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| Foreword | |
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| Preface | |
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| Acknowledgments | |
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| Introduction | |
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| A Historical Perspective | |
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| What Is Quality? | |
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| Elements of Cost | |
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| Fundamental Principle | |
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| Tools Used in Robust Design | |
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| Applications and Benefits of Robust Design | |
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| Organization of the Book | |
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| Summary | |
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| Principles of Quality Engineering | |
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| Quality Loss Function--The Fraction Defective Fallacy | |
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| Quadratic Loss Function | |
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| Noise Factors--Causes of Variation | |
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| Average Quality Loss | |
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| Exploiting Nonlinearity | |
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| Classification of Parameters: P Diagram | |
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| Optimization of Product and Process Design | |
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| Role of Various Quality Control Activities | |
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| Summary | |
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| Matrix Experiments Using Orthogonal Arrays | |
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| Matrix Experiment for a CVD Process | |
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| Estimation of Factor Effects | |
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| Additive Model for Factor Effects | |
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| Analysis of Variance | |
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| Prediction and Diagnosis | |
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| Summary | |
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| Steps in Robust Design | |
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| The Polysilicon Deposition Process and Its Main Function | |
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| Noise Factors and Testing Conditions | |
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| Quality Characteristics and Objective Functions | |
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| Control Factors and Their Levels | |
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| Matrix Experiment and Data Analysis Plan | |
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| Conducting the Matrix Experiment | |
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| Data Analysis | |
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| Verification Experiment and Future Plan | |
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| Summary | |
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| Signal-To-Noise Ratios | |
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| Optimization for Polysilicon Layer Thickness Uniformity | |
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| Evaluation of Sensitivity to Noise | |
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| S/N Ratios for Static Problems | |
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| S/N Ratios for Dynamic Problems | |
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| Analysis of Ordered Categorical Data | |
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| Summary | |
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| Achieving Additivity | |
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| Guidelines for Selecting Quality Characteristics | |
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| Examples of Quality Characteristics | |
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| Examples of S/N Ratios | |
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| Selection of Control Factors | |
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| Role of Orthogonal Arrays | |
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| Summary | |
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| Constructing Orthogonal Arrays | |
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| Counting Degrees of Freedom | |
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| Selecting a Standard Orthogonal Array | |
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| Dummy Level Technique | |
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| Compound Factor Method | |
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| Linear Graphs and Interaction Assignment | |
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| Modification of Linear Graphs | |
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| Column Merging Method | |
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| Branching Design | |
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| Strategy for Constructing an Orthogonal Array | |
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| Comparison with the Classical Statistical Experiment Design | |
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| Summary | |
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| Computer Aided Robust Design | |
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| Differential Op-Amp Circuit | |
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| Description of Noise Factors | |
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| Methods of Simulating the Variation in Noise Factors | |
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| Orthogonal Array Based Simulation of Variation in Noise Factors | |
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| Quality Characteristic and S/N Ratio | |
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| Optimization of the Design | |
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| Tolerance Design | |
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| Reducing the Simulation Effort | |
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| Analysis of Nonlinearity | |
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| Selecting an Appropriate S/N Ratio | |
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| Summary | |
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| Design of Dynamic systems | |
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| Temperature Control Circuit and Its Function | |
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| Signal, Control, and Noise Factors | |
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| Quality Characteristics and S/N Ratios | |
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| Optimization of the Design | |
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| Iterative Optimization | |
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| Summary | |
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| Tuning Computer Systems for High Performance | |
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| Problem Formulation | |
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| Noise Factors and Testing Conditions | |
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| Quality Characteristic and S/N Ratio | |
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| Control Factors and Their Alternate Levels | |
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| Design of the Matrix Experiment and the Experimental Procedure | |
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| Data Analysis and Verification Experiments | |
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| Standardized S/N Ratio | |
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| Related Applications | |
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| Summary | |
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| Reliability Improvement | |
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| Role of S/N Ratios in Reliability Improvement | |
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| The Routing Process | |
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| Noise Factors and Quality Characteristics | |
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| Control Factors and Their Levels | |
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| Design of the Matrix Experiment | |
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| Experimental Procedure | |
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| Data Analysis | |
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| Survival Probability Curves | |
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| Summary | |
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| Orthogonality of a Matrix Experiment | |
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| Unconstrained Optimization | |
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| Standard Orthogonal Arrays and Linear Graphs | |
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| References | |
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| Index | |