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Proceedings Paper

Automated semiconductor wafer defect classification dealing with imbalanced data
Author(s): Po-Hsuan Lee; Zhe Wang; Cho Teh; Yi-Sing Hsiao; Wei Fang
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Paper Abstract

In the semiconductor manufacturing industry, Automatic Defect Classification (ADC) plays an important role in maintaining high wafer inspection quality and reducing yield loss. ADC performance has benefitted from using machine learning (ML) algorithms; however, performance is negatively affected by the data imbalance and limited amounts of training data. Synthetic Minority Oversampling Technique (SMOTE) is an oversampling technique to adjust the skewed class distribution of a dataset so that the bias of the majority class is reduced. This paper shows that applying SMOTE achieved higher accuracy and purity on two imbalanced datasets, consisting of scanning electron microscopy (SEM) images collected with ASML-HMI eP™ and eScan® series inspection tools. The ML models are also less sensitive to the selection of hyperparameters when SMOTE is applied. We also show that better classification results can be obtained with less training samples with SMOTE; we conducted an experiment where a ML model trained on only 25% of samples with SMOTE achieved a higher ADC accuracy and purity performance compared to the same ML model trained on all samples but without SMOTE. In another experiment using a highly imbalanced SEM dataset with very few counts of the defect-of- interest (DOI), the combination of SMOTE and random undersampling of the majority class improves the accuracy by up to 5x while maintaining the same level of purity.

Paper Details

Date Published: 20 March 2020
PDF: 7 pages
Proc. SPIE 11325, Metrology, Inspection, and Process Control for Microlithography XXXIV, 1132526 (20 March 2020);
Show Author Affiliations
Po-Hsuan Lee, Hermes Microvision Inc. (ASML) (United States)
Zhe Wang, Hermes Microvision Inc. (ASML) (United States)
Cho Teh, Hermes Microvision Inc. (ASML) (United States)
Yi-Sing Hsiao, Hermes Microvision Inc. (ASML) (United States)
Wei Fang, Hermes Microvision Inc. (ASML) (United States)

Published in SPIE Proceedings Vol. 11325:
Metrology, Inspection, and Process Control for Microlithography XXXIV
Ofer Adan; John C. Robinson, Editor(s)

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