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A Numerical Study on the Structure of Optimal Preventive Maintenance Policies in Prototype Tandem Queues

机译:原型串联队列最优预防性维护策略结构的数值研究

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While high levels of automation in modern manufacturing systems increase the reliability of production, tool failure and preventive maintenance (PM) events remain a significant source of production variability. It is well known for production systems, such as the M/G/1 queue, that optimal PM policies possess a threshold structure. Much less is known for networks of queues. Here we consider the prototypical tandem queue consisting of two exponential servers in series subject to health deterioration leading to failure and repair. We model the PM decision problem as a Markov decision process (MDP) with a discounted infinite- horizon cost. We conduct numerical studies to assess the structure of optimal policies. Simulation is used to assess the value of the optimal PM policy relative to the use of a PM policy derived by considering each queue in isolation. Our simulation studies demonstrate that the mean cycle time and discounted operating costs are 10% superior.
机译:虽然现代制造系统中的高水平自动化提高了生产的可靠性,但工具故障和预防性维护(PM)事件仍然是生产变异性的重要来源。它众所周知,生产系统(例如M / G / 1队列),最佳PM策略具有阈值结构。队列网络众所周知。在这里,我们考虑由串联的两台指数服务器组成的原型串联队列,这些串联受到健康恶化,导致故障和修复。我们将PM决策问题模拟为Markov决策过程(MDP),具有折扣无限的地平线成本。我们进行数值研究以评估最佳政策的结构。模拟用于评估相对于通过考虑每个队列的PM策略来评估最佳PM策略的值。我们的仿真研究表明,平均循环时间和折扣运营成本优于10%。

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