Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering

Katherine Shu Min Li; Leon Li-Yang Chen; Ken Chau Cheung Cheng; Peter Yi-Yu Liao; Sying Jyan Wang; Andrew Yi An Huang; Nova Tsai; Leon Chou; Gus Chang Hung Han; Jwu E. Chen; Hsing Chung Liang; Chun Lung Hsu

doi:10.1109/ETS50041.2021.9465457

Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering

Katherine Shu Min Li
, Leon Li-Yang Chen
, Ken Chau Cheung Cheng
, Peter Yi-Yu Liao
, Sying Jyan Wang
, Andrew Yi An Huang
, Nova Tsai
, Leon Chou
, Gus Chang Hung Han
, Jwu E. Chen
, Hsing Chung Liang
, Chun Lung Hsu

National Sun Yat-sen University
NXP Semiconductors
National Chung Hsing University
National Central University
Industrial Technology Research Institute of Taiwan

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

3 引文斯高帕斯（Scopus）

摘要

we propose an automatic wafer defect maps detection method based on unsupervised learning. There is no need for human labeling, and similar defect clusters are identified automatically without human intervention. As a result, the process is less error-prone. Whenever the wafer test result of a WUT is available, it can be compared immediately with existing clusters. If the wafer map matches one of the known defect patterns, then RCA can be done efficiently.

原文	英語
主出版物標題	Proceedings - 2021 IEEE European Test Symposium, ETS 2021
發行者	Institute of Electrical and Electronics Engineers Inc.
ISBN（電子）	9781665418492
DOIs	https://doi.org/10.1109/ETS50041.2021.9465457
出版狀態	已出版 - 24 05 2021
對外發佈	是
事件	26th IEEE European Test Symposium, ETS 2021 - Virtual, Bruges, 比利時持續時間: 24 05 2021 → 28 05 2021

出版系列

名字	Proceedings of the European Test Workshop
卷	2021-May
ISSN（列印）	1530-1877
ISSN（電子）	1558-1780

Conference

Conference	26th IEEE European Test Symposium, ETS 2021
國家/地區	比利時
城市	Virtual, Bruges
期間	24/05/21 → 28/05/21

文獻附註

Publisher Copyright:
© 2021 IEEE.

存取文件

10.1109/ETS50041.2021.9465457

其它文件與鏈接

Link to publication in Scopus

引用此

Li, K. S. M., Li-Yang Chen, L., Cheng, K. C. C., Yi-Yu Liao, P., Wang, S. J., Huang, A. Y. A., Tsai, N., Chou, L., Han, G. C. H., Chen, J. E., Liang, H. C., & Hsu, C. L. (2021). Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering. 於 Proceedings - 2021 IEEE European Test Symposium, ETS 2021 文章 9465457 (Proceedings of the European Test Workshop; 卷 2021-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETS50041.2021.9465457

@inproceedings{0e4f53b60fd04f67aa2f338ad904be19,

title = "Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering",

abstract = "we propose an automatic wafer defect maps detection method based on unsupervised learning. There is no need for human labeling, and similar defect clusters are identified automatically without human intervention. As a result, the process is less error-prone. Whenever the wafer test result of a WUT is available, it can be compared immediately with existing clusters. If the wafer map matches one of the known defect patterns, then RCA can be done efficiently.",

keywords = "clustering, defect pattern, machine learning, mask, wafermap, yield learning",

author = "Li, \{Katherine Shu Min\} and \{Li-Yang Chen\}, Leon and Cheng, \{Ken Chau Cheung\} and \{Yi-Yu Liao\}, Peter and Wang, \{Sying Jyan\} and Huang, \{Andrew Yi An\} and Nova Tsai and Leon Chou and Han, \{Gus Chang Hung\} and Chen, \{Jwu E.\} and Liang, \{Hsing Chung\} and Hsu, \{Chun Lung\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 26th IEEE European Test Symposium, ETS 2021 ; Conference date: 24-05-2021 Through 28-05-2021",

year = "2021",

month = may,

day = "24",

doi = "10.1109/ETS50041.2021.9465457",

language = "英语",

series = "Proceedings of the European Test Workshop",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings - 2021 IEEE European Test Symposium, ETS 2021",

address = "美国",

}

Li, KSM, Li-Yang Chen, L, Cheng, KCC, Yi-Yu Liao, P, Wang, SJ, Huang, AYA, Tsai, N, Chou, L, Han, GCH, Chen, JE, Liang, HC & Hsu, CL 2021, Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering. 於 Proceedings - 2021 IEEE European Test Symposium, ETS 2021., 9465457, Proceedings of the European Test Workshop, 卷 2021-May, Institute of Electrical and Electronics Engineers Inc., 26th IEEE European Test Symposium, ETS 2021, Virtual, Bruges, 比利時, 24/05/21. https://doi.org/10.1109/ETS50041.2021.9465457

Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering. / Li, Katherine Shu Min; Li-Yang Chen, Leon; Cheng, Ken Chau Cheung 等.
Proceedings - 2021 IEEE European Test Symposium, ETS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 9465457 (Proceedings of the European Test Workshop; 卷 2021-May).

研究成果: 圖書/報告稿件的類型 › 會議稿件 › 同行評審

TY - GEN

T1 - Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering

AU - Li, Katherine Shu Min

AU - Li-Yang Chen, Leon

AU - Cheng, Ken Chau Cheung

AU - Yi-Yu Liao, Peter

AU - Wang, Sying Jyan

AU - Huang, Andrew Yi An

AU - Tsai, Nova

AU - Chou, Leon

AU - Han, Gus Chang Hung

AU - Chen, Jwu E.

AU - Liang, Hsing Chung

AU - Hsu, Chun Lung

PY - 2021/5/24

Y1 - 2021/5/24

N2 - we propose an automatic wafer defect maps detection method based on unsupervised learning. There is no need for human labeling, and similar defect clusters are identified automatically without human intervention. As a result, the process is less error-prone. Whenever the wafer test result of a WUT is available, it can be compared immediately with existing clusters. If the wafer map matches one of the known defect patterns, then RCA can be done efficiently.

AB - we propose an automatic wafer defect maps detection method based on unsupervised learning. There is no need for human labeling, and similar defect clusters are identified automatically without human intervention. As a result, the process is less error-prone. Whenever the wafer test result of a WUT is available, it can be compared immediately with existing clusters. If the wafer map matches one of the known defect patterns, then RCA can be done efficiently.

KW - clustering

KW - defect pattern

KW - machine learning

KW - mask

KW - wafermap

KW - yield learning

UR - https://www.scopus.com/pages/publications/85113716266

U2 - 10.1109/ETS50041.2021.9465457

DO - 10.1109/ETS50041.2021.9465457

M3 - 会议稿件

AN - SCOPUS:85113716266

T3 - Proceedings of the European Test Workshop

BT - Proceedings - 2021 IEEE European Test Symposium, ETS 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 26th IEEE European Test Symposium, ETS 2021

Y2 - 24 May 2021 through 28 May 2021

ER -

Li KSM, Li-Yang Chen L, Cheng KCC, Yi-Yu Liao P, Wang SJ, Huang AYA 等. Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering. 於 Proceedings - 2021 IEEE European Test Symposium, ETS 2021. Institute of Electrical and Electronics Engineers Inc. 2021. 9465457. (Proceedings of the European Test Workshop). doi: 10.1109/ETS50041.2021.9465457

Automatic Inspection for Wafer Defect Pattern Recognition with Unsupervised Clustering

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出版系列

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