Abstract: Aiming at the periodic condition-based repair-by-replacement and continuous review of repairable critical components,the joint optimization policy of (S,s) type spare provisioning was proposed.Based on the consideration of definite maintenance time and imperfect maintenance effect,the relationship between maintenance capacities,maintenance policy and inventory strategy was analyzed.The simulation optimization model with testing period,preventive maintenance threshold,inventory parameter and maintenance capacities as the decision variable and minimum average cost rate in infinite time range as the target was established.The discrete event simulation and genetic algorithm were combined to solve this model.Simulation results showed that the combination of repair-by-replacement with continuous reviewed spare provisioning policy could reduce system down,increase system availability and decrease maintenance cost.The results of sensitivity analysis showed that the trades-off among maintenance policy,spare parts inventories and repair capacity were existed.

Key words: condition-based repair-by-replacement, (S,s) type spare provisioning policy, repair capacity, average cost rate, simulation, optimization

摘要： 针对可修复杂关键组件提出周期性视情更换式维修与连续检查的(S,s)备件订购联合优化策略。在考虑确定的维修时间和非完美维修效果的基础上,分析了维修能力与维修策略、库存策略之间的权衡关系,建立了以检测周期、预防维修阈值、库存参数及维修能力为决策变量,以单位设备无限时间范围内的平均费用率最小为目标的仿真优化模型。采用离散事件仿真和遗传算法相结合的方法对模型进行求解。仿真结果表明,更换式维修和连续检查的备件订购策略相结合可以减少系统停机、提高系统可用度、降低维修成本。灵敏度分析结果表明,维修策略、备件策略和维修能力之间存在一定的权衡。

关键词: 视情更换维修, (S, s)备件订购策略, 维修能力, 平均费用率, 仿真, 优化