Statistical Process Control For Quality Improvement- Hardcover Version

J. Koronacki, J.R. Thompson

December 26, 2001 by Chapman and Hall/CRC
Reference - 456 Pages - 144 B/W Illustrations
ISBN 9781584882428 - CAT# C2425

USD$172.95

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Features

  • Provides a comprehensive treatment of the Theory of Contaminated Distribution, which forms the basis for SPC
  • Develops algorithms for using quality control based on higher dimensional data
  • Describes exploratory and graphical techniques for diagnosing the cause of a manufacturing or production problem
  • Demonstrates new graphical techniques that help clarify complex problems encountered at the planning stage
  • Offers optimization techniques useful in the design of experiments, including the simplex algorithm of Nelder and Mead as well as the rotatable designs of Box, Hunter, and Draper
  • Introduces bootstrapping as a means of test design and evaluation in SPC
  • Demonstrates new Bayesian-Pareto techniques for SPC
  • Explains the Seven Managerial and Planning Tools
  • Develops nonparametric tests for SPC
  • Examines testing procedures using numerous practical examples
  • Summary

    While the common practice of Quality Assurance aims to prevent bad units from being shipped beyond some allowable proportion, statistical process control (SPC) ensures that bad units are not created in the first place. Its philosophy of continuous quality improvement, to a great extent responsible for the success of Japanese manufacturing, is rooted in a paradigm as process-oriented as physics, yet produces a friendly and fulfilling work environment.

    The first edition of this groundbreaking text showed that the SPC paradigm of W. Edwards Deming was not at all the same as the Quality Control paradigm that has dominated American manufacturing since World War II. Statistical Process Control: The Deming Paradigm and Beyond, Second Edition reveals even more of Deming's philosophy and provides more techniques for use at the managerial level. Explaining that CEOs and service industries need SPC at least as much as production managers, it offers precise methods and guidelines for their use.

    Using the practical experience of the authors working both in America and Europe, this book shows how SPC can be implemented in a variety of settings, from health care to manufacturing. It also provides you with the necessary technical background through mathematical and statistical appendices. According to the authors, companies with managers who have adopted the philosophy of statistical process control tend to survive. Those with managers who do not are likely to fail. In which group will your company be?