Abstract
•A heterogenous system must supply a demand during a mission time.•Operating components may be replaced by standby components.•Replaced components can undergo maintenance and be reactivated.•Mission success probability is obtained for any operation/maintenance schedule.•The mission losses are minimized by finding the optimal schedule.
This paper contributes by modeling a new class of repairable, dynamic m-out-of-n standby systems operating in random shock environments. Operating components are exposed to a common shock process and can fail due to external shocks and/or internal deterioration, causing the failure of the entire mission. Therefore, it is pivotal to implement an operation and maintenance schedule (OMS), according to which any operating component may be preventively replaced by a standby component to undergo perfect maintenance during the mission. Due to heterogeneity of system components, different OMSs incur different expected mission cost (EMC) and mission success probability (MSP). We formulate a new optimization problem to determine the optimal OMS that minimizes the EMC while satisfying a certain level of MSP. The solution methodology encompasses a new recursive procedure to evaluate MSP and the realization of genetic algorithm. A case study of a chemical reactor cooling system is conducted to showcase the proposed model and study the effects of component heterogeneity as well as several key model parameters on the system performance. The mission cost sensitivity analysis is also demonstrated, providing insights on the most cost-effective component performance or shock resistance improvement. The proposed model extends the OMS study of standby systems in literature from non-shock to shock operating environments.