Quality engineering using robust design

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Title:

Personal Author:

Phadke, Madhav S.

Publication Information:

New Jersey : Prentice Hall, 1989

ISBN:

9780137451678

Subject Term:

Engineering design

Computer-aided design

UNIX (Computer operating system)

Integrated circuits -- Very large scale integration

Available:*

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ KL	30000005035294	TA174 P42 1989	Open Access Book	Book	Searching... Unknown

Phadke was trained in robust design techniques by Genichi Taguchi, the mastermind behind Japanese quality manufacturing technologies and the father of Japanese quality control. Taguchi's approach is currently under consideration to be adopted as a student protocol with the US govrnment. The foreword is written by Taguchi. This book offers a complete blueprint for structuring projects to achieve rapid completion with high engineering productivity during the research and development phase to ensure that high quality products can be made quickly and at the lowest possible cost. Some topics covered are: orthogonol arrays, how to construct orthogonal arrays, computer-aided robutst design techniques, dynamic systems design methods, and more.

Foreword	p. xiii
Preface	p. xv
Acknowledgments	p. xvii
Chapter 1 Introduction	p. 1
1.1 A Historical Perspective	p. 2
1.2 What Is Quality?	p. 3
1.3 Elements of Cost	p. 4
1.4 Fundamental Principle	p. 5
1.5 Tools Used in Robust Design	p. 6
1.6 Applications and Benefits of Robust Design	p. 8
1.7 Organization of the Book	p. 10
1.8 Summary	p. 10
Chapter 2 Principles of Quality Engineering	p. 13
2.1 Quality Loss Function--The Fraction Defective Fallacy	p. 14
2.2 Quadratic Loss Function	p. 18
2.3 Noise Factors--Causes of Variation	p. 23
2.4 Average Quality Loss	p. 25
2.5 Exploiting Nonlinearity	p. 27
2.6 Classification of Parameters: P Diagram	p. 30
2.7 Optimization of Product and Process Design	p. 32
2.8 Role of Various Quality Control Activities	p. 35
2.9 Summary	p. 38
Chapter 3 Matrix Experiments Using Orthogonal Arrays	p. 41
3.1 Matrix Experiment for a CVD Process	p. 42
3.2 Estimation of Factor Effects	p. 44
3.3 Additive Model for Factor Effects	p. 48
3.4 Analysis of Variance	p. 51
3.5 Prediction and Diagnosis	p. 59
3.6 Summary	p. 63
Chapter 4 Steps in Robust Design	p. 67
4.1 The Polysilicon Deposition Process and Its Main Function	p. 68
4.2 Noise Factors and Testing Conditions	p. 71
4.3 Quality Characteristics and Objective Functions	p. 72
4.4 Control Factors and Their Levels	p. 74
4.5 Matrix Experiment and Data Analysis Plan	p. 76
4.6 Conducting the Matrix Experiment	p. 79
4.7 Data Analysis	p. 80
4.8 Verification Experiment and Future Plan	p. 90
4.9 Summary	p. 93
Chapter 5 Signal-To-Noise Ratios	p. 97
5.1 Optimization for Polysilicon Layer Thickness Uniformity	p. 98
5.2 Evaluation of Sensitivity to Noise	p. 105
5.3 S/N Ratios for Static Problems	p. 108
5.4 S/N Ratios for Dynamic Problems	p. 114
5.5 Analysis of Ordered Categorical Data	p. 121
5.6 Summary	p. 128
Chapter 6 Achieving Additivity	p. 133
6.1 Guidelines for Selecting Quality Characteristics	p. 135
6.2 Examples of Quality Characteristics	p. 136
6.3 Examples of S/N Ratios	p. 138
6.4 Selection of Control Factors	p. 144
6.5 Role of Orthogonal Arrays	p. 146
6.6 Summary	p. 146
Chapter 7 Constructing Orthogonal Arrays	p. 149
7.1 Counting Degrees of Freedom	p. 150
7.2 Selecting a Standard Orthogonal Array	p. 151
7.3 Dummy Level Technique	p. 154
7.4 Compound Factor Method	p. 156
7.5 Linear Graphs and Interaction Assignment	p. 157
7.6 Modification of Linear Graphs	p. 163
7.7 Column Merging Method	p. 166
7.8 Branching Design	p. 168
7.9 Strategy for Constructing an Orthogonal Array	p. 171
7.10 Comparison with the Classical Statistical Experiment Design	p. 174
7.11 Summary	p. 181
Chapter 8 Computer Aided Robust Design	p. 183
8.1 Differential Op-Amp Circuit	p. 184
8.2 Description of Noise Factors	p. 186
8.3 Methods of Simulating the Variation in Noise Factors	p. 189
8.4 Orthogonal Array Based Simulation of Variation in Noise Factors	p. 190
8.5 Quality Characteristic and S/N Ratio	p. 194
8.6 Optimization of the Design	p. 194
8.7 Tolerance Design	p. 202
8.8 Reducing the Simulation Effort	p. 205
8.9 Analysis of Nonlinearity	p. 207
8.10 Selecting an Appropriate S/N Ratio	p. 208
8.11 Summary	p. 209
Chapter 9 Design of Dynamic systems	p. 213
9.1 Temperature Control Circuit and Its Function	p. 214
9.2 Signal, Control, and Noise Factors	p. 217
9.3 Quality Characteristics and S/N Ratios	p. 218
9.4 Optimization of the Design	p. 222
9.5 Iterative Optimization	p. 227
9.6 Summary	p. 228
Chapter 10 Tuning Computer Systems for High Performance	p. 231
10.1 Problem Formulation	p. 232
10.2 Noise Factors and Testing Conditions	p. 234
10.3 Quality Characteristic and S/N Ratio	p. 235
10.4 Control Factors and Their Alternate Levels	p. 236
10.5 Design of the Matrix Experiment and the Experimental Procedure	p. 238
10.6 Data Analysis and Verification Experiments	p. 240
10.7 Standardized S/N Ratio	p. 246
10.8 Related Applications	p. 249
10.9 Summary	p. 249
Chapter 11 Reliability Improvement	p. 253
11.1 Role of S/N Ratios in Reliability Improvement	p. 254
11.2 The Routing Process	p. 256
11.3 Noise Factors and Quality Characteristics	p. 256
11.4 Control Factors and Their Levels	p. 257
11.5 Design of the Matrix Experiment	p. 258
11.6 Experimental Procedure	p. 265
11.7 Data Analysis	p. 265
11.8 Survival Probability Curves	p. 271
11.9 Summary	p. 275
Appendix A Orthogonality of a Matrix Experiment	p. 277
Appendix B Unconstrained Optimization	p. 281
Appendix C Standard Orthogonal Arrays and Linear Graphs	p. 285
References	p. 321
Index	p. 327

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