考虑不完美维护的视情维修和备件订购联合策略优化

针对现有研究多关注维修策略优化而忽略备件采购决策问题，本文对单部件系统提出不完美维护下基于剩余寿命预测的视情维修和备件订购联合策略.采用控制限维修策略判断是否执行最小维修、预防性维护或故障更换，当系统退化达到预防性维护阈值时进行不完美维护，同时预测系统剩余寿命并引入预防性更换阈值和订购阈值，以决定是否执行预防性更换或者订购备件.综合考虑系统退化状态和备件状态，分析可能的更新事件进而计算各事件发生概率，并利用更新报酬理论构建费用-时间率联合决策模型.最后，设计离散事件仿真算法通过算例分析对状态检测周期、预防性维护阈值进行优化，验证模型和算法的有效性.

Optimization of Joint Policy of Condition-Based Maintenance and Spare Part Ordering Considering Imperfect Maintenance

Considering most studies focused on the maintenance policy optimization but neglected the ordering decision of spare parts， a joint policy of condition-based maintenance and spare part ordering under imperfect maintenance for single-component systems based on the remaining useful life(RUL)was proposed. The control limit policy was used to determine whether to perform minimal maintenance， preventive maintenance or corrective replacement. When the system degradation reaches the preventive maintenance threshold， the imperfect maintenance was carried out. Simultaneously， the RUL was predicted and the preventive replacement threshold and ordering threshold were introduced to decide whether to carry out preventive replacement or order spare parts. Considering the degradation state of systems and the state of spare parts， all the possible update events were analyzed to calculate the occurrence probability of each event， and the cost-time rate model of such a joint policy was constructed by using the renewal award theorem. Finally， the discrete event simulation algorithm was designed to optimize the detection interval and the imperfect maintenance threshold in a numerical example， and the effectiveness of the proposed model and algorithm was verified as well.