Academic Press Reliability Analysis and Plans for Successive Testing: Start-up Demonstration Tests and Applications

Reliability Analysis and Plans for Successive Testing: Start-up Demonstration Tests and Applications discusses all past and recent developments on start-up demonstration tests in the context of current numerical and illustrative examples to clarify available methods for distribution theorists and applied mathematicians dealing with control problems. Throughout the book, the authors focus on the panorama of open problems and issues of further interest. As contemporary manufacturers face tremendous commercial pressures to assemble works of high reliability, defined as ‘the probability of the product performing its role under the stated conditions and over a specified period of time’, this book helps address testing issues. Review Complete reference guide for statistical distribution theorists and applied mathematicians specializing in quality control research for reliability assurance purposes From the Back Cover Contemporary manufacturers face tremendous commercial pressures to assemble works of high reliability, defined as ``the probability of the product performing its intended purpose under the stated conditions and over a specified period of time. A start-up demonstration testing approach (in terms of runs, frequency, scans, etc.) is frequently used as a proxy for this critical concept of reliability. Often, it is the basis on which the decision to accept or reject a unit is made. Reliability Analysis and Plans for Successive Testing: Start-up Demonstration Tests and Applications discusses all past and recent developments on start-up demonstration tests, in addition to providing current numerical and illustrative examples to clarify available methods for distribution theorists and applied mathematicians dealing with quality control problems. As the criteria used in start-up demonstration tests are closely related to general pattern waiting problems, defined on sequences of discrete random variables, the authors also provide a detailed discussion about the relation between the theory of start-up demonstration testing with some well-known discrete distributions. Throughout, while describing all the developments, the authors also comment on the panorama of open problems with issues of further interest. About the Author Narayanaswamy Balakrishnan, Distinguished University Professor, is in the Department of Mathematics and Statistics McMaster University Hamilton, Ontario, Canada. Professor Balakrishnan is an internationally recognized expert on statistical distribution theory, and a book-powerhouse with 16 authored books, 4 authored handbooks, and 27 edited books under his name. He is currently the Editor-in-Chief of Communications in Statistics published by Taylor & Francis, and was also the Editor-in-Chief for the revised version of Encyclopedia of Statistical Sciences published by John Wiley & Sons. He is a Fellow of the American Statistical Association and a Fellow of the Institute of Mathematical Statistics, and in 2016 was awarded an Honorary Doctorate for The National and Kapodistrian University of Athens, Athens, Greece. Markos Koutras, Professor of Statistics and Applied Probability, is in the Department of Statistics and Insurance Science, University of Piraeus, and is currently the Vice-Rector of Finance, Planning and Development of the University of Piraeus, Greece. Koutras’ research interests include asymptotic theory, combinatorial distributions, multivariate analysis, reliability theory, statistical quality control, and theory of runs/scans/patterns, and he has published a book on the last topic, collaboratively with Professor N. Balakrishnan, with John Wiley & Sons. Fotios Milienos, Assistant Professor, in the Department of Sociology, Panteion University of Social and Political Sciences, Greece. His research interests include theory of runs and patterns, cure rate modeling, and statistical methods in behavioral research.