J. Qin
Survival signature for reliability evaluation of a multi-state system with multi-state components
Qin, J.; Coolen, F.P.A.
Abstract
Survival signature technology has recently attracted increasing attention for its merits on quantifying reliability of systems with multiple types of components. In order to implement reliability evaluation of multi-state system (MSS), computing methods of survival signature are studied for reliability analysis of several different systems in this paper. For an MSS consisting of multi-state components, its survival signature can be developed based on the different state definition of system. For the binary-state system with multi-state components, its survival signature is based on the generalization of survival signature for multi-state components. For a real life engineering MSS consisting of subsystems, the computing method of survival signature of system has also been derived based on the survival signature of subsystems and mapping of subsystems’ states to system's states. This enables consecutive application of the new method to substantial realistic MSS, with no theoretical limit on the size of the systems. Examples illustrate the applicability of the analysis approach for systems reliability.
Citation
Qin, J., & Coolen, F. (2022). Survival signature for reliability evaluation of a multi-state system with multi-state components. Reliability Engineering & System Safety, 218(Part A), Article 108129. https://doi.org/10.1016/j.ress.2021.108129
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 7, 2021 |
Online Publication Date | Oct 13, 2021 |
Publication Date | 2022-02 |
Deposit Date | Oct 11, 2021 |
Publicly Available Date | Oct 13, 2022 |
Journal | Reliability Engineering and System Safety |
Print ISSN | 0951-8320 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 218 |
Issue | Part A |
Article Number | 108129 |
DOI | https://doi.org/10.1016/j.ress.2021.108129 |
Public URL | https://durham-repository.worktribe.com/output/1236744 |
Files
Accepted Journal Article
(9.4 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by-nc-nd/4.0/
Copyright Statement
© 2021 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Parametric Predictive Bootstrap Method for the Reproducibility of Hypothesis Tests
(2025)
Journal Article
Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data
(2024)
Journal Article
Nonparametric Predictive Inference for Discrete Lifetime Data
(2024)
Journal Article
Reproducibility of estimates based on randomised response methods
(2024)
Journal Article
A Bayesian Imprecise Classification method that weights instances using the error costs
(2024)
Journal Article