A nonparametric Bayesian network approach to assessing system reliability at early design stages

Dongjin Lee and Rong Pan

Reliability Engineering and System Safety, 2018, vol. 171, issue C, 57-66

Abstract: It is important to predict a system’s reliability at its early design stages because modifying design to improve reliability and maintainability at a later time in the system’s lifecycle will be costly and, oftentimes, impossible. However, this early prediction is challenging because of the lack of reliability data and the incomplete knowledge of a complex system’s reliability structure. To tackle this problem, this paper presents a nonparametric Bayesian network approach. Employing nonparametric Bayesian network, the limitation of discrete Bayesian network can be overcome, and it can be used as a useful tool for decision support. The proposed methodology is applied to a case study to demonstrate its prognostic and diagnostic capabilities.

Keywords: Product design; Complex system; Graphical models; Copula; Reliability prediction (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:171:y:2018:i:c:p:57-66

DOI: 10.1016/j.ress.2017.11.009

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