Classical and bayesian estimation of reliability in multicomponent stress-strength model based on weibull distribution

Abstract

In this study, we consider a multicomponent system which has k independent and identical strength components X<inf>1</inf>,….,X<inf>k</inf> and each component is exposed to a common random stress Y when the underlying distributions are Weibull. The system is regarded as operating only if at least s out of k (1 ? s ? k) strength variables exceeds the random stress. We estimate the reliability of the system by using frequentist and Bayesian approaches. The Bayes estimate of the reliability has been developed by using Lindley’s approximation and the Markov Chain Monte Carlo methods due to the lack of explicit forms. The asymptotic confidence interval and the highest probability density credible interval are constructed for the reliability. The comparison of the reliability estimators is made in terms of the estimated risks by the Monte Carlo simulations. © 2021 Elsevier B.V., All rights reserved.