Application of Bayesian Methods for Age-Dependent Reliability Analysis
Article first published online: 16 JAN 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Quality and Reliability Engineering International
Volume 30, Issue 1, pages 121–132, February 2014
How to Cite
Alzbutas, R. and Iešmantas, T. (2014), Application of Bayesian Methods for Age-Dependent Reliability Analysis. Qual. Reliab. Engng. Int., 30: 121–132. doi: 10.1002/qre.1482
- Issue published online: 27 JAN 2014
- Article first published online: 16 JAN 2013
- Manuscript Accepted: 16 OCT 2012
- Manuscript Revised: 17 AUG 2012
- Manuscript Received: 29 SEP 2011
- age-dependent reliability;
- bayesian methods;
- reliability data;
- failure rate;
In this article, the authors present a general methodology for age-dependent reliability analysis of degrading or ageing components, structures and systems. The methodology is based on Bayesian methods and inference—its ability to incorporate prior information and on ideas that ageing can be thought of as age-dependent change of beliefs about reliability parameters (mainly failure rate), when change of belief occurs not only because new failure data or other information becomes available with time but also because it continuously changes due to the flow of time and the evolution of beliefs.
The main objective of this article is to present a clear way of how practitioners can apply Bayesian methods to deal with risk and reliability analysis considering ageing phenomena. The methodology describes step-by-step failure rate analysis of ageing components: from the Bayesian model building to its verification and generalization with Bayesian model averaging, which as the authors suggest in this article, could serve as an alternative for various goodness-of-fit assessment tools and as a universal tool to cope with various sources of uncertainty.
The proposed methodology is able to deal with sparse and rare failure events, as is the case in electrical components, piping systems and various other systems with high reliability. In a case study of electrical instrumentation and control components, the proposed methodology was applied to analyse age-dependent failure rates together with the treatment of uncertainty due to age-dependent model selection. Copyright © 2013 John Wiley & Sons, Ltd.