Introduction to Statistical Quality Control, 6th Edition
May 2008, ©2009
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.
- 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.
Emphasis on statistical techniques, as well as a strong engineering and management orientation.
All examples in the book utilize data from real applications.
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