摘要
为了降低设备运营总成本,充分发挥视情维修的优势,开展了设备的视情维修决策与备件库存量的联合优化研究。首先,采用Wiener过程建立了退化模型,估计了设备退化参数和剩余寿命;以此为基础,为充分利用剩余寿命的信息价值,引入预约备件的概念,选用遗传算法和蒙特卡罗相结合的方法,建立了以库存参数、预防性检测阈值和预约备件剩余寿命阈值为变量,以部件平均费用率最小为目标的维修与备件的联合优化仿真模型;最后,通过实例比较分析,表明联合优化方法大大地降低了维修和备件总成本,验证了方法的可行性和有效性。
In order to reduce the operational cost and take full advantage of condition-based maintenance（CBM）,the joint optimization of spare parts inventory and CBM decision is carried out.Firstly,the degradation model of the equipment is established with the Wiener process,and the degradation parameters and residual life are estimated.Secondly,the concept of appointment of spare parts is adopted to make full use of residual life information,and inventory parameters,inspection interval and appointment threshold are used as variables,the genetic algorithm and the Monte Carlo method are combined to set up ajoint optimization simulation model of maintenance and spare parts to minimize the total cost rate.Finally,an example is analyzed,and the result shows that the joint optimization method greatly reduces the total cost of maintenance and spares part,which indicates the feasibility and effectiveness of the proposed method.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2016年第8期1854-1859,共6页
Systems Engineering and Electronics
基金
国家自然科学基金(61079013)
中央高校基本科研业务费专项资金(NS2015072)资助课题
关键词
维修决策
备件管理
联合优化
维纳过程
maintenance decision
spare part management
joint optimization
Wiener process
