Completely revised and updated, A First Course in Quality Engineering: Integrating Statistical and Management Methods of Quality, Second Edition contains virtually all the information an engineer needs to function as a quality engineer. The authors not only break things down very simply but also give a full understanding of why each topic covered is essential to learning proper quality management. They present the information in a manner that builds a strong foundation in quality management without overwhelming readers. See what’s new in the new edition: Reflects changes in the latest revision of the ISO 9000 Standards and the Baldrige Award criteria Includes new mini-projects and examples throughout Incorporates Lean methods for reducing cycle time, increasing throughput, and reducing waste Contains increased coverage of strategic planning This text covers management and statistical methods of quality engineering in an integrative manner, unlike other books on the subject that focus primarily on one of the two areas of quality. The authors illustrate the use of quality methods with examples drawn from their consulting work, using a reader-friendly style that makes the material approachable and encourages self-study. They cover the must-know fundamentals of probability and statistics and make extensive use of computer software to illustrate the use of the computer in solving quality problems. Reorganized to make the book suitable for self study, the second edition discusses how to design Total Quality System that works. With detailed coverage of the management and statistical tools needed to make the system perform well, the book provides a useful reference for professionals who need to implement quality systems in any environment and candidates preparing for the exams to qualify as a certified quality engineer (CQE).

This edition includes increased emphasis on the connection between the experiment and the model that can be developed from the results of the experiment, as well as material on computer output and computer graphics.

Through years of teaching experience, John S. Lawson and John Erjavec have learned that it doesn't take much theoretical background before engineers can learn practical methods of data collections, analysis, and interpretation that will be useful in real life and on the job. With this premise in mind, the authors wrote ENGINEERING AND INDUSTRIAL STATISTICS, which includes the basic topics of engineering statistics but puts less emphasis on the theoretical concepts and elementary topics usually found in an introductory statistics book. Instead, the authors put more emphasis on techniques that will be useful for engineers. With fewer details of traditional probability and inference and more emphasis on the topics useful to engineers, the book is flexible for instructors and interesting for students.