A Stochastic Approach for Evaluating the Reliability of Multi-stated Phased-Mission Systems with Imperfect Fault Coverage

A phased-mission system (PMS) is usually consisting of a number of non-overlapping phases, and the phases should be completed sequentially to achieve a successful mission. In practice, imperfect fault coverage (IPC) plays an important effect on the system reliability. In this paper, stochastic multi-value (SMV) models are proposed to predict the system reliability of a multi-stated PMS consisting of non-repairable components; during the evaluating process, three different imperfect fault coverage conditions (listed as Element Level Coverage, Fault Level Coverage, and Performance dependent Coverage) are incorporated. In the stochastic analysis, performance values and their corresponding probabilities of elements are simultaneously encoded in random sequences consisting of permutation of fixed numbers of multi-value numbers. Thus, the types of components' failure distributions are not limited for the proposed approach. By feeding the obtained stochastic sequences into the proposed system structure, reliability of a PMS can be efficiently determined which avoids cumbersome analyzing process. The efficiency of the SMV approach is verified by several case studies compared to universal generating function (UGF).