Managing, controlling and improving quality is a critical activity in modern business organizations. Quality is directly linked to productivity, competitiveness, customer satisfaction, business growth, elimination of waste and other non-value added activities, and overall business success. Cycle time and throughput is just as important in a hospital emergency room as it is in a semiconductor factory. Defects and errors don't occur just in factories, they occur in transactional and service business such as banks, insurance companies, and hospitals. Even your local and state governments have a keen interest in improving service quality in operations such as issuing drivers licenses and motor vehicle registration. The U.S. Navy has had an intensive quality improvement program for many years.
This book presents an organized approach to quality management, control, and improvement. Quality problems usually are the outcome of uncontrolled or excessive variability in product or service characteristics that are critical to the customer and statistical tools and other analytical methods play an important role in solving these problems. However, these techniques need to be implemented within a management structure that will ensure success. We focus on both the management structure and the statistical and analytical tools. Our approach to organizing and presenting this material is based on many years of teaching, research, and professional practice across a wide range of business and industrial settings.
Show moreManaging, controlling and improving quality is a critical activity in modern business organizations. Quality is directly linked to productivity, competitiveness, customer satisfaction, business growth, elimination of waste and other non-value added activities, and overall business success. Cycle time and throughput is just as important in a hospital emergency room as it is in a semiconductor factory. Defects and errors don't occur just in factories, they occur in transactional and service business such as banks, insurance companies, and hospitals. Even your local and state governments have a keen interest in improving service quality in operations such as issuing drivers licenses and motor vehicle registration. The U.S. Navy has had an intensive quality improvement program for many years.
This book presents an organized approach to quality management, control, and improvement. Quality problems usually are the outcome of uncontrolled or excessive variability in product or service characteristics that are critical to the customer and statistical tools and other analytical methods play an important role in solving these problems. However, these techniques need to be implemented within a management structure that will ensure success. We focus on both the management structure and the statistical and analytical tools. Our approach to organizing and presenting this material is based on many years of teaching, research, and professional practice across a wide range of business and industrial settings.
Show moreChapter 1. Introduction to Quality.
1.1 The Meaning of Quality and Quality Improvement.
1.2 A Brief History of Quality Control and Improvement.
1.3 Statistical Methods for Quality Control and Improvement.
1.4 Quality and Productivity.
1.5 Quality Costs.
1.6 Legal Aspects of quality.
1.7 Implementing Quality Improvement.
Chapter 2. Management Aspects of Quality.
2.1 Introduction.
2.2 Quality Philosophy and Management Strategies.
2.3 The DMAIC Process.
Chapter 3. Tools and Techniques for Quality Control and Improvement.
3.1 Introduction.
3.2 Chance and Assignable Causes of Quality Variation.
3.3 The Control Chart.
3.4 The Rest of the Magnificent Seven.
3.5 Implementing SPC in a Quality Improvement Program.
3.6 An Application of SPC.
3.7 Applications of Quality Process and Quality Improvement Tools in Transactional
and Service Businesses.
Chapter 4. Statistical Inference about Product and Process Quality.
4.1 Describing Variation.
4.2 Probability Distributions.
4.3 The Normal Distribution.
4.4 Statistical Inference.
4.5 Statistical Inference for a Single Sample.
4.6 Statistical Inference for Two
Chapter 5. Control Charts for Variables.
5.1 Introduction.
5.2 and R x Charts.
5.3 and S Charts.
5.4 Shewart Control Chart for Individual Measurements.
5.5 Summary of Procedures for , R, S, and Individuals Charts.
5.6 Example Applications of , R, S, and Individuals Charts.
5.7 Cumulative Sum Control Charts.
5.8 Exponentially Weighted Moving Average Control Charts.
5.9 Process Capability Analysis Using Control Charts.
Chapter 6. Control Charts for Attributes.
6.1 Introduction.
6.2 The Control Chart for Fraction Nonconforming.
6.3 Control Charts for Nonconformities (Defects).
6.4 Choice between Attributes and Variables Control Charts.
6.5 Guidelines for Implementing Control Charts.
Chapter 7. Lot-by-Lot Acceptance Sampling Procedures.
7.1 The Acceptance Sampling Problem.
7.2 Single-Sampling Plans for Attributes.
7.3 Double, Multiple, and Sequential Sampling.
7.4 Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859).
7.5 The Dodge–Romig Sampling Plans.
7.6 Military Standard 414 (ANSI/ASQ Z1.9).
7.7 Chain Sampling.
7.8 Continuous Sampling.
7.9 Skip-Lot Sampling Plans.
Chapter 8. Process Design and Improvement with Designed Experiments.
8.1 What Is Experimental Design?
8.2 Examples of Designed Experiments in Process and Product Improvement.
8.3 Guidelines for Designing Experiments.
8.4 The Analysis of Variance.
8.5 Factorial Experiments.
8.6 The 2k Factorial Design.
8.7 Fractional Replication of the 2k Design.
8.8 Response Surface Methods.
8.9 Robust Product and Process Design.
Chapter 9. Reliability.
9.1 Basic Concepts of Reliability.
9.2 Life Distributions.
9.3 Instantaneous Failure Rate.
9.4 Life Cycle Reliability.
9.5 Determining System Reliability from Component Reliabilities.
9.6 Life Testing and Reliability Estimation.
9.7 Availability and Maintainability.
9.8 Failure Mode and Effects Analysis.
References.
Glossary.
Appendix.
A. I Summary of Common Probability Distribution Cities Used in Quality Control and Improvement.
A. II Cumulative Standard Normal Distribution.
A. III Percentage Points of the Distribution.
A. IV Percentage Points of the t Distribution.
A. V Percentage Points of the F Distribution.
A. VI Factors for Constructing Variables Control Charts.
Answers to Selected Exercises.
Index.
DOUGLAS C. MONTGOMERY, PhD, is Regents Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery is a Fellow of the American Statistical Association, the American Society for Quality, the Royal Statistical Society, and the Institute of Industrial Engineers and has more than thirty years of academic and consulting experience. He has devoted his research to engineering statistics, specifically the design and analysis of experiments, statistical methods for process monitoring and optimization, and the analysis of time-oriented data. Dr. Montgomery is the coauthor of Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition and Introduction to Time Series Analysis and Forecasting, both published by Wiley.
Your book Managing, Controlling, and ImprovingQuality worked out very well in my senior-level class in thepast fall semester. Actually students really liked the book. Iplanned to cover a little bit of acceptance sampling plans but Ididn t have sufficient time. I did cover Chapter 9Reliability though. It was a great mix of managing aspects ofquality, tools and techniques of quality control and design ofexperiments, plus a little bit of reliability. Students were happyand I was also happy. We will keep using this book which is idealfor my class. Dr. Byung Rae Choe, Indiana University ofPennsylvania
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