Statistical Quality Control: A Modern Introduction

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Covering everything from basic principles to state-of-the-art concepts and applications, this book armsreaders with a comprehensive understanding of modern statistical methods for quality control and improvement. The author covers basic and advanced methods of statistical process control (SPC), show how statistically designed experiments can be used for process design, development and improvement, and explore acceptance sampling. Throughout the pages, guidelines are provided for selecting the correct statistical technique to use in a variety of situations.

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Dr. Douglas C. Montgomery Professor of Engineering and Statistics at Arizona State University, received his B.S., M.S., and Ph.D. degrees from Virginia Polytechnic Institute, all in engineering. Dr. Montgomery has research and teaching interests in industrial statistics including statistical quality control techniques, design of experiments, regression analysis and empirical model building, and the application of operations research methodology to problems in manufacturing systems. He is a Stewart Medallist of the American Society for Quality, and has also received the Brumbaugh Award, the William G. Hunter Award, and the Shewell Award(twice) from the ASQ. He is a recipient of the Ellis R. Ott Award. He is a former editor of the Journal of Quality Technology, the current editor of Quality and Reliability Engineering International, and serves on the editorial boards of several journals. 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 Appendix