Preface

Introduction

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-the-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 situations. Although statistical techniques are emphasized throughout, the book has a strong engineering and management orientation. Extensive knowledge of statistics is not a prerequisite for using this book. Readers whose background includes a basic course in statistical methods will find much of the material in this book easily accessible.

Audience

The book is an outgrowth of more than 40 years of teaching, research, and consulting in the application of statistical methods for industrial problems. It is designed as a textbook for students enrolled in colleges and universities who are studying engineering, statistics, management, and related fields and are taking a first course in statistical quality control. The basic quality-control course is often taught at the junior or senior level. All of the standard topics for this course are covered in detail. Some more advanced material is also available in the book, and this could be used with advanced undergraduates who have had some previous exposure to the basics or in a course aimed at graduate students. I have also used the text materials extensively in programs for professional practitioners, including quality and reliability engineers, manufacturing and development engineers, product designers, managers, procurement specialists, marketing personnel, technicians and laboratory analysts, inspectors, and operators. Many professionals have also used the material for self-study.

Chapter Organization and Topical Coverage

The book contains five parts. Part 1 is introductory. The first chapter is an introduction to the philosophy and basic concepts of quality improvement. It notes that quality has become a major business strategy and that organizations that successfully improve quality can increase their productivity, enhance their market penetration, and achieve greater profitability and a strong competitive advantage. Some of the managerial and implementation aspects of quality improvement are included. Chapter 2 describes DMAIC, an acronym for Define, Measure, Analyze, Improve, and Control. The DMAIC process is an excellent framework to use in conducting quality-improvement projects. DMAIC often is associated with Six Sigma, but regardless of the approach taken by an organization strategically, DMAIC is an excellent tactical tool for quality professionals to employ.

Part 2 is a description of statistical methods useful in quality improvement. Topics include sampling and descriptive statistics, the basic notions of probability and probability distributions, point and interval estimation of parameters, and statistical hypothesis testing. These topics are usually covered in a basic course in statistical methods; however, their presentation in this text is from the quality-engineering viewpoint. My experience has been that even readers with a strong statistical background will find the approach to this material useful and somewhat different from a standard statistics textbook.

Part 3 contains four chapters covering the basic methods of statistical process control (SPC) and methods for process capability analysis. Even though several SPC problem-solving tools are discussed (including Pareto charts and cause-and-effect diagrams, for example), the primary focus in this section is on the Shewhart control chart. The Shewhart control chart certainly is not new, but its use in modern-day business and industry is of tremendous value.

There are four chapters in Part 4 that present more advanced SPC methods. Included are the cumulative sum and exponentially weighted moving average control charts (Chapter 9), several important univariate control charts such as procedures for short production runs, autocorrelated data, and multiple stream processes (Chapter 10), multivariate process monitoring and control (Chapter 11), and feedback adjustment techniques (Chapter 12). Some of this material is at a higher level than Part 3, but much of it is accessible by advanced undergraduates or first-year graduate students. This material forms the basis of a second course in statistical quality control and improvement for this audience.

Part 5 contains two chapters that show how statistically designed experiments can be used for process design, development, and improvement. Chapter 13 presents the fundamental concepts of designed experiments and introduces factorial and fractional factorial designs, with particular emphasis on the two-level system of designs. These designs are used extensively in the industry for factor screening and process characterization. Although the treatment of the subject is not extensive and is no substitute for a formal course in experimental design, it will enable the reader to appreciate more sophisticated examples of experimental design. Chapter 14 introduces response surface methods and designs, illustrates evolutionary operation (EVOP) for process monitoring, and shows how statistically designed experiments can be used for process robustness studies. Chapters 13 and 14 emphasize the important interrelationship between statistical process control and experimental design for process improvement.

Two chapters deal with acceptance sampling in Part 6. The focus is on lot-by-lot acceptance sampling, although there is some discussion of continuous sampling and MIL STD 1235C in Chapter 14. Other sampling topics presented include various aspects of the design of acceptance-sampling plans, a discussion of MIL STD 105E, and MIL STD 414 (and their civilian counterparts: ANSI/ASQC ZI.4 and ANSI/ASQC ZI.9), and other techniques such as chain sampling and skip-lot sampling.

Throughout the book, guidelines are given for selecting the proper type of statistical technique to use in a wide variety of situations. In addition, extensive references to journal articles and other technical literature should assist the reader in applying the methods described. I also have shown how the different techniques presented are used in the DMAIC process.

New To This Edition

The 8^th edition of the book has new material on several topics, including implementing quality improvement, applying quality tools in nonmanufacturing settings, monitoring Bernoulli processes, monitoring processes with low defect levels, and designing experiments for process and product improvement. In addition, I have rewritten and updated many sections of the book. This is reflected in over two dozen new references that have been added to the bibliography. I think that has led to a clearer and more current exposition of many topics. I have also added over 80 new exercises to the end-of-chapter problem sets.

Supporting Text Materials

Computer Software

The computer plays an important role in a modern quality-control course. This edition of the book uses Minitab as the primary illustrative software package. I strongly recommend that the course have a meaningful computing component. To request this book with a student version of Minitab included, contact your local Wiley representative. The student version of Minitab has limited functionality and does not include DOE capability. If your students will need DOE capability, they can download the fully functional 30-day trial at www.minitab.com or purchase a fully functional time-limited version from e-academy.com.

Supplemental Text Material

I have written a set of supplemental materials to augment many of the chapters in the book. The supplemental material contains topics that could not easily fit into a chapter without seriously disrupting the flow. The topics are shown in the Table of Contents for the book and in the individual chapter outlines. Some of this material consists of proofs or derivations, new topics of a (sometimes) more advanced nature, supporting details concerning remarks or concepts presented in the text, and answers to frequently asked questions. The supplemental material provides an interesting set of accompanying readings for anyone curious about the field. It is available at www.wiley.com/college/montgomery.

   Student Resource Manual

The text contains answers to most of the odd-numbered exercises. A Student Resource Manual is available from John Wiley & Sons that presents comprehensive annotated solutions to these same odd-numbered problems. This is an excellent study aid that many text users will find extremely helpful. The Student Resource Manual may be ordered in a set with the text or purchased separately. Contact your local Wiley representative to request the set for your bookstore or purchase the Student Resource Manual from the Wiley Web site.

Instructor’s Materials

The instructor’s section of the textbook Website contains the following:

1. Solutions to the text problems
2. The supplemental text material described above
3. A set of Microsoft PowerPoint slides for the basic SPC course
4. Data sets from the book, in electronic form
5. Image Gallery illustrations from the book in electronic format

The instructor’s section is for instructor use only and is password protected. Visit the Instructor Companion Site portion of the Web site, located at www.wiley.com/college/montgomery, to register for a password.

The World Wide Web Page

The Web page for the book is accessible through the Wiley home page. It contains the supplemental text material and the data sets in electronic form. It will also be used to post items of interest to text users. The Web site address is www.wiley.com/college/montgomery. Click on the cover of the text you are using.

ACKNOWLEDGMENTS

Many people have generously contributed their time and knowledge of statistics and quality improvement to this book. I would like to thank Dr. Bill Woodall, Dr. Doug Hawkins, Dr. Joe Sullivan, Dr. George Runger, Dr. Bert Keats, Dr. Bob Hogg, Mr. Eric Ziegel, Dr. Joe Pignatiello, Dr. John Ramberg, Dr. Ernie Saniga, Dr. Enrique Del Castillo, Dr. Sarah Streett, and Dr. Jim Alloway for their thorough and insightful comments on this and previous editions. They generously shared many of their ideas and teaching experiences with me, leading to substantial improvements in the book.

Over the years since the first edition was published, I have received assistance and ideas from a great many other people. A complete list of colleagues with whom I have interacted would be impossible to enumerate. However, some of the major contributors and their professional affiliations are as follows: Dr. Mary R. Anderson-Rowland, Dr. Dwayne A. Rollier, and Dr. Norma F. Hubele, Arizona State University; Dr. Murat Kulahci, Technical University of Denmark; Mr. Seymour M. Selig, formerly of the Office of Naval Research; Dr. Lynwood A. Johnson, Dr. Russell G. Heikes, Dr. David E. Fyffe, and Dr. H. M. Wadsworth, Jr., Georgia Institute of Technology; Dr. Sharad Prabhu, Dr. Bradley Jones, and Dr. Robert Rodriguez, SAS Institute; Dr. Scott Kowalski, Minitab; Dr. Richard L. Storch and Dr. Christina M. Mastrangelo, University of Washington; Dr. Cynthia A. Lowry, formerly of Texas Christian University; Dr. Smiley Cheng, Dr. John Brewster, Dr. Brian Macpherson, and Dr. Fred Spiring, University of Manitoba; Dr. Joseph D. Moder, University of Miami; Dr. Frank B. Alt, University of Maryland; Dr. Kenneth E. Case, Oklahoma State University; Dr. Daniel R. McCarville, Dr. Lisa Custer, Dr. Pat Spagon, and Mr. Robert Stuart, all formerly of Motorola; Dr. Richard Post, Intel Corporation; Dr. Dale Sevier, San Diego State University; Mr. John A. Butora, Mr. Leon V. Mason, Mr. Lloyd K. Collins, Mr. Dana D. Lesher, Mr. Roy E. Dent, Mr. Mark Fazey, Ms. Kathy Schuster, Mr. Dan Fritze, Dr. J. S. Gardiner, Mr. Ariel Rosentrater, Mr. Lolly Marwah, Mr. Ed Schleicher, Mr. Amiin Weiner, and Ms. Elaine Baechtle, IBM; Mr. Thomas C. Bingham, Mr. K. Dick Vaughn, Mr. Robert LeDoux, Mr. John Black, Mr. Jack Wires, Dr. Julian Anderson, Mr. Richard Alkire, and Mr. Chase Nielsen, Boeing Company; Ms. Karen Madison, Mr. Don Walton, and Mr. Mike Goza, Alcoa; Mr. Harry Peterson-Nedry, Ridgecrest Vineyards and The Chehalem Group; Dr. Russell A. Boyles, formerly of Precision Castparts Corporation; Dr. Sadre Khalessi and Mr. Franz Wagner, Signetics Corporation; Mr. Larry Newton and Mr. C. T. Howlett, Georgia Pacific Corporation; Mr. Robert V. Baxley, Monsanto Chemicals; Dr. Craig Fox, Dr. Thomas L. Sadosky, Mr. James F. Walker, and Mr. John Belvins, Coca-Cola Company; Mr. Bill Wagner and Mr. Al Pariseau, Litton Industries; Mr. John M. Fluke, Jr., John Fluke Manufacturing Company; Dr. Paul Tobias, formerly of IBM and Semitech; Dr. William DuMouchel and Ms. Janet Olson, BBN Software Products Corporation. I would also like to acknowledge the many contributions of my late partner in Statistical Productivity Consultants, Mr. Sumner S. Averett. All of these individuals and many others have contributed to my knowledge of the quality-improvement field.

Other acknowledgments go to the editorial and production staff at Wiley, particularly Ms. Charity Robey and Mr. Wayne Anderson, with whom I worked for many years, and my current editor, Ms. Jenny Welter; they have had much patience with me over the years and have contributed greatly toward the success of this book. Dr. Cheryl L. Jennings made many valuable contributions by her careful checking of the manuscript and proof materials. I also thank Dr. Gary Hogg and Dr. Ron Askin, former and current chairs of the Department of Industrial Engineering at Arizona State University, for their support and for providing a terrific environment in which to teach and conduct research.

I thank the various professional societies and publishers who have given permission to reproduce their materials in my text. Permission credit is acknowledged at appropriate places in this book.

I am also indebted to the many organizations that have sponsored my research and my graduate students for a number of years, including the member companies of the National Science Foundation/Industry/University Cooperative Research Center in Quality and Reliability Engineering at Arizona State University, the Office of Naval Research, the National Science Foundation, Semiconductor Research Corporation, Aluminum Company of America, and IBM Corporation. Finally, I thank the many users of the previous editions of this book, including students, practicing professionals, and my academic colleagues. Many of the changes and improvements in this edition of the book are the direct result of your feedback.

DOUGLAS C. MONTGOMERY

Tempe, Arizona