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

Authors :
Li, Katherine Shu-Min
Chen, Leon Li-Yang
Cheng, Ken Chau-Cheung
Liao, Peter Yi-Yu
Wang, Sying-Jyan
Huang, Andrew Yi-Ann
Chou, Leon
Tsai, Nova Cheng-Yen
Lee, Chen-Shiun
Source :
IEEE Transactions on Semiconductor Manufacturing; May2022, Vol. 35 Issue 2, p372-374, 3p
Publication Year :
2022

Abstract

Wafer failure pattern recognition can be used for root cause analysis, which is very important for yield learning. Recently, TestDNA was proposed to improve diagnosis resolution with data collected from wafer test. Previous studies on wafer failure pattern recognition using machine learning achieve good classification results. In this letter, we propose to enhance the classification accuracy with the help of spatial information and ensemble learning algorithms. Experimental results indicate that the proposed method can further improve the accuracy by 8.9%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08946507
Volume :
35
Issue :
2
Database :
Complementary Index
Journal :
IEEE Transactions on Semiconductor Manufacturing
Publication Type :
Academic Journal
Accession number :
156741933
Full Text :
https://doi.org/10.1109/TSM.2022.3145855