A Bayesian reliability evaluation method with different types of data from multiple sources

Lizhi Wang, Rong Pan, Xiaohong Wang, Wenhui Fan and Jinquan Xuan

Reliability Engineering and System Safety, 2017, vol. 167, issue C, 128-135

Abstract: Bernoulli data (pass/fail), lifetime data, and degradation data are commonly encountered in product reliability assessment. Oftentimes these data are collected from different sources (such as field use, accelerated tests, history, and so on), and it is desirable to utilize these heterogeneous data within one computational framework to provide a comprehensive evaluation of product reliability. In this paper, three Bayesian inference models are proposed to establish the relationship among pass/fail-type Bernoulli data, lifetime data, and degradation data, and to integrate them to solve relevant problems and improve the accuracy of reliability prediction. The proposed methods are demonstrated by a synthetic example and two real examples. The evaluation results can be used for formulating product development strategies.

Keywords: Data integration; Reliability evaluation; Bayesian method; Bernoulli data; Data from multiple sources (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:167:y:2017:i:c:p:128-135

DOI: 10.1016/j.ress.2017.05.039

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