Fundamentals of Semiconductor Manufacturing and Process Control (eBook)

GARY S. MAY, PhD, is Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. Dr. May is a Fellow of the IEEE and Senior Member of the Society of Manufacturing Engineers. He has published more than 150 articles and given over 100 technical presentations in the area of IC computer-aided manufacturing. COSTAS J. SPANOS, PhD, is Professor in the Department of Electrical Engineering and Computer Sciences and the Associate Dean for Research for the College of Engineering at the University of California, Berkeley. Dr. Spanos is a Fellow of the IEEE and has published extensively in the area of semiconductor manufacturing.

Preface.

Acknowledgments.

1. Introduction to Semiconductor Manufacturing.

Objectives.

Introduction.

1.1. Historical Evolution.

1.2. Modern Semiconductor Manufacturing.

1.3. Goals of Manufacturing.

1.4. Manufacturing Systems.

1.5. Outline for Remainder of the Book.

Summary.

Problems.

References.

2. Technology Overview.

Objectives.

Introduction.

2.1. Unit Processes.

2.2. Process Integration.

Summary.

Problems.

References.

3. Process Monitoring.

Objectives.

Introduction.

3.1. Process Flow and Key Measurement Points.

3.2. Wafer State Measurements.

3.3. Equipment State Measurements.

Summary.

Problems.

References.

4. Statistical Fundamentals.

Objectives.

Introduction.

4.1. Probability Distributions.

4.2. Sampling from a Normal Distribution.

4.3. Estimation

4.4. Hypothesis Testing.

Summary.

Problems.

Reference.

5. Yield Modeling.

Objectives.

Introduction.

5.1. Definitions of Yield Components.

5.2. Functional Yield Models.

5.3. Functional Yield Model Components.

5.4. Parametric Yield.

5.5. Yield Simulation.

5.6. Design Centering.

5.7. Process Introduction and Time-to-Yield.

Summary.

Problems.

References.

6. Statistical Process Control.

Objectives.

Introduction.

6.1. Control Chart Basics.

6.2. Patterns in Control Charts.

6.3. Control Charts for Attributes.

6.4. Control Charts for Variables.

6.5. Multivariate Control.

6.6. SPC with Correlated Process Data.

Summary.

Problems.

References.

7. Statistical Experimental Design.

Objectives.

Introduction.

7.1. Comparing Distributions.

7.2. Analysis of Variance.

7.3. Factorial Designs.

7.4. Taguchi Method.

Summary.

Problems.

References.

8. Process Modeling.

Objectives.

Introduction.

8.1. Regression Modeling.

8.2. Response Surface Methods.

8.3. Evolutionary Operation.

8.4. Principal-Component Analysis.

8.5. Intelligent Modeling Techniques.

8.6. Process Optimization.

Summary.

Problems.

References.

9. Advanced Process Control.

Objectives.

Introduction.

9.1. Run-by-Run Control with Constant Term Adaptation.

9.2. Multivariate Control with Complete Model Adaptation.

9.3. Supervisory Control.

Summary.

Problems.

References.

10. Process and Equipment Diagnosis.

Objectives.

Introduction.

10.1. Algorithmic Methods.

10.2. Expert Systems.

10.3. Neural Network Approaches.

10.4. Hybrid Methods.

Summary.

Problems.

References.

Appendix A: Some Properties of the Error Function.

Appendix B: Cumulative Standard Normal Distribution.

Appendix C: Percentage Points of the chi2
Distribution.

Appendix D: Percentage Points of the t
Distribution.

Appendix E: Percentage Points of the F
Distribution.

Appendix F: Factors for Constructing Variables Control
Charts.

Index.

"...offers insight into the IC manufacturing process...[to] the practicing engineer or interested professional." (IEEE Circuits & Devices Magazine, November/December 2006)