Description: First edition. | Hoboken, NJ, USA : Wiley, 2021. | Includes
bibliographical references and index.
Identifiers: LCCN 2020035725 (print) | LCCN 2020035726 (ebook) | ISBN
9781119664000 (cloth) | ISBN 9781119664017 (adobe pdf) | ISBN
9781119663942 (epub)
Subjects: LCSH: Accelerated life testing. | Failure analysis (Engineering)
Classification: LCC TA169.3 .B35 2021 (print) | LCC TA169.3 (ebook) | DDC
620/.00452–dc23
LC record available at https://lccn.loc.gov/2020035725
LC ebook record available at https://lccn.loc.gov/2020035726
Cover Design: Wiley
Cover Image: © Piergiov/Getty Images
With great love and affection, we dedicate this book to
Sarah and Julia Balakrishnan, and Colleen Cutler NB
Grace Chu, Sophia Ling, and Sheldon Ling MHL
Tian Feng and Victoria So HYS
Preface
Lifetime information obtained from one‐shot devices is very limited as the entire data are either left‐ or right‐censored. For this reason, the analysis of one‐shot device testing data poses a special challenge. This book provides several statistical inferential methods for analyzing one‐shot device lifetime data obtained from accelerated life‐tests and also develops optimal designs for two mainstream accelerated life‐tests – constant‐stress and step‐stress accelerated life‐tests – that are commonly used in reliability practice. The discussions provided in the book would enable reliability practitioners to better design their experiments for data collection from efficient accelerated life‐tests when there are budget constraints in place. This is important from estimation and prediction point of view as such optimal designs would result in as accurate an inference as possible under the constraints imposed on the reliability experiment. Moreover, R codes are presented within each chapter so that users can try out performing their own analysis on one‐shot device testing data.
In addition, the inferential methods and the procedures for planning accelerated life‐tests discussed in this book are not only limited to one‐shot devices alone but also can be extended naturally to accelerated life‐tests with periodic inspections (interval‐censoring) and those with continuous monitoring and censoring (right‐censoring). The book finally concludes by highlighting some important issues and problems that are worth considering for further research. This may be especially useful for research scholars and new researchers interested in taking on this interesting and challenging area of research in reliability theory and practice.
It is possible that some pertinent results or references got omitted in this book, and we assure you that it is due to inadvertency on our part and not due to scientific antipathy. We will appreciate greatly if the readers inform us of any corrections/omissions, or any comments pertinent to any of the discussions in the book!
Our sincere thanks go to the entire Wiley team, Ms. Mindy Okura‐Marszycki, Ms. Kathleen Santoloci, and Mr. Brett Kurzman, for taking great interest in this project from day one, for all their help and encouragement during the whole course, and for their fine assistance during the final production stage of the book. Our thanks also go to our research collaborators and graduate students for their incisive comments and queries, which always benefited us greatly and helped clarify some of our own ideas! We express our sincere appreciation to Ms. Elena Maria Castilla Gonzalez, a doctoral student of Professor Leandro Pardo in the Department of Statistics and Operations Research at Complutense University of Madrid, Spain, for her careful reading of Chapter 5 and also for sharing with us some R codes that she had developed concerning robust inferential methods for one‐shot device test analyses. Last but not least, our special thanks go to our families for their patience and understanding, and for providing constant support and encouragement during our work on this book!
Finally, the first author (NB) wishes to state to his older daughter, Ms. Sarah Balakrishnan, that though she lost out on getting his Volvo car due to a major car accident, she should be heartened by the fact that the accident resulted in the germination of his interest and ideas on one‐shot devices (airbags), and ultimately this book solely dedicated to the topic!
July, 2020
Narayanaswamy Balakrishnan
Man Ho Ling
Hon Yiu So
About the Companion Website
This book is accompanied by a companion website:
www.wiley.com/go/Balakrishnan/Accelerated_Life_Testing
The Student companion site will contain the codes and case studies.
1 One‐Shot Device Testing Data
1.1 Brief Overview
One‐shot device testing data analyses have recently received great attention in reliability studies. The aim of this chapter is to provide an overview on one‐shot device testing data collected from accelerated life‐tests (ALTs). Section 1.2 surveys typical examples of one‐shot devices and associated tests in practical situations. Section 1.3 describes several popular ALTs, while Section 1.4 provides some examples of one‐shot device testing data that are typically encountered in reliability and survival studies. Finally, Section 1.5 details some recent developments on one‐shot device testing data analyses and associated issues of interest.
1.2 One‐Shot Devices
Valis et al. (2008) defined one‐shot devices as units that are accompanied by an irreversible chemical reaction or physical destruction and could no longer function properly after its use. Many military weapons are examples of one‐shot devices. For instance, the mission of an automatic weapon gets completed successfully only if it could fire all the rounds placed in a magazine or in ammunition feed belt without any external intervention. Such devices will usually get destroyed during usual operating conditions and can therefore perform their intended function only once.
Shaked and Singpurwalla (1990) discussed the submarine pressure hull damage problem from a Bayesian perspective and assessed the effect of various strengths of underwater shock waves caused by either a nuclear device or a chemical device on the probability of damage
