An efficient phased-mission reliability model considering dynamic k-out-of-n subsystem redundancy

In this article, an efficient method is proposed for exact reliability evaluation of a special class of Phased-Mission Systems (PMSs) containing multiple k-out-of-n subsystems, each of which has multiple identical and non-repairable components. A PMS performs missions involving multiple, consecutive, and non-overlapping phases of operations. In each phase, the system has to accomplish a specific task and may be subject to different stresses. Thus, the configuration of each subsystem can change from phase to phase, including its active and inactive status, redundancy type, and minimum required working components. If any one of the required (active) subsystems is failed in a phase, the system is considered to be failed in that phase. The proposed method for accurate reliability analysis of PMS considers statistical dependencies of component states across the phases, time-varying and phase-dependent failure rates, and associated cumulative damage effects. Based on conditional probabilities and an efficient recursive formula to compute these probabilities, the proposed method has both computational time and memory requirements linear to the system size. Medium-scale and large-scale systems are analyzed to demonstrate high efficiency of the proposed method.