Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability

• Published in: Annals of operations research Vol. 311; no. 1; pp. 195 - 209
• Main Authors: Li, Yan-Feng, Huang, Hong-Zhong, Mi, Jinhua, Peng, Weiwen, Han, Xiaomeng
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2022; Springer; Springer Nature B.V
• Subjects: Bayesian analysis; Boring machines; Business and Management; Combinatorics; Common cause failures; Complex systems; Engineering; Failure; Fault diagnosis; Feasibility studies; Feed systems; Fuzzy algorithms; Fuzzy logic; Fuzzy sets; Fuzzy systems; Mathematical models; Methods; Numerical controls; Operations research; Operations Research/Decision Theory; Probability; Quantitative analysis; Random variables; Reliability (Engineering); Reliability analysis; S.I.: Reliability Modeling with Applications Based on Big Data; Set theory; System reliability; Theory of Computation; Uncertainty; China; Reliability analysis; Fuzzy probability; Common cause failures; Multi-state systems; Bayesian network
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-019-03247-6

Multi-state components, common cause failures (CCFs) and data uncertainty are the general problems for reliability analysis of complex engineering systems. In this paper, a method incorporating fuzzy probability and Bayesian network (BN) into multi-state systems (MSSs) with CCFs is proposed. In particular, basic theories of multi-state BN and fuzzy probability are developed. Moreover, a model integrating CCFs with BN has also been illustrated. In order to incorporate fuzzy probability into MSSs reliability evaluation considering common parent node generated by CCFs, fuzzy probability has to be translated into accurate probability through defuzzification and normalization methods which are both elaborated. In addition, quantitative analysis based on BN is carried out. In this paper, feed system of boring spindle in computer numerical control machine is analyzed as an example to validate the feasibility of the proposed method. It can improve the ability of BN on reliability evaluation of complex system with uncertainty issues.