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The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
". . . a goldmine of knowledge on accelerated life testing principles and practices . . . one of the very few capable of advancing the science of reliability. It definitely belongs in every bookshelf on engineering."
–Dev G. Raheja, Quality and Reliability Engineering International
". . . an impressive book. The width and number of topics covered, the practical data sets included, the obvious knowledge and understanding of the author and the extent of published materials reviewed combine to ensure that this will be a book used frequently."
–Journal of the Royal Statistical Society
A benchmark text in the field, Accelerated Testing: Statistical Models, Test Plans, and Data Analysis offers engineers, scientists, and statisticians a reliable resource on the effective use of accelerated life testing to measure and improve product reliability. From simple data plots to advanced computer programs, the text features a wealth of practical applications and a clear, readable style that makes even complicated physical and statistical concepts uniquely accessible. A detailed index adds to its value as a reference source.
About the Author
Wayne B. Nelson, PHD, is a leading expert on analysis of reliability and accelerated test data. Formerly with General Electric Research & Development for twenty-three years, he now privately consults on and teaches engineering applications of statistics for many companies, professional societies, and universities. For his outstanding contributions to reliability data analysis and accelerated testing, he was elected a fellow of the Institute of Electrical and Electronics Engineers, the American Society for Quality, and the American Statistical Association.
DR. WAYNE NELSON IS AWARDED THE SHEWHART MEDAL
American Society for Quality awarded Dr. Wayne Nelson of Schenectady, New York the 2003 Shewhart Medal. The Medal honors his outstanding technical leadership, particularly for innovative developments and applications of theory and methods for analyzing quality, reliability, and accelerated test data, and for widely disseminating such developments through his books and many publications, talks, and courses.
The Shewhart Medal for outstanding technical leadership is named after Dr. Walter A. Shewhart, who pioneered statistical methods for controlling and improving the quality of manufactured products. These methods contributed significantly to the United States' war effort in World War II. Subsequently taken to Japan by Dr. W. Edwards Deming, these methods revolutionized Japan's industries. Today these methods are part of widely used Six Sigma training on how to improve the quality of products and services.
The American Society for Quality is the world's largest professional society dedicated to the improved quality of products and services. It serves its members and the public through a variety of educational activities, including conferences, training courses, journals, and books.
Dr. Nelson is a graduate of the California Institute of Technology (Caltech) and the University of Illinois. Formerly with GE Research & Development, he now privately consults and gives courses for companies, professional societies, and universities. For his technical contributions, he was elected a Fellow of the American Society for Quality, the American Statistical Association, and the Institute of Electrical and Electronic Engineers. He recently spent four months in Argentina on a Fulbright Award, lecturing on analysis of product reliability data.
Table of Contents
Models for Life Tests with Constant Stress.
Graphical Data Analysis.
Complete Data and Least Squares Analyses.
Censored Data and Maximum Likelihood Methods.
Competing Failure Modes and Size Effect.
Least-Squares Comparisons for Complete Data.
Maximum Likelihood Comparisons for Censored and Other Data.
Models and Data Analyses for Step and Varying Stress.