In a semiconductor plasma etcher, it is becoming increasingly necessary to improve productivity by reducing unplanned equipment maintenance. Thus, predictive maintenance (PdM) is typically conducted using equipment data to predict the failure timing, after which proactive measures should be taken. In PdM, the planned maintenance schedule is updated on the basis of the predicted failure timing. However, in practice, the predicted failure timing has a probabilistic variability. Therefore, we propose a maintenance schedule update method based on the expected maintenance cost calculated from the probabilistic variability of the failure timing. We applied our method and conventional methods to a dataset of failure cases that model actual component failures of etchers and found that our method was effective in terms of reducing maintenance costs.

中文翻译：

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半导体等离子蚀刻机预测性维护的计划维护计划更新方法

在半导体等离子蚀刻机中，通过减少计划外的设备维护来提高生产率变得越来越必要。因此，预测性维护 (PdM) 通常使用设备数据来预测故障时间，然后应采取主动措施。在 PdM 中，计划维护计划根据预测的故障时间进行更新。然而，在实践中，预测的故障时间具有概率可变性。因此，我们提出了一种基于从故障时间的概率可变性计算出的预期维护成本的维护计划更新方法。我们将我们的方法和传统方法应用于模拟蚀刻机实际组件故障的故障案例数据集，并发现我们的方法在降低维护成本方面是有效的。