigma Project Algorithm 129 5.2 Form a Synergistic Design Team (DFSS Algorithm Step 1) 132 5.3 Determine Customer Expectations (DFSS Algorithm Step 2) 133 5.4 Understand Functional Requirements Evolution (DFSS Algorithm Step 3) 147 5.6 Select the Best Concept (DFSS Algorithm Step 5) 152 5.7 Finalize the Physical Structure of the Selected Concept (DFSS Algorithm Step 6) 153 5.8 Initiate Design Scorecards and Transfer Function Development (DFSS Algorithm Step 7) 157 5.9 Assess Risk Using DFMEA/PFMEA (DFSS Algorithm Step 8) 159 5.10 Transfer Function Optimization (DFSS Algorithm Step 9) 167 5.12 Tolerance Design and Tolerancing (DFSS Algorithm Step 11) 176 5.13 Pilot and Prototyping Design (DFSS Algorithm Step 12) 178 5.15 Launch Mass Production (DFSS Algorithm Step 14) 180 5.16 Project Risk Management 181 5.17 Other DFSS Roadmaps 183 Chapter 6. DFSS Transfer Function and Scorecards 185 6.3 DFSS Design Synthesis 186 6.4 Design Scorecards and Transfer Function Development 195 Chapter 7. Quality Function Deployment (QFD) 213 7.2 History of QFD 215 7.3 QFD Benefits, Assumptions, and Realities 215 7.4 QFD Methodology Overview 216 7.5 Kano Model of Quality 224 Contents ix 7.6 The Four Phases of QFD 225 7.2 Why Axiomatic Design Is Needed 238 8.4 The Independence Axiom (Axiom 1) 240 8.6 The Implications of Axiom 2 262 8.7 Case Study: Axiomatic Design of the Water Faucet 269 8.8 Summary 272 Appendix 8A: Axiomatic Design Theorems and Corollaries 273 Appendix 8B: Historical Development of Axiomatic Design 278 Chapter 9.
Theory of Inventive Problem Solving (TRIZ) 281 9.3 TRIZ Problem-Solving Process 295 9.4 Physical Contradiction Resolution/Separation Principles 298 9.5 Technical Contradiction Elimination—Inventive Principles 307 9.6 Functional Improvement Methods/TRIZ Standard Solutions 314 9.7 Complexity Reduction/Trimming 330 9.8 S-Curve Analysis of Technical Systems 331 9.9 Evolution of Technological Systems 333 9.10 Physical, Chemical, and Geometric Effects Database 339 9.11 Comparison of Axiomatic Design and TRIZ 339 Appendix: Contradiction Table of Inventive Principles 347 Chapter 10.2 Design for Manufacture and Assembly (DFMA) 356 10.3 Design for Reliability (DFR) 365 10.4 Design for Maintainability 367 10.5 Design for Serviceability 368 10.6 Design for Environmentality 378 10.7 Design for Life-Cycle Cost (LCC): Activity-Based Costing with Uncertainty 380 10. Failure Mode–Effect Analysis 387 11.5 Quality Systems and Control Plans 410 x Contents Chapter 12. Fundamentals of Experimental Design 413 12.1 Introduction to Design of Experiments (DOE) 413 12.3 Two-Level Full Factorial Designs 426 12.4 Fractional Two-Level Factorial Design 437 12.5 Three-Level Full Factorial Design 446 12.6 Incomplete Factorial Experiments 450 12. Taguchi’s Orthogonal Array Experiment 469 13.1 Taguchi’s Orthogonal Arrays 469 13.2 Taguchi Experimental Design 472 13.4 Taguchi Experiment Data Analysis 483 13.5 Summary 491 Appendix: Selected Orthogonal Arrays 491 Chapter 14.
Design Optimization: Taguchi’s Robust Parameter Design 499 14.2 Loss Function and Parameter Design 500 14.3 Loss Function and Signal-to-Noise Ratio 508 14.4 Noise Factors and Inner-Outer Arrays 516 14.5 Parameter Design for Smaller-the-Better Characteristics 521 14.6 Parameter Design for Nominal-the-Best Characteristics 525 14.7 Parameter Design for Larger-the-Better Characteristics 528 Chapter 15. Design Optimization: Advanced Taguchi Robust Parameter Design 533 15.2 Design Synthesis and Technical Systems 535 15.3 Parameter Design for Dynamic Characteristics 546 15.4 Functional Quality and Dynamic S/N Ratio 565 15.5 Robust Technology Development 568 Chapter 16.2 Worst-Case Tolerance 576 16.4 Cost-Based Optimal Tolerance 587 16.5 Taguchi’s Loss Function and Safety Tolerance Design 592 16.6 Taguchi’s Tolerance Design Experiment 599 16.7 Computer-Aided Robust Parameter and Tolerance Design 602 Chapter 17. Response Surface Methodology 611 17.2 Search and Identify the Region That Contains the Optimal Solution 615 17.3 Response Surface Experimental Designs 622 17.4 Response Surface Experimental Data Analysis for Single Response 628 Contents xi 17.5 Response Surface Experimental Data Analysis for Multiple Responses 632 17.6 Mixture Experiments 642 Chapter 18.2 Design Analysis and Testing 670 18.4 Process and Production Validation 689 18.5 DFSS Validation and Measurement 697 Appendix: Glossary of Terms 702 Acronyms 705 References 709 Index 717 This page intentionally left blank Preface We are extremely pleased by the overwhelming reception of the first edi- tion of this book by readers all over the world. In this second edition, we have kept all the good materials of the first edition, and we added a sub- stantial amount of new material based on the trend in the Lean Six Sigma movement and many readers’ feedback.
The following is a sum- mary of what is added in the second edition. The principles of lean operation are added and covered in great detail, and we also describe how the lean operation principles can be inte- grated with Six Sigma to form an effective Lean Six Sigma approach. All these additions are in Chapter 2 of the second edition. Design for Six Sigma (DFSS) is an effective approach to improve prod- uct value and quality in the design stage.
Complementary to DFSS, lean product development is an emerging and effective system to improve product development efficiency and effectiveness, and to decrease prod- uct development lead time. This approach has been proved by many good practices such as those of Toyota. We believe that DFSS and lean product development should be carried out simultaneously in the prod- uct development process. In the second edition, the principles and prac- tices of lean product development are covered in detail, and these materials can be found in Chapter 3.
In Design for Six Sigma practice, there are several alternative DFSS project roadmaps that are widely applied, such as IDOV (identify, design, optimize, verify), and DMADV (define, measure, analyze, design, verify). We covered these DFSS roadmaps in the second edition. This material is found in Chapter 5. Axiomatic design is an important tool in DFSS.
In the second edition we added a new practical case study and more theorems and corol- laries of the axiomatic design.