Miaoxin Chang
New reliability model for complex systems based on stochastic processes and survival signature
Chang, Miaoxin; Huang, Xianzhen; Coolen, F.P.A.; Coolen-Maturi, Tahani
Authors
Xianzhen Huang
Professor Frank Coolen frank.coolen@durham.ac.uk
Professor
Dr Tahani Coolen-Maturi tahani.maturi@durham.ac.uk
Professor
Abstract
For systems with complicated structures, reliability analysis based on survival signature has been carried out by modelling time-to-failure data with specific distributions. However, for highly reliable systems, only little or no failure data may be available. To enable reliability analysis without failure data, a new generalised reliability method is proposed for complex systems, based on the survival signature and using stochastic processesto model degradation. The combination of the survival signature and stochastic processes enables the proposed method to be applied to complex systems with different structures and stochastically degrading components. First, system reliability is analysed based on the survival signature and a generalised stochastic process. Then, component reliability analysis based on the generalised stochastic process is introduced using Wiener and Gamma processes. Finally, the approach presented in this paper is illustrated using two numerical examples, and the estimation results are compared with those calculated using failure time distribution functions.
Citation
Chang, M., Huang, X., Coolen, F., & Coolen-Maturi, T. (2023). New reliability model for complex systems based on stochastic processes and survival signature. European Journal of Operational Research, 309(3), 1349-1364. https://doi.org/10.1016/j.ejor.2023.02.027
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 18, 2023 |
Online Publication Date | Feb 23, 2023 |
Publication Date | Sep 16, 2023 |
Deposit Date | Feb 18, 2023 |
Publicly Available Date | Feb 24, 2025 |
Journal | European Journal of Operational Research |
Print ISSN | 0377-2217 |
Electronic ISSN | 1872-6860 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 309 |
Issue | 3 |
Pages | 1349-1364 |
DOI | https://doi.org/10.1016/j.ejor.2023.02.027 |
Public URL | https://durham-repository.worktribe.com/output/1180907 |
Files
Accepted Journal Article
(2.9 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by-nc-nd/4.0/
Copyright Statement
© 2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://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
Combining biomarkers to improve diagnostic accuracy using the overlap coefficient
(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