Feng, G. and Patelli, E. and Beer, M. and Coolen, F.P.A. (2016) 'Imprecise system reliability and component importance based on survival signature.', Reliability engineering & system safety., 150 . pp. 116-125.
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.
Item Type: | Article |
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Keywords: | Imprecision, Survival signature, System reliability, Component importance, Sensitivity analysis. |
Full text: | (AM) Accepted Manuscript Available under License - Creative Commons Attribution Non-commercial No Derivatives. Download PDF (484Kb) |
Status: | Peer-reviewed |
Publisher Web site: | http://dx.doi.org/10.1016/j.ress.2016.01.019 |
Publisher statement: | © 2016 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Date accepted: | 27 January 2016 |
Date deposited: | 22 February 2016 |
Date of first online publication: | 06 February 2016 |
Date first made open access: | 06 February 2017 |
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