Redundancy Allocation Optimization for Multistate Systems With Failure Interactions Using Semi-Markov Process
Adding redundancy is a widely used method in engineering to improve the system reliability. How to add redundancy, (i.e., to meet the reliability requirement with the minimum cost), is an interesting topic in system design. Traditionally, the optimal redundancy allocation scheme is obtained under two simplified assumptions, i.e., binary states of each component and no failure dependency between components. The binary-state assumption assumes that each component and the entire system can only have two states: fully operational and completely failed. The failure independency assumption assumes no failure interaction between components, i.e., one component failure will not affect the failure process of other components. Although those two assumptions can simplify the analysis, they may lead to inaccurate reliability predictions and thus results in doubtful and misleading redundancy allocation scheme which in fact may not meet the reliability requirement. This work proposes a method to obtain the optimal redundancy allocation scheme by using the Semi-Markov process and optimization techniques without those two simplified assumptions. The target system is a type of commonly-seen system having multiple states and failure interactions. The target system contains a main subsystem providing the required output and an auxiliary subsystem helping the main subsystem function normally, such as the rotating subsystem and the lubricating subsystem, the computer mother board and the fan, and so on. A case study of a shipboard power electronic cabinet demonstrates the applicability of the proposed approach.
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