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大多数研究单机调度与维修决策集成问题的文献采用基于役龄的维修策略.然而,设备劣化状态与加工对象、加工环境和加工时间等诸多因素相关.鉴于此,针对设备状态可检测的系统,采用非完美预防性视情维修、小修与故障更换相结合的维修策略,建立一种以加工作业次序和预防维修阈值为决策变量,加工作业的总加权期望完成时间最小为优化目标的随机期望值集成模型.实验结果表明,所提出的模型能更有效地避免过维修或欠维修,并且能够降低生产持有成本.
Most of the literature that studies the problem of single machine scheduling and maintenance decision integration uses service-age-based maintenance strategy.However, the equipment degradation state is related to many factors such as the processing object, processing environment and processing time, etc. In view of this, A non-perfect preventive maintenance strategy based on condition-based maintenance, minor repair and fault replacement is adopted to set up a random expectation value integration goal which takes processing task sequence and preventive maintenance threshold as decision variables. Model.The experimental results show that the proposed model can avoid over-repair or under-repair more effectively, and can reduce the cost of production and holding.