Out-Of-Control Detection In Semiconductor Manufacturing using One-Class Support Vector Machines

Ilham Rabhi, A. Roussy, F. Pasqualini, C. Alegret
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Abstract

Semiconductor manufacturing is a continuously challenging and competitive industry. It is important to detect any anomalies in the production facilities, or fabs, as they occur to avoid defect accumulations and loss of performance. In this paper we present a literature review of classification methods and detailed the chosen method which is One Class-Support Vector Machine (OC-SVM). This method is used for out-of-control detection in semiconductor manufacturing. The method is tested via an application using industrial data of the studied fab.
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一类支持向量机在半导体制造中的失控检测
半导体制造是一个不断挑战和竞争的行业。检测生产设施或晶圆厂中的任何异常,以避免缺陷累积和性能损失,这一点非常重要。本文对分类方法进行了文献综述,并详细介绍了所选择的一类支持向量机(OC-SVM)分类方法。该方法用于半导体制造中的失控检测。利用所研究晶圆厂的工业数据,对该方法进行了应用测试。
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