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A Bayesian reliability evaluation method with different types of data from multiple sources
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DOI：10.1016/j.ress.2017.05.039.png)
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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. (C) 2017 Elsevier Ltd. All rights reserved.
Keyword:
Data integration
Reliability evaluation
Bayesian method
Bernoulli data
Data from multiple sources
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