1 Introduction. - 1. 1 Design for Quality and Manufacturability. - 1. 2 Notation. - 1. 3 Interpretation of Basic Concepts. - 1. 4 Summary. - 2 Overview of IC Statistical Modeling. - 2. 1 Introduction. - 2. 2 Process Variations. - 2. 3 Environmental Variations. - 2. 4 Statistical Macromodeling. - 2. 5 Summary. - 3 Design of Experiments. - 3. 1 Introduction. - 3. 2 Experiment Analysis. - 3. 3 Orthogonal Arrays. - 3. 4 Main Effect Analysis. - 3. 5 Interaction Analysis. - 3. 6 Taguchi Experiments. - 3. 7 Summary. - 4 Parametric Yield Maximization. - 4. 1 Introduction. - 4. 2 Yield Estimation. - 4. 3 Indirect Yield Improvement. - 4. 4 Direct Yield Optimization Methods. - 4. 5 Generalized and Orthogonal Array-Based Gradient Methods for Discrete Circuits. - 4. 6 Gradient Methods for Integrated Circuits. - 4. 7 Examples. - 4. 8 Summary. - 5 Variability Minimization and Tuning. - 5. 1 Introduction. - 5. 2 Principles of Discrete Circuit Variability Minimization. - 5. 3 Principles of IC Variability Minimization. - 5. 4 Factor Screening. - 5. 5 Taguchi's on-target Design. - 5. 6 Two-Stage Design Strategy. - 5. 7 Example 4: CMOS Delay Circuit. - 5. 8 Example 5: CMOS Clock Driver. - 5. 9 Summary. - 6 Worst-Case Measure Reduction. - 6. 1 Introduction. - 6. 2 The ? Transistor Modeling. - 6. 3 Worst-Case Measure Minimization. - 6. 4 Comments on the ? Model. - 6. 5 Creation of Worst-Case Models From the Statistical Model. - 6. 6 Summary. - 7 Multi-Objective Circuit Optimization. - 7. 1 Introduction. - 7. 2 Multiple-Objective Optimization: An Overview. - 7. 3 Fuzzy Sets. - 7. 4 Multiple-Performance Statistical Optimization. - 7. 5 Multiple-Performance Variability Minimization. - 7. 6 Summary. - References. Language: English