A first course in quality engineering : integrating statistical and management methods of quality.

Includes bibliographical references and index.

"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 criteriaIncludes new mini-projects and examples throughoutIncorporates Lean methods for reducing cycle time, increasing throughput, and reducing wasteContains increased coverage of strategic planningThis 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)"--

"Preface to Second Edition "The average Japanese worker has a more in-depth knowledge of statistical methods than an average American engineer," explained a U.S. business executive returning from a visit to Japan, as a reason why the Asian rivals were able to produce better quality products than U.S. manufacturers. That statement, made almost 30 years ago, may be true even today as Japanese cars are continuously sought by customers who care for quality and reliability. Dr. Deming, recognized as the guru who taught the Japanese how to make quality products, said: "Industry in America needs thousands of statistically minded engineers, chemists, doctors of medicine, purchasing agents, managers" as a remedy to improve the quality of products and services produced in the U.S. He insisted that engineers, and other professionals, should have the capacity for statistical thinking, which comes from learning the statistical tools and the theory behind them. The engineering accreditation agency in the U.S., ABET, a body made up of academics and industry leaders, stipulates that every engineering graduate should have "an ability to design and conduct experiments, as well as to analyze data and interpret results" as part of the accreditation criteria. Yet, we see that most of the engineering majors from a typical "--