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

Annals of operations research, 2022-04, Vol.311 (1), p.195-209 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2019 ;COPYRIGHT 2022 Springer ;Annals of Operations Research is a copyright of Springer, (2019). All Rights Reserved. ;Springer Science+Business Media, LLC, part of Springer Nature 2019. ;ISSN: 0254-5330 ;EISSN: 1572-9338 ;DOI: 10.1007/s10479-019-03247-6

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Title:
Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability
Author: Li, Yan-Feng ; Huang, Hong-Zhong ; Mi, Jinhua ; Peng, Weiwen ; Han, Xiaomeng
Subjects: Bayesian analysis ; Boring machines ; Business and Management ; Combinatorics ; Common cause failures ; Complex systems ; Computer numerical control ; Engineering ; Failure ; Fault diagnosis ; Feasibility studies ; Feed systems ; Fuzzy algorithms ; Fuzzy logic ; Fuzzy sets ; Fuzzy systems ; Mathematical models ; Methods ; 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
Is Part Of: Annals of operations research, 2022-04, Vol.311 (1), p.195-209
Description: 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.
Publisher: New York: Springer US
Language: English
Identifier: ISSN: 0254-5330
EISSN: 1572-9338
DOI: 10.1007/s10479-019-03247-6
Source: AUTh Library subscriptions: ProQuest Central

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

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