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Imprecise system reliability and component importance based on survival signature

Feng, G.; Patelli, E.; Beer, M.; Coolen, F.P.A.

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Authors

G. Feng

E. Patelli

M. Beer



Abstract

The concept of the survival signature has recently attracted increasing attention for performing reliability analysis on systems with multiple types of components. It opens a new pathway for a structured approach with high computational efficiency based on a complete probabilistic description of the system. In practical applications, however, some of the parameters of the system might not be defined completely due to limited data, which implies the need to take imprecisions of component specifications into account. This paper presents a methodology to include explicitly the imprecision, which leads to upper and lower bounds of the survival function of the system. In addition, the approach introduces novel and efficient component importance measures. By implementing relative importance index of each component without or with imprecision, the most critical component in the system can be identified depending on the service time of the system. Simulation method based on survival signature is introduced to deal with imprecision within components, which is precise and efficient. Numerical example is presented to show the applicability of the approach for systems.

Citation

Feng, G., Patelli, E., Beer, M., & Coolen, F. (2016). Imprecise system reliability and component importance based on survival signature. Reliability Engineering & System Safety, 150, 116-125. https://doi.org/10.1016/j.ress.2016.01.019

Journal Article Type Article
Acceptance Date Jan 27, 2016
Online Publication Date Feb 6, 2016
Publication Date Jun 1, 2016
Deposit Date Feb 18, 2016
Publicly Available Date Mar 28, 2024
Journal Reliability Engineering and System Safety
Print ISSN 0951-8320
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 150
Pages 116-125
DOI https://doi.org/10.1016/j.ress.2016.01.019
Keywords Imprecision, Survival signature, System reliability, Component importance, Sensitivity analysis.

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