需求随机波动下多设备批量生产系统的视情维护策略研究

针对需求随机波动情况下多设备批量生产系统的设备维护问题，提出了一种基于滚动生产计划和设备退化状况的视情维护策略。首先，通过滚动时域规划方法预测不同产品的随机需求并在此基础上以总生产成本最小确定滚动生产计划。其次，在每一滚动生产周期开始前检测系统中各设备的退化水平，利用Gamma过程描述退化增量，以最小维护成本率确定当前退化状态下各设备的最佳维护时间，同时为避免生产过程中断利用提前延后维护策略对预防维护进行动态调整。在系统层，利用生产转换时机对需要维护的组件进行组合维护。再次，引入时间约束和服务水平约束，建立批量生产与视情维护的联合优化模型，以总成本最小为目标，确定实际生产计划和维护计划。最后，通过算例以整个生产计划期内的总成本和故障次数为度量验证了所提出的多设备批量生产系统视情维护策略的有效性。

Research on condition-based maintenance strategy of multi-equipment batch production system based on stochastic demand fluctuation

In view of the maintenance problem of multi-equipment batch production systems under stochastic demand, this paper proposed a condition-based maintenance strategy based on a rolling production plan and equipment degradation state. Firstly, the method used the rolling horizon approach to forecast the stochastic demand for different products. On this basis, it determined the rolling production plan by minimizing the total production cost. Secondly, before each rolling production cycle starts, detected the degradation level of each equipment in the system and used the Gamma process to describe the degradation increment. And determine the optimal maintenance time of each equipment in the current degradation state with the minimum maintenance cost rate. To avoid interruptions in the production process, dynamically adjusted preventive maintenance using an advanced-postponed maintenance strategy. At the system level, it used production changeover opportunities to perform combined maintenance on components that require maintenance. Thirdly, the joint optimization model introduced time and service level constrainted to determine the actual production plan and maintenance plan to minimize the total cost. Finally, with the total cost and the number of failures in the whole production planning period as the measures, the example verifies the effectiveness of the condition-based maintenance strategy of the proposed multi-equipment batch production system.