基于仿真的多部件设备机会维修多目标决策优化方法  

Multi-Objective Decision-Making Optimization Method for Opportunistic Maintenance of multi-Component Equipment Based on Simulation

作　　者：王梅[1] 张少文 张祥祥[1] 胡子翔 WANG Mei;ZHANG Shaowen;ZHANG Xiangxiang;HU Zixiang(No.38 Research Institute of CETC,Hefei 230088,China)

机构地区：[1]中国电子科技集团公司第三十八研究所,安徽合肥230088

出　　处：《机械》2023年第5期20-26,共7页Machinery

摘　　要：提出一种基于仿真的多部件设备机会维修多目标决策优化方法,考虑了多种维修方式、多种机会维修策略、非预期故障的随机持续时长和成本以及随机的预防性维修时长,利用蒙特卡洛仿真计算系统可用度和总成本,多目标粒子群算法进行求解最佳维修方式。将该方法应用到电子组装线的某生产设备,结果显示,同时考虑了随机故障和预防性维修的机会维修策略具有更优的Pareto前沿,能够进一步优化系统可用度与系统总成本,并对可用度和总成本的随机分布进行了分析。This paper proposes a multi-objective decision-making optimization method for opportunistic maintenance of multi component equipment based on simulation,taking into consideration multiple maintenance modes,multiple opportunistic maintenance strategies,random duration and cost of unexpected faults,and random preventive maintenance duration.Monte Carlo simulation is used to calculate system availability and total cost,and multi-objective particle swarm optimization algorithm is used to solve the optimal maintenance mode.The method is applied to a production equipment of an electronic assembly line.The results show that the opportunistic maintenance strategy,considering both random failures and preventive maintenance,has a better Pareto frontier,which can further optimize the system availability and total system cost.The random distribution of availability and total cost is analyzed.

关 键 词：预防性维修 机会维修 PARETO优化 蒙特卡洛仿真 粒子群算法 

分 类 号：TH17[机械工程—机械制造及自动化]