针对具有多个相关退化过程系统的状态维修及备件订购决策问题,在连续监测条件下,建立系统维修与备件订购决策优化模型.首先,采用Gamma过程和Copula函数建立系统多元退化模型,然后提出基于控制限策略的系统维修与备件订购策略.在此基础上,考虑系统退化量对维修费用的影响,获得系统长期运行条件下的期望维修费用率解析表达式.同时为简化模型计算,提出系统期望维修费用率近似表达式.利用人工蜂群算法在费用准则下获得系统最优预防性更换阈值和备件订购阈值.案例分析结果说明了在维修决策中考虑退化相关的必要性.与已有策略相比,综合优化预防性更换和备件订购阈值能够有效降低系统维修费用.

Aimed at the decision-making problem of condition-based maintenance and spare parts ordering for systems with multiple dependent degradation processes, an optimization model of system maintenance and spare parts ordering policy is developed under the condition of continuously monitoring. First, the Gamma process and Copula function are used to develop the system multivariate degradation model. Then, the system maintenance and spare parts ordering policy based on the control limit strategy is proposed. Considering the influence of system degradation on maintenance cost, the analytical expression of the expected maintenance cost rate under long-term operation conditions is obtained. At the same time, an approximate expression of the expected maintenance cost rate is proposed to simplify the model calculation. The optimal preventive replacement threshold and spare parts ordering threshold of the system are obtained by using the artificial bee colony algorithm under the cost criterion. The case analysis shows that it is necessary to consider degradation in maintenance decision-making. Compared with the existing policy, the comprehensive optimization of preventive replacement and spare parts ordering thresholds can effectively reduce the maintenance cost of the system.