An algorithmic approach for the dynamic reliability analysis of non-repairable multi-state weighted <i>k</i>-out-of-<i>n</i>:G system

Abstract

In this paper, we study a multi-state weighted k-out-of-n:G system model in a dynamic setup. In particular, we study the random time spent by the system with a minimum performance level of k. Our method is based on ordering the lifetimes of the system's components in different state subsets. Using this ordering along with the Monte-Carlo simulation algorithm, we obtain estimates of the mean and survival function of the time spent by the system in state k or above. We present illustrative computational results when the degradation in the components follows a Markov process. (C) 2014 Elsevier Ltd. All rights reserved.