系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (7): 1560-1567.doi: 10.3969/j.issn.1001-506X.2019.07.17

• 系统工程 • 上一篇    下一篇

装备视情维修与备件库存联合优化决策

逯程1,徐廷学1,王虹2   

  1. 1. 海军航空大学岸防兵学院, 山东 烟台 264001;
    2. 联合参谋部第55研究所, 北京 100094
  • 出版日期:2019-06-28 发布日期:2019-07-09

Joint optimization decision of equipment condition based maintenance and spare parts inventory

LU Cheng1,XU Tingxue1,WANG Hong2   

  1. 1. Coastal Defense College, Naval Aviation University, Yantai 264001, China; 2. The 55th Institute, Joint Staff Department, Beijing 100094, China
  • Online:2019-06-28 Published:2019-07-09

摘要: 研究周期检测条件下装备视情维修与备件库存的联合优化问题。针对相同多部件系统,根据系统的退化状态和备件库存状态确定维修需求,建立了以系统检测周期、预防维修阈值和备件安全库存阈值为决策变量,以平均费用率最低为目标的联合维修决策模型。在模型求解过程中,利用退化状态空间划分法分析各决策点的维修需求,在系统的联合概率密度求解的基础上,确定维修组合概率和备件库存状态概率。最后,通过末制导雷达某部件系统的实例计算,验证了优化方法的有效性,另外还通过灵敏度分析,探讨了相关参数对模型的影响。

关键词: 视情维修, 备件库存, 联合优化, 多部件系统, 费用率

Abstract: The joint optimization of equipment condition based maintenance and spare parts inventory under periodic detection is carried out. For the same multi-unit system, the maintenance requirement is determined according to the deterioration state of the whole system and the spare parts inventory state, and a joint maintenance decision model with the system detection cycle, the preventive maintenance threshold and the safety stock threshold of spare parts as decision variables and the average cost rate as the target is set up. In the process of solving the model, the degenerate state space division method is used to analyze the maintenance requirements of each decision point. On the basis of the joint probability density solution of the system, the probability of maintenance combination and the spare parts inventory state is determined. Finally, the effectiveness of the optimization method is verified by an example of multi-unit system of the terminal guidance radar, and the influence of the related parameters on the model is also discussed by sensitivity analysis.


Key words: condition based maintenance, spare parts inventory, joint optimization, multi-unit system, cost rate