Quality engineering using robust design / Madhav S. Phadke.

By: Phadke, Madhav Shridhar, 1948-.

Material type: materialTypeLabel

BookPublisher: Englewood Cliffs, N.J. : Prentice-Hall, 1989Description: xviii, 334 p. ; 24 cm. + hbk.ISBN: 0137451679.Subject(s): UNIX (Computer file) | Engineering design

| Computer-aided design

| Integrated circuits -- Very large scale integration

DDC classification: 620.00420285

Contents:

Introduction -- Principles of quality engineering -- Matrix experiments using orthogonal arrays -- Steps in robust design -- Signal-to-noise ratios -- Achieving additivity -- Constructing orthogonal arrays -- Computer aided robust design -- Design of dynamic systems -- Tuning computer systems for high performance -- Reliability improvement.

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode	Item holds
General Lending	MTU Bishopstown Library Lending	620.00420285 (Browse shelf(Opens below))	1	Available		00080869

Total holds: 0

Enhanced descriptions from Syndetics:

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.

Bibliography; p. 321-325. - Includes index.

Table of contents provided by Syndetics

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)