Estimation of components reliability in a parallel system using masked system life data

Abstract

In this paper we estimate the reliability of the individual components that belong to a parallel system using masked-system life test data. In particular, we compute the maximum likelihood and Bayes estimates of component reliabilities. The considered system consists of J independent components having non-identical complementary exponential lifetime distributions. It is assumed for Bayes estimates that the unknown parameters are independent random variables having symmetrical triangle probability density functions. The approaches are illustrated with a two-component parallel system. A numerical simulation study is introduced to show how one can use the present approaches to compute these estimations for a practical problem. Also in the numerical simulation study a comparison between Bayes and maximum likelihood estimates is introduced.