Application of Bayesian Methods for Age-dependent Reliability Analysis

TL;DR

This paper introduces a Bayesian methodology for age-dependent reliability analysis, enabling practitioners to incorporate prior knowledge and evolving beliefs about system failure rates over time, improving risk assessment of aging systems.

Contribution

It presents a comprehensive step-by-step Bayesian approach for analyzing aging systems, including model verification and Bayesian model averaging as a universal uncertainty tool.

Findings

Bayesian methods effectively model age-dependent failure rates.

Bayesian model averaging enhances reliability assessment accuracy.

The methodology offers a practical framework for practitioners.

Abstract

In this paper authors present a general methodology for age dependent reliability analysis of degrading or ageing systems, structures and components.The methodology is based on Bayesian methods and inference, its ability to incorporate prior information and on idea that ageing can be thought as age dependent change of believes about reliability parameters, when change of belief occurs not just due to new failure data or other information which becomes available in time, but also it continuously changes due to flow of time and beliefs evolution. The main objective of this paper is to present the clear way of how Bayesian methods can be applied by practitioners to deal with risk and reliability analysis considering ageing phenomena. The methodology describes step by step failure rate analysis of ageing systems: from the Bayesian model building to its verification and generalization with Bayesian model averaging which, as authors suggest in this paper, could serve as alternative for various goodness of fit assessment tools and as universal tool to cope with various sources of uncertainty.