This paper investigates the selective maintenance o systems that perform multi-mission in succession. Selective maintenance is performed on systems with limited break time to improve the success of the next mission. I...This paper investigates the selective maintenance o systems that perform multi-mission in succession. Selective maintenance is performed on systems with limited break time to improve the success of the next mission. In general, the duration of the mission is stochastic. However, existing studies rarely take into account system availability and the repairpersons with different skill levels. To solve this problem, a new multi-mission selective maintenance and repairpersons assignment model with stochastic duration of the mission are developed. To maximize the minimum phase-mission reliability while meeting the minimum system availability, the model is transformed into an optimization problem subject to limited maintenance resources. The optimization is then realized using an analytical method based on a self-programming function and a Monte Carlo simulation method, respectively. Finally, the validity of the model and solution method approaches are verified by numerical arithmetic examples. Comparative and sensitivity analyses are made to provide proven recommendations for decision-makers.展开更多
This paper presents a joint optimization policy of preventive maintenance(PM)and spare ordering for single-unit systems,which deteriorate subject to the delay-time concept with three deterioration stages.PM activities...This paper presents a joint optimization policy of preventive maintenance(PM)and spare ordering for single-unit systems,which deteriorate subject to the delay-time concept with three deterioration stages.PM activities that combine a non-periodic inspection scheme with age-replacement are implemented.When the system is detected to be in the minor defective stage by an inspection for the first time,place an order and shorten the inspection interval.If the system has deteriorated to a severe defective stage,it is either repaired imperfectly or replaced by a new spare.However,an immediate replacement is required once the system fails,the maximal number of imperfect maintenance(IPM)is satisfied or its age reaches to a pre-specified threshold.In consideration of the spare’s availability as needed,there are three types of decisions,i.e.,an immediate or a delayed replacement by a regular ordered spare,an immediate replacement by an expedited ordered spare with a relative higher cost.Then,some mutually independent and exclusive renewal events at the end of a renewal cycle are discussed,and the optimization model of such a joint policy is further developed by minimizing the long-run expected cost rate to find the optimal inspection and age-replacement intervals,and the maximum number of IPM.A Monte-Carlo based integration method is also designed to solve the proposed model.Finally,a numerical example is given to illustrate the proposed joint optimization policy and the performance of the Monte-Carlo based integration method.展开更多
针对现有故障预测与健康管理(prognostics and health management,PHM)系统难以给出实时、动态健康管理决策结果的问题,综合考虑不完善维修、多资源约束(人力、时间、成本等)、备件订购、任务规划等因素,基于选择性维修理论,建立了动态...针对现有故障预测与健康管理(prognostics and health management,PHM)系统难以给出实时、动态健康管理决策结果的问题,综合考虑不完善维修、多资源约束(人力、时间、成本等)、备件订购、任务规划等因素,基于选择性维修理论,建立了动态健康管理决策模型,得到了最优方案,包括部件最优维修对策、维修任务分配、备件订购数量、最优任务规划等。最后,结合算例,分析了维修人员数量、备件数量、任务规划等因素对动态健康管理决策结果的影响,验证了所提模型的有效性,对于指导装备健康管理实践、提升保障质效具有重要的意义。展开更多
文摘This paper investigates the selective maintenance o systems that perform multi-mission in succession. Selective maintenance is performed on systems with limited break time to improve the success of the next mission. In general, the duration of the mission is stochastic. However, existing studies rarely take into account system availability and the repairpersons with different skill levels. To solve this problem, a new multi-mission selective maintenance and repairpersons assignment model with stochastic duration of the mission are developed. To maximize the minimum phase-mission reliability while meeting the minimum system availability, the model is transformed into an optimization problem subject to limited maintenance resources. The optimization is then realized using an analytical method based on a self-programming function and a Monte Carlo simulation method, respectively. Finally, the validity of the model and solution method approaches are verified by numerical arithmetic examples. Comparative and sensitivity analyses are made to provide proven recommendations for decision-makers.
基金supported by the Naitonal Natural Science Foundation of China(71701038)China Ministry of Education Humanities and Social Sciences Research Youth Fund Project(16YJC630174)+2 种基金the Natural Science Foundation of Hebei Province(G2019501074)the Fundamental Research Funds for the Central Universities(N2123019)the Postgraduate Funding Project of PLA(JY2020B085).
文摘This paper presents a joint optimization policy of preventive maintenance(PM)and spare ordering for single-unit systems,which deteriorate subject to the delay-time concept with three deterioration stages.PM activities that combine a non-periodic inspection scheme with age-replacement are implemented.When the system is detected to be in the minor defective stage by an inspection for the first time,place an order and shorten the inspection interval.If the system has deteriorated to a severe defective stage,it is either repaired imperfectly or replaced by a new spare.However,an immediate replacement is required once the system fails,the maximal number of imperfect maintenance(IPM)is satisfied or its age reaches to a pre-specified threshold.In consideration of the spare’s availability as needed,there are three types of decisions,i.e.,an immediate or a delayed replacement by a regular ordered spare,an immediate replacement by an expedited ordered spare with a relative higher cost.Then,some mutually independent and exclusive renewal events at the end of a renewal cycle are discussed,and the optimization model of such a joint policy is further developed by minimizing the long-run expected cost rate to find the optimal inspection and age-replacement intervals,and the maximum number of IPM.A Monte-Carlo based integration method is also designed to solve the proposed model.Finally,a numerical example is given to illustrate the proposed joint optimization policy and the performance of the Monte-Carlo based integration method.
文摘针对现有故障预测与健康管理(prognostics and health management,PHM)系统难以给出实时、动态健康管理决策结果的问题,综合考虑不完善维修、多资源约束(人力、时间、成本等)、备件订购、任务规划等因素,基于选择性维修理论,建立了动态健康管理决策模型,得到了最优方案,包括部件最优维修对策、维修任务分配、备件订购数量、最优任务规划等。最后,结合算例,分析了维修人员数量、备件数量、任务规划等因素对动态健康管理决策结果的影响,验证了所提模型的有效性,对于指导装备健康管理实践、提升保障质效具有重要的意义。
