About the Book
American industry is becoming more aware of the importance of applying statistical methods to improve its competitive edge in the world market. Examples of real industrial applications can serve as a major motivator for industries that want to increase their use of statistical methods.
This book contains a broad selection of case studies written by professionals in the semiconductor industry that illustrate the use of statistical methods to improve manufacturing processes. These case studies offer engineers, scientists, technicians, and managers numerous examples of best-in-class practices by their peers. Because of the universal nature of statistical applications, the methods described here can be applied to a wide range of industries, including the chemical, biotechnology, automotive, steel, plastics, textile, and food industries. Many industries already benefit from the use of statistical methods, although the semiconductor industry is considered both a leader in and a model for the wide application and effective use of statistics.
Specific case studies address the following statistical methods: gauge studies, passive data collection (sources of variation studies), design of experiments, statistical process control, and equipment reliability.
Readers familiar with the statistical methodologies that comprise the Six Sigma® tool box will find a wealth of applications. Czitrom has written an introduction to each statistical method, which, along with a glossary, gives basic definitions of frequently occurring statistical terms and suggestions for further reading. The case studies, which can be used in industrial training as well as in academia, are an extremely useful classroom supplement and will remain a rich source of used and useful approaches to real industrial problems for years to come.
Table of Contents:
Foreword
Preface
Acknowledgments
Introduction
Facts About SEMATECH
SEMATECH Qualification Plan, Veronica Czitrom and Karen Horrell
Part One: GAUGE STUDIES. Chapter 1: Introduction to Gauge Studies, Veronica Czitrom
Chapter 2: Prometrix RS35e Gauge Study in Five Two-Level Factors and One Three-Level Factor, James Buckner, Barry Chin, and Jon Henri
Chapter 3: Calibration of an FTIR Spectrometer for Measuring Carbon, Peter C. Pankratz
Chapter 4: Revelation of a Microbalance Warm-Up Effect, James Buckner, Barry Chin, Todd Green, and Jon Henri
Chapter 5: GRR Methodology for Destructive Testing and Quantitative Assessment of Gauge Capability For One-Side Specifications, Teresa Mitchell, Victor Hegemann, and K. C. Liu
Part Two: PASSIVE DATA COLLECTION. Chapter 6: Introduction to Passive Data Collection, Veronica Czitrom
Chapter 7: Understanding the Nature of Variability in a Dry Etch Process, Richard O. Lynch and Richard J. Markle
Chapter 8: Virgin Versus Recycled Wafers for Furnace Qualification: Is the Expense Justified?, Veronica Czitrom and Jack E. Reece
Chapter 9: Identifying Sources of Variation in a Wafer Planarization Process, Arnon M. Hurwitz and Patrick D. Spagon
Chapter 10: Factors Which Affect the Number of Aerosol Particles Released by Clean Room Operators, William Kahn and Carole Baczkowski
Chapter 11: A Skip-Lot Sampling Plan Based on Variance Components for Photolithographic Registration Measurements, Dwayne Pepper
Chapter 12: Sampling to Meet a Variance Specification: Clean Room Qualification, Kathryn Hall and Steven Carpenter
Chapter 13: Snapshot: A Plot Showing Progress Through a Device Development Laboratory, Diane Lambert, James M. Landwehr, and Ming-Jen Shyu
Part Three: DESIGN OF EXPERIMENTS. Chapter 14: Introduction To Design Of Experiments, Veronica Czitrom
Chapter 15: Elimination of TiN Peeling During Exposure to CVD Tungsten Deposition Process Using Designed Experiments
James Buckner, David J. Cammenga, and Ann Weber
Chapter 16: Modeling a Uniformity Bulls-Eye Inversion, James Buckner, Richard Huang, Kenneth A. Monnig, Eliot K. Broadbent, Barry Chin, Jon Henri, Mark Sorell, and Kevin Venor
Chapter 17: Using Fewer Wafers to Resolve Confounding in Screening Experiments, Joel Barnett, Veronica Czitrom, Peter W. M. John, and Ramón V. León
Chapter 18: Planarization by Chemical Mechanical Polishing: A Rate and Uniformity Study, Anne E. Freeny and Warren Y.-C. Lai
Chapter 19: Use of Experimental Design to Optimize a Process for Etching Polycrystalline Silicon Gates, Fred Preuninger, Joseph Blasko, Steven Meester, and Taeho Kook
Chapter 20: Optimization of a Wafer Stepper Alignment System Using Robust Design, Brenda Cantell, José Ramírez, and William Gadson
Part Four: STATISTICAL PROCESS CONTROL. Chapter 21: Introduction to Statistical Process Control, Veronica Czitrom
Chapter 22: Removing Drift Effects When Calculating Control Limits, Ray L. Marr
Chapter 23: Implementation of a Statistical Process Control Capability Strategy in the Manufacture of Raw Printed Circuit Boards for Surface Mount Technology, Ricky M. Watson
Chapter 24: Obtaining and Using Statistical Process Control Limits in the Semiconductor Industry, Madhukar Joshi and Kimberley Sprague
Part Five: EQUIPMENT RELIABILITY. Chapter 25: Introduction to Equipment Reliability, Veronica Czitrom
Chapter 26: Marathon Report for a Photolithography Exposure Tool, John T. Canning and Kent G. Green
Chapter 27: Experimentation for Equipment Reliability Improvement, Donald K. Lewis, Craig Hutchens, and Joseph M. Smith
Chapter 28: How to Determine Component-Based Preventive Maintenance Plans, Stephen V. Crowder
Part Six: COMPREHENSIVE CASE STUDY. Chapter 29: Introduction to Comprehensive Case Study, Veronica Czitrom
Chapter 30: Characterization of a Vertical Furnace Chemical Vapor Deposition (CVD) Silicon Nitride Process, Jack E. Reece and Mohsen Shenasa
Part Seven: APPENDICES. Appendix: Introduction to Integrated Circuit Manufacture
Review :
'A wonderful collection of superbly documented industrial statistical experiences ... This book will inspire experienced researchers. Beginners, in addition, will learn a good deal about statistical techniques for industrial problem solving.' Lloyd S. Nelson, Journal of Quality Technology ' ... A good investment for those who are directly involved in the study or application of statistical methods.' George G. R. Maharage, Manufacturing Engineer
