Reliability Estimations of Components in Series System Using Type-II Censored and Masked Life Data

This paper introduces estimations of reliabilities index for Rayleigh components in a series system using Type-II censored and masked system life data. We derive the Maximum likelihood estimation (MLE) of the unknown parameters for Rayleigh components and reliabilities index. In view of the limitation of MLE under complete masked case, we employ the Bayes approach. Bayes estimations of the Rayleigh parameters and reliabilities index are obtained under the Square Error loss function. Also, a numerical example is given by means of the Monte-Carlo simulation for comparing the effects of the maximum likelihood estimation and the Bayes estimation, which shows that the Bayes estimation is better than MLE.