Statistical Analysis of Modern Reliability Data

Yueyao Wang, I. Chen Lee, Lu Lu, Yili Hong

Research output: Chapter in Book/Report/Conference proceedingChapter


Reliability analysis has been using time-to-event data, degradation data, and recurrent event data, while the associated covariates tend to be simple and constant over time. Over the past years, we have witnessed rapid development of sensor and wireless technology, which enables us to track the product usage and use environment. Nowadays, we are able to collect richer information on covariates which provides opportunities for better reliability predictions. In this chapter, we first review recent development on statistical methods for reliability analysis. We then focus on introducing several specific methods that were developed for different types of reliability data by utilizing the covariate information. Illustrations of those methods are also provided using examples from industry. We also provide a brief review on recent developments of test planning and then focus on illustrating the sequential Bayesian designs with examples of fatigue testing for polymer composites. The chapter is concluded with some discussions and remarks.

Original languageEnglish
Title of host publicationSpringer Handbooks
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages23
Publication statusPublished - 2023

Publication series

NameSpringer Handbooks
ISSN (Print)2522-8692
ISSN (Electronic)2522-8706

All Science Journal Classification (ASJC) codes

  • General


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