Abstract
It is a common practice to use product storage to enhance the system operation efficiency and mission success probability (MSP). However, very few studies in the reliability literature considered the storage component and none of the existing models addressed the optimal loading problem. This paper contributes by analyzing and maximizing the MSP for repairable systems with load-dependent performance and product storage of limited capacity. The storage is used to cumulate surplus product when the system performance exceeds the demand and compensate the deficiency when the system has insufficient performance or is failed and under repair. Both time-to-failure and time-to-repair are random, following arbitrary distributions. A numerical MSP evaluation algorithm is put forward for the considered repairable system with specified demand and mission time. As another contribution, the optimal loading problem is solved to determine the loading policy that maximizes the MSP. A case study on a repairable pump system in a chemical reactor is provided to examine the influences of storage capacity and initial storage filling on the MSP and the optimized loading policy.
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