首页> 外文期刊>Proceedings of the Workshop on Principles of Advanced and Distributed Simulation >A MARKOV DECISION PROCESS MODEL FOR OPTIMAL POLICY MAKING IN THE MAINTENANCE OF A SINGLE-MACHINE SINGLE-PRODUCT TOOLSET
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A MARKOV DECISION PROCESS MODEL FOR OPTIMAL POLICY MAKING IN THE MAINTENANCE OF A SINGLE-MACHINE SINGLE-PRODUCT TOOLSET

机译:维护单机单产品工具集的最优策略的MARKOV决策过程模型

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摘要

An aspect of great importance in Semiconductor Manufacturing Systems (SMS) is that machines are subject to unpredictable failures. Since Semiconductor Manufacturing is a highly capital intensive industry, it is crucial to optimize the usage of the resources. Performing preventive maintenance (PM), if done optimally, can reduce the risk of unpredicted failures and hence minimize the cost of outages. However, performing frequent PM results in higher cycle time and WIP accumulation at the toolset. In this paper we present a method to create optimal policies for a single-server single-product workstation using a Markov Decision Process model. The optimal policy determines whether or not to perform the PM based on the WIP level and the time since last repair. We present some numerical examples to illustrate the behavior of the optimal policy under different scenarios and compare the results with some common policies such as fixed frequency PM.
机译:在半导体制造系统(SMS)中,非常重要的一个方面是机器容易发生无法预测的故障。由于半导体制造是高度资本密集型产业,因此优化资源的使用至关重要。如果进行了最佳维护,则执行预防性维护(PM)可以降低意外故障的风险,从而最大程度地减少停机成本。但是,频繁执行PM会导致更长的循环时间和工具集上的WIP累积。在本文中,我们提出一种使用马尔可夫决策过程模型为单服务器单产品工作站创建最佳策略的方法。最佳策略根据WIP级别和自上次维修以来的时间来确定是否执行PM。我们提供一些数值示例,以说明在不同情况下最优策略的行为,并将结果与​​固定频率PM等一些常见策略进行比较。

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