Covering everything from basic principles to state-of-the-art concepts and applications, this book arms readers 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. About The Author: 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 Attribute