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Run-to-Run Fault Detection based on ARX Model and PCA for Semiconductor Manufacturing Processes

机译:基于ARX模型和PCA的运行间故障检测在半导体制造过程中的应用

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This paper proposes a run-to-run(RtR) fault detection approach for general semiconductor manufacturing processes. In this paper, a data -based model, auto-regressive with exogenous inputs (ARX) model, will be introduced as an alternative of a mechanical model for a semiconductor manufacturing process. In this model a recursive least-squares (RLS) algorithm is proposed to identify the on-line parameter. Once the process abnormalities occurred,the fault will be detected with a statistical principal component analysis (PCA) method applied to ARX parameters. And the results will be illustrated by several simulations.
机译:本文提出了一种用于一般半导体制造过程的运行到运行(RtR)故障检测方法。在本文中,将引入基于数据的模型(具有外生输入的自回归(ARX)模型)作为半导体制造过程的机械模型的替代方法。在该模型中,提出了一种递归最小二乘(RLS)算法来识别在线参数。一旦发生过程异常,将通过应用于ARX参数的统计主成分分析(PCA)方法来检测故障。结果将通过几个模拟进行说明。

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