System reliability assessment with multilevel information using the Bayesian melding method

Jian Guo, (Steven) Li, Zhaojun and (Judy) Jin, Jionghua

Reliability Engineering and System Safety, 2018, vol. 170, issue C, 146-158

Abstract: This paper investigates the Bayesian melding method (BMM) for system reliability analysis by effectively integrating various available sources of expert knowledge and data at both subsystem and system levels. The integration of multiple priors is investigated under both linear and geometric pooling methods. The aggregated system prior distributions using various pooling methods including the BMM are evaluated and compared. Based on these integrated and updated prior distributions and three scenarios of data availability from a system and/or subsystems, methods for posterior system reliability inference are proposed. Computational challenges for posterior inferences using the sophisticated BMM are addressed using the adaptive sampling importance re-sampling (SIR) method. A numerical example with simulation results illustrates the applications of the proposed methods and provides insights for system reliability analysis using multilevel information.

Keywords: System reliability; Bayesian inference; Bayesian melding method; Multilevel information; Non-informative and informative priors; Markov Chain Monte Carlo; Adaptive sampling importance re-sampling (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:170:y:2018:i:c:p:146-158

DOI: 10.1016/j.ress.2017.09.020

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