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TestDNA: Novel Wafer Defect Signature for Diagnosis and Pattern Recognition.

Authors :
Li, Katherine Shu-Min
Tsai, Nova Cheng-Yen
Cheng, Ken Chau-Cheung
Jiang, Xu-Hao
Liao, Peter Yi-Yu
Wang, Sying-Jyan
Huang, Andrew Yi-Ann
Chou, Leon
Lee, Chen-Shiun
Source :
IEEE Transactions on Semiconductor Manufacturing; Aug2020, Vol. 33 Issue 3, p383-390, 8p
Publication Year :
2020

Abstract

The spatial failure patterns in wafer defect maps can be related to problems in the manufacturing and test process. Therefore, failure pattern recognition can be used for root cause analysis, which is very important for defect diagnosis resolution improvement and yield learning. However, previous studies show that wafers with recognizable failure patterns only account for a small part of all defective wafers. In order to further improve diagnosis resolution with data collected from wafer test, we propose a novel way to present results of various test items in order to facilitate feature extraction. The test results are exhibited in a DNA-like signature called TestDNA such that sources of wafer defects can be effectively and efficiently identified. Since more defect information can be incorporated into a TestDNA, more defect types of wafer defects can be identified and predicted with higher accuracy. Experimental results show that the proposed TestDNA method can be used to identify and predict more defect types such that both higher diagnosis resolution and prediction accuracy are achieved. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08946507
Volume :
33
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Semiconductor Manufacturing
Publication Type :
Academic Journal
Accession number :
145130865
Full Text :
https://doi.org/10.1109/TSM.2020.2992927