Synopses & Reviews
Expert guidance on modern SQC methods, from the name you trust!Douglas Montgomery's modern iintroduction to SQC prepares you for professional practice with comprehensive coverage of current statistical methods for quality control and improvement. With this text, you'll learn how to apply state-of-the-art techniques for statistical process monitoring and control, design experiments for process characterization and optimization, conduct process robustness studies, and implement quality management techniques such as the six-sigma approach.
Fullu updated and revised, this Fifth Edition features more fully integrated coverage of Minitab, new homework problems, new and more modern examples, and more.
Introduction to Statistical Quality Control, Fifth Edition:
- Provides guidelines throughout the book for selecting the proper type of statistical technique to use in a wide variety of product and non-product situations.
- Presents comprehensive coverage—ranging from basic principles to state-of-the-art applications.
- Provides clear and relevant examples, including new examples that illustrate applications of statistical quality improvement techniques in non-manufacturing settings. many examples and exercises are based on real data.
- Reflects contempory practice and provides more information on management aspects of quality improvement.
- Emphasizes statistical techniques in the context of a strong engineering and management orientation.
- Includes electronic versions of all data sets in the text, supplemental text material, and all instructor resources on the Montgomery SQC website www.wiley.com/college/montgomery.
Synopsis
This book is about the use of modern statistical methods for quality control and improvement. It provides comprehensive coverage of the subject from basic principles to state-of-art concepts and applications. The objective is to give the reader a sound understanding of the principles and the basis for applying them in a variety of both product and nonproduct situations. While statistical techniques are emphasized throughout, the book has a strong engineering and management orientation. Guidelines are given throughout the book for selecting the proper type of statistical technique to use in a wide variety of product and nonproduct situations. By presenting theory, and supporting the theory with clear and relevant examples, Montgomery helps the reader to understand the big picture of important concepts. Updated to reflect contemporary practice and provide more information on management aspects of quality improvement.
Synopsis
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 authors cover 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.
Synopsis
The trusted guide to the statistical methods for quality control and improvement.Quality control and improvement is more than an engineering concern. Quality has become a major business strategy for increasing productivity and gaining competitive advantage. Introduction to Statistical Quality Control,Sixth Editiongives you a sound understanding of the principles of statistical quality control (SQC) and how to apply them in a variety of situations for quality control and improvement.
With this text, you'll learn how to apply state-of-the-art techniques for statistical process monitoring and control, designing experiments for process characterization and optimization, conduct process robustness studies, and implement quality management techniques.
You’ll appreciate the significant updates in the Sixth Edition including:
- In-depth attention to DMAIC, the problem-solving strategy of Six Sigma. It will give you an excellent framework to use in conducting quality improvement projects.
- New examples that illustrate applications of statistical quality improvement techniques in non-manufacturing settings. Many examples and exercises are based on real data.
- New developments in the area of measurement systems analysis
- New features of Minitab V15 incorporated into the text
- Numerous new examples, exercises, problems, and techniques to enhance your absorption of the material
About the Author
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, from 1969 to 1984 he was a faculty member of the School of Industrial & Systems Engineering at the Georgia Institute of Technology; from 1984 to 1988 he was at the University of Washington, where he held the John M. Fluke Distinguished chair of Manufacturing Engineering, was Professor of Mechanical Engineering, and Director of the Program in industrial 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 has authored and coauthored many technical papers in these fields and is an author of twelve other books. Dr. Montgomery is a Fellow of the American Society for Quality, a Fellow of the American Statistical Association, a Fellow of the Royal Statistical Society, a Fellow of the Institute of Industrial Engineers, and an Elected member of the International Statistical Institute. 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
Chapter 1. Quality Improvement in the Modern Business Environment .
PART I: STATISTICAL METHODS USEFUL IN QUALITY CONTROL AND IMPROVEMENT.
Chapter 2. Modeling Process Quality.
Chapter 3. Statistics and Sampling Distributions.
PART II: BASIC METHODS OF STATISTICAL PROCESS CONTROL AND CAPABILITY ANALYSIS.
Chapter 4. Methods and Philosophy of Statistical Process Control.
Chapter 5. Control Charts for Variables.
Chapter 6. Control Charts for Attributes.
Chapter 7. Process and Measurement System Capability Analysis.
PART III: OTHER STATISTICAL PROCESS-MONITORING AND CONTROL TECHNIQUES.
Chapter 8. Cumulative Sum and Exponentially Weighted Moving Average Control Charts.
Chapter 9. Other Univariate Statistical Process Monitoring and Control Techniques.
Chapter 10. Multivariate Process Monitoring and Control.
Chapter 11. Engineering Process Control and SPC.
PART IV: PROCESS DESIGN AND IMPROVEMENT WITH DESIGNED EXPERIMENTS.
Chapter 12. Factorial and Fractional Factorial Experiments for Process Design and Improvement.
Chapter 13. Process Optimization with Designed Experiments.
PART V: ACCEPTANCE SAMPLING.
Chapter 14. Lot-by-Lot Acceptance Sampling for Attributes.
Chapter 15. Other Acceptance-Sampling Techniques.
Appendices.
Answers to Selected Problems .
Index.