The sixth edition of Introduction to Statistical Quality Control provides a comprehensive treatment of the major aspects of using statistical methodology for quality control and improvement. Both traditional and modern methods are presented, including state-of-the-art techniques for statistical process monitoring and control and statistically designed experiments for process characterization, optimization, and process robustness studies. The sixth edition has been updated to place more focus on DMAIC (define, measure, analyze, improve, and control--the problem-solving strategy of six sigma) including a new chapter on the implementation process. Additionally, the text includes new examples, exercises, problems, and techniques. SQC is best suited for upper-division students in engineering, statistics, business and management science or students in graduate courses.
New to this Edition
- A new chapter (Chapter 2) on the DMAIC project implementation process is added. DMAIC (define, measure, analyze, improve, and control) is the problem solving strategy of six sigma.
- Includes new examples and exercises that illustrate quality improvement activities in service and transactional organizations.
- Experimental design chapters more strongly linked to design for six sigma
- New developments in the area of measurement systems analysis are included.
- The chapters on advanced SPC techniques will be updated as well as the problems in every chapter.
- New examples and exercises that illustrate quality improvement activities in service and transactional organizations.
- Incorporation of the new features in Minitab V15.
- Comprehensive coverage of the subject from basic principles to state-of-the-art applications.
- Emphasis on statistical techniques, as well as a strong engineering and management orientation.
- All examples in the book utilize data from real applications.
Table of Contents
- Part I: Introduction
- Chapter 1: Quality Improvement in the Modern Business Environment
- Chapter 2: The DMAIC Process
- Part II: Statistical Methods Useful in Quality Control and Improvement
- Chapter 3: Modeling Process Quality
- Chapter 4: Inferences about Process Quality
- Part III: Basic Methods of Statistical Process Control and Capability Analysis
- Chapter 5: Methods and Philosophy of Statistical Process Control
- Chapter 6: Control Charts for Variables
- Chapter 7: Control Charts for Attributes
- Chapter 8: Process and Measurement System Capability Analysis
- Part IV: Other Statistical Process-Monitoring and Control Techniques
- Chapter 9: Cumulative Sum and Exponentially Weighted Moving Average Control Charts
- Chapter 10: Other Univariate Statistical Process Monitoring and Control Techniques
- Chapter 11: Multivariate Process Monitoring and Control
- Chapter 12: Engineering Process Control and SPC
- Part V: Process Design and Improvement with Designed Experiments
- Chapter 13: Factorial and Fractional Experiments for Process Design and Improvements
- Chapter 14: Process Optimization and Designed Experiments
- Part VI: Acceptance Sampling
- Chapter 15: Lot-by-Lot Acceptance Sampling for Attributes
- Chapter 16: Other Acceptance Sampling Techniques
Douglas C. Montgomery is Professor of Engineering and Statistics at Arizona State University. He received his B.S., M.S., and Ph.D. degrees from Virginia Polytechnic Institute, all in engineering. The author and coauthor of many technical papers and twelve other books. Dr. Montgomery is a Fellow of the American Society for Quality, the American Statistical Association, the Royal Statistical Society, the Institute of Industrial Engineers, and an Elected member of the International Statistical Institute.