Abstract: In the process of outsourcing strategy for complex equipment maintenance,there are the problems of considering only one party's interests or the unclear characteristics of third-party maintenance.To solve these problems,a multi-stage and periodical preventive maintenance strategy was proposed,which could maximize the satisfaction of equipment users and the profit of maintenance outsourcing service contractors.The dynamic service age decreasing factor was introduced to optimize the failure rate change rule.The number of preventive maintenance times,maintenance intervals and the average failure response time for maintenance service contractors were taken as decision variables,and the service contractor profit model and equipment user satisfaction model were constructed.The fast elitist Non-dominated Sorting Genetic Algorithm(NSGAII)was used to solve the multi-objective optimal scheme under different segments and compared.The results showed that the two-stage preventive maintenance strategy obtained the optimal scheme with better quality.Then,the particle swarm optimization algorithm was used to find the single-objective optimal scheme corresponding to two-stage maintenance and compared it with the multi-objective optimal scheme to verify the superiority and practicability of the multi-objective maintenance outsourcing model.

Key words: maintenance outsourcing, multi-stage and periodical preventive maintenance, satisfaction of equipment users, average failure response time, multi-objective optimization

摘要： 针对复杂设备维护外包策略制定过程中,仅考虑一方利益或第三方维护特点表现不明问题,提出了同时使设备使用商满意度最高和维护外包服务承包商利润最大的分阶段等周期预防性维护策略。首先,引入动态役龄递减因子来优化故障率变化规则;其次,以每个阶段的预防性维护次数和维护间隔以及维护外包服务承包商的平均响应时间为决策变量,构建了服务承包商利润模型和设备使用商满意度模型;最后,用NSGAII算法求解不同分段下的多目标最优方案并进行比较,得出两阶段预防性维护策略所得最优方案质量更佳;使用粒子群算法求出两阶段维护对应的单目标最优方案并与多目标最优方案进行对比,以验证多目标维护外包模型的优越性和实用性。

关键词: 维护外包, 分阶段等周期预防性维护, 设备使用商满意度, 平均故障响应时间, 多目标优化