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Predictive inference for system reliability after common-cause component failures
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DOI：10.1016/j.ress.2014.11.005.png)
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This paper presents nonparametric predictive inference for system reliability following common-cause failures of components. It is assumed that a single failure event may lead to simultaneous failure of multiple components. Data consist of frequencies of such events involving particular numbers of components. These data are used to predict the number of components that will fail at the next failure event. The effect of failure of one or more components on the system reliability is taken into account through the system's survival signature. The predictive performance of the approach, in which uncertainty is quantified using lower and upper probabilities, is analysed with the use of ROC curves. While this approach is presented for a basic scenario of a system consisting of only a single type of components and without consideration of failure behaviour over time, it provides many opportunities for more general modelling and inference, these are briefly discussed together with the related research challenges. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
Common-cause failures
Lower and upper probabilities
Nonparametric predictive inference
ROC curves
Survival signature
System reliability
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11
论文数:
9.0K
被引数:
4.2W
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A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models在共因故障模型中对认知不确定性建模的鲁棒贝叶斯方法OAAI
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