TestDNA-E: Wafer Defect Signature for Pattern Recognition by Ensemble Learning

被引：4

作者：

Chen, Leon Li-Yang ^{[1
]}

Li, Katherine Shu-Min ^{[2
]}

Cheng, Ken Chau-Cheung ^{[1
]}

Wang, Sying-Jyan ^{[2
]}

Huang, Andrew Yi-Ann ^{[1
]}

Chou, Leon ^{[1
]}

Tsai, Nova Cheng-Yen ^{[1
]}

Lee, Chen-Shiun ^{[1
]}

机构：

[1] NXP Semicond Taiwan Ltd, Dept Wafer Test, Kaohsiung, Taiwan

[2] Natl Sun Yat Sen Univ, Dept Comp Sci & Engn, Kaohsiung, Taiwan

来源：

2020 IEEE INTERNATIONAL TEST CONFERENCE (ITC) | 2020年

关键词：

wafer defect map; diagnosis classification; machine learning; AUTOMATIC IDENTIFICATION; REGRESSION NETWORK; CLASSIFICATION;

D O I：

10.1109/ITC44778.2020.9325237

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We propose a machine learning based method targeted for accurate wafer defect map classification. The proposed method is referred to as TestDNA-E, as it applies ensemble learning based on improved TestDNA features. Experimental results show that the proposed method achieves high hit rate for each defect type and overall accuracy.

引用

页数：4

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