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Process Capability Indices, by Samuel Kotz, Norman L. Johnson
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A solid, rigorous, yet comprehensible analysis of process capability indices, this work bridges the gap between theoretical statisticians and quality control practitioners, showing how an understanding of these indices can lead to process improvement.
- Sales Rank: #1817022 in Books
- Published on: 1993-06-01
- Released on: 1993-06-01
- Original language: English
- Number of items: 1
- Dimensions: 8.50" h x .51" w x 5.51" l, .76 pounds
- Binding: Hardcover
- 224 pages
About the Author
N. BALAKRISHNAN, PhD, is a Professor in the Department of Mathematics and Statistics at McMaster University, Hamilton, Ontario, Canada. He has published widely in different areas of statistics including distribution theory, order statistics and reliability. He has authored a number of books including four volumes in "Distributions in Statistics Series" of Wiley, coauthored with N. L. Johnson and S. Kotz. He is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.
CAMPBELL B. READ, PhD, is Professor Emeritus of Statistical Science at the Institute for the Study of Earth and Man at Southern Methodist University in Dallas, Texas. He studied mathematics at the University of Cambridge in England, and obtained a PhD in mathematical statistics from the University of North Carolina at Chapel Hill. He is the author of several research papers in sequential analysis, properties of statistical distributions, and contingency table analysis. He is the author of several biographies appearing in "Leading Personalities in Statistical Sciences" and of various entries in this Encyclopedia, and is a coauthor of "Handbook of the Normal Distribution," He is an elected member of the International Statistical institute, has served on the faculty of the American University of Beirut, Lebanon, and was a Senior Research Scholar in 1987 at Corpus Christi College, University of Cambridge.
BRANI VIDAKOVIC, PhD, is Professor of Statistics at The Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology, Atlanta, Georgia. He obtained a BS and MS in mathematics at the University of Belgrade, Serbia, and a PhD instatistics at Purdue University, West Lafayette, Indiana. He is the author or coauthor of several books and numerous research papers on minimax theory, wavelets and computational and applied statistics. Dr. Vidakovic is a member of the Institute of Mathematical Statistics, American Statistical Association, International Society for Bayesian Analysis, and Bernoulli Society, and an elected member of the International Statistical Institute.
NORMAN L. JOHNSON, PHD, was Professor Emeritus, Department of Statistics, University of North Carolina at Chapel Hill. Dr. Johnson was Editor-in-Chief (with Dr. Kotz) of the "Encyclopedia of Statistical Sciences," Second Edition (Wiley).
ADRIENNE W. KEMP, PHD, is Honorary Senior Lecturer at the Mathematical Institute, University of St. Andrews in Scotland.
SAMUEL KOTZ, PHD, is Professor and Research Scholar, Department of Engineering Management and Systems Engineering, The George Washington University in Washington, DC.
Most helpful customer reviews
27 of 27 people found the following review helpful.
first good statistical treatment for general distributions
By Michael R. Chernick
The quality movement in the US in the 1980s and 1990s has led to a great deal of quality efforts that stress statistical measurements of process capability. These indices are intended to answer the question "How often will a manufactured part fall outsided specification limits?" Certain standards and tests based on capability indices have validity when the process variation has a normal distribution.
However, it has been my experience in the medical device industry that many processes are non-normal and that the application of the normal theory in these cases can lead one astray. Others have found this to be the case in the automobile industry as well as in other industries.
Also some people treat these indices as though they are known constants when in practice we almost always use sample estimates of means and standard deviations in our calculation of the index. This means that the "index" is itself an estimate of the capability parameter.
These issues are recognized and emphasized by Kotz and Johnson in this wonderful little monograph. It was the first book to address many of these issues and to summarize what it known based on the scattered literature. They treat all the major indices and present normal theory and bootstrap alternatives among others. It is very authoritative and is an important reference for anyone dealing with these quality control issues.
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