Preface

Chapter 1. Quality Concepts

1.1 What Is Quality?

1.2 Quality Assurance and Product/Service Life Cycle

1.3 Development of Quality Methods

1.4 Business Excellence, Whole Quality, and Other Metrics in Business Operations

1.5 Summary

Chapter 2. Six Sigma Fundamentals

2.1 What Is Six Sigma?

2.2 Process : The Basic Unit for the Six Sigma Improvement Project

2.3 Process Mapping, Value Stream Mapping, and Process Management

2.4 Process Capability and Six Sigma

2.5 Overview of Six Sigma Process Improvement

2.6 Six Sigma Goes Upstream: Design for Six Sigma (DFSS)

2.7 Summary

Chapter 3. Design for Six Sigma

3.1 Introduction

3.2 What is Design for Six Sigma Theory?

3.3 Why "Design for Six Sigma?"

3.4 Design for Six Sigma (DFSS) Phases

3.5 More on Design Process and Design Vulnerabilities

3.6 Differences between Six Sigma and DFSS

3.7 What Kinds of Problems Can Be Solved by DFSS?

3.8 Design for a Six Sigma (DFSS) Company

3.9 Features of a Sound DFSS Strategy Appendix: Historical Development in Design

Chapter 4. Design for Six Sigma Deployment

4.1 Introduction

4.2 Black Belt-DFSS Team: Cultural Change

4.3 DFSS Deployment Prerequisites

4.4 DFSS Deployment Strategy

4.5 DFSS Deployment Strategy Goals

4.6 Six Sigma Project Financial Management

4.7 DFSS Training

4.8 Elements Critical to Sustain DFSS Deployment

4.9 DFSS Sustainability Factors

Chapter 5. Design for Six Sigma Project Algorithm

5.1 Introduction

5.2 Form a Synergistic Design Team (DFSS Algorithm Step 1)

5.3 Determine Customer Expectations (DFSS Algorithm Step 2)

5.4 Understand Functional Requirements Evolution {DFSS Algorithm Step 3)

5.5 Generate Concepts (DFSS Algorithm Step 4)

5.6 Select the Best Concept (DFSS Algorithm Step 5)

5.7 Finalize the Physical Structure of the Selected Concept (DFSS Algorithm Step 6)

5.8 Initiate Design Scorecards and Transfer Function Development (DFSS Algorithm Step 7)

5.9 Assess Risk Using DFMEA/PFMEA (DFSS Algorithm Step 8)

5.10 Transfer Function Optimization (DFSS Algorithm Step 9)

5.11 Design for X (DFSS Algorithm Step 10)

5.12 Tolerance Design and Tolerancing (DFSS Algorithm Step 11)

5.13 Pilot and Prototyping Design (DFSS Algorithm Step 12)

5.14 Validate Design (DFSS Algorithm Step 13)

5.15 Launch Mass Production (DFSS Algorithm Step 14)

5.16 Project Risk Management

Chapter 6. DFSS Transfer Function and Scorecards

6.1 Introduction

6.2 Design Analysis

6.3 DFSS Design Synthesis

6.4 Design Scorecards and Transfer Function Development

Chapter 7. Quality Function Deployment (QFD)

7.1 Introduction

7.2 History of QFD

7.3 QFD Benefits, Assumptions and Realities

7.4 QFD Methodology Overview

7.5 Kano Model of Quality

7.6 The Four Phases of QFD

7.7 QFD Analysis

7.8 QFD Example

7.9 Summary

Chapter 8. Axiomatic Design

8.1 Introduction

8.2 Why Axiomatic Design is Needed

8.3 Design Axioms

8.4 The Independence Axiom (Axiom 1)

8.5 Coupling Measures

8.6 The Implication of Axiom 2

8.7 Summary

Appendix: Historical Development of Axiomatic Design

Chapter 9. Theory of Inventive Problem Solving (TRIZ)

9.1 Introduction

9.2 TRIZ Foundations

9.3 TRIZ Problem-Solving Process

9.4 Physical Contradiction Resolution/Separation Principles

9.5 Technical Contradiction Elimination/Inventive Principles

9.6 Functional Improvement Methods/TRIZ Standard Solutions

9.7 Complexity Reduction/Trimming

9.8 Evolution of TechnoEogical Systems

9.9 Physical, Chemical, and Geometric Effects Database

9.10 Comparisons of Axiomatic Design and TRIZ Appendix: Contradiction Table of Inventive Principles

Chapter 10. Design for X

10.1 Introduction

10.2 Design for Manufacture and Assembly (DFMA)

10.3 Design for Reliability (DFR)

10.4 Design for Maintainability

10.5 Design for Serviceability

10.6 Design for Environmentality

10.7 Design for Life-Cycle Cost (LCC): Activity-Based Costing with Uncertainty

10.8 Summary

Chapter 11. Failure Mode-Effect Analysis

11.1 Introduction

11.2 FMEA Fundamentals

11.3 Design FMEA (DFMEA)

11.4 Process FMEA (PFMEA)

11.5 Quality Systems and Control Plans

Chapter 12. Fundamentals of Experimental Design

12.1 Introduction to Design of Experiments (DOE)

12.2 Factorial Experiment

12.3 Two-Level Full Factorial Designs

12.4 Fractional Two-Level Factorial Design

12.5 Three-Level Full Factorial Design

12.6 Summary

Chapter 13. Taguchi's Orthogonal Array Experiment

13.1 Taguchi's Orthogonal Arrays

13.2 Taguchi Experimental Design

13.3 Special Techniques

13.4 Taguchi Experiment Data Analysis

13.5 Summary

Appendix: Selected Orthogonal Arrays

Chapter 14. Design Optimization: Taguchi's Robust Parameter Design

14.1 Introduction

14.2 Loss Function and Parameter Design

14.3 Loss Function and Signal-to-Noise Ratio

14.4 Noise Factors and Inner-Outer Arrays

14.5 Parameter Design for Smaller-the Better Characteristics

14.6 Parameter Design for Nominal-the-Best Characteristics

14.7 Parameter Design for Larger-the-Better Characteristics

Chapter 15. Design Optimization: Advanced Taguchi Robust Parameter Design

15.1 Introduction

15.2 Design Synthesis and Technical Systems

15.3. Parameter Design for Dynamic Characteristics

15.4 Functional Quality and Dynamic S/N Ratio

15.5 Robust Technology Development

Chapter 16. Tolerance Design

16.1 Introduction

16.2 Worst-Case Tolerance

16.3 Statistical Tolerance

16.4 Cost-Based Optimal Tolerance

16.5 Taguchi's Loss Function and Safety Tolerance Design

16.6 Taguchi's Tolerance Design Experiment

Chapter 17. Response Surface Methodology

17.1 Introduction

17.2 Searching and Identifying the Region that Contains the Optimal Solution

17.3 Response Surface Experimental Designs

17.4 Response Surface Experimental Data Analysis for Single Response

17.5 Response Surface Experimental Data Analysis for Multiple Responses

Chapter 18. Design Validation

18.1 Introduction

18.2 Design Analysis and Testing

18.3 Prototypes

18.4 Process and Production Validation

Acronyms

References

Index