Dr Louis Aslett louis.aslett@durham.ac.uk
Associate Professor
Dr Louis Aslett louis.aslett@durham.ac.uk
Associate Professor
Professor Frank Coolen frank.coolen@durham.ac.uk
Professor
S.P. Wilson
The concept of survival signature has recently been introduced as an alternative to the signature for reliability quantification of systems. While these two concepts are closely related for systems consisting of a single type of component, the survival signature is also suitable for systems with multiple types of component, which is not the case for the signature. This also enables the use of the survival signature for reliability of networks. In this article, we present the use of the survival signature for reliability quantification of systems and networks from a Bayesian perspective. We assume that data are available on tested components that are exchangeable with those in the actual system or network of interest. These data consist of failure times and possibly right-censoring times. We present both a nonparametric and parametric approach.
Aslett, L., Coolen, F., & Wilson, S. (2015). Bayesian inference for reliability of systems and networks using the survival signature. Risk Analysis, 35(9), 1640-1651. https://doi.org/10.1111/risa.12228
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 1, 2014 |
Online Publication Date | Jun 11, 2014 |
Publication Date | Sep 1, 2015 |
Deposit Date | Sep 29, 2015 |
Publicly Available Date | Jun 11, 2016 |
Journal | Risk Analysis |
Print ISSN | 0272-4332 |
Electronic ISSN | 1539-6924 |
Publisher | Wiley |
Peer Reviewed | Peer Reviewed |
Volume | 35 |
Issue | 9 |
Pages | 1640-1651 |
DOI | https://doi.org/10.1111/risa.12228 |
Keywords | Bayesian methods, Networks, Nonparametrics, Parametric lifetime distributions, System reliability. |
Public URL | https://durham-repository.worktribe.com/output/1398952 |
Accepted Journal Article
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Copyright Statement
This is the accepted version of the following article: Aslett, L. J. M., Coolen, F. P. A. and Wilson, S. P. (2015), Bayesian Inference for Reliability of Systems and Networks Using the Survival Signature. Risk Analysis, 35(9): 1640-1651., which has been published in final form at http://dx.doi.org/10.1111/risa.12228. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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