Quality Improvement, Pearson New International Edition, 9th edition

Published by Pearson (August 27, 2013) © 2014

  • Dale H. Besterfield College of Engineering, Southern University at Carbondale, Besterfield and Associates
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For undergraduate and graduate-level courses in Quality Control, Statistical Process Control, Quality Improvement, and Quality Assurance. This book will be valuable in programs such as Quality Improvement, Lean Six Sigma, Quality Control, and Statistical Process Control; in Associate Degree in Quality and other technical programs; in Baccalaureate programs in Engineering, Technology, Health Care, Education, and Business; and in Masters Degree programs in business.

Formerly titled Quality Control, the field’s most accessible introduction to quality has been renamed and revamped to focus on quantitative aspects of quality improvement. New chapters on Lean Enterprise, Six Sigma, Experimental Design, and Taguchi’s Quality Engineering have been added, and this edition adds comprehensive coverage of fundamental statistical quality improvement concepts. A practical state-of-the-art approach is stressed throughout, and sufficient theory is presented to ensure that students develop a solid understanding of basic quality principles. To improve accessibility, probability and statistical techniques are presented through simpler math or developed via tables and charts. As with previous editions, this text is written to serve a widely diverse audience of students, including the growing number of “math shy” individuals who must play key roles in quality improvement.

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  • 1. Introduction to Quality Improvement
  • 2. Lean Enterprise
  • 3. Six Sigma
  • 4. Fundamentals of Statistics
  • 5. Statistical Process Control
  • 6. Control Charts for Variables
  • 7. Additional SPC Techniques for Variables
  • 8. Fundamentals of Probability
  • 9. Control Charts for Attributes
  • 10. Acceptance Sampling.
  • 11. Reliability
  • 12. Management and Planning Tools
  • 13. Experimental Design
  • 14. Taguchi’s Quality Engineering
  • Appendix
  • Table A. Areas under the Normal Curve
  • Table B. Factors for Computing Central Lines and 3 Control Limits for S, and R Charts
  • Table C. The Poisson Distribution
  • Table D. Random Numbers
  • Table E. Commonly Used Conversion Factors
  • Table-F. Critical Values of  T Distribution
  • Table G-1. Critical Values of F Distribution (a = 0.1)  
  • Table G-2. Critical Values of F Distribution (a = 0.05)  
  • Table G-3. Critical Values of F Distribution (a = 0.01)  
  • Table H. Orthogonal Arrays  
  • Selected Bibliography
  • Answers to Selected Exercises
  • Index

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