Wafer-Level Test Path Pattern Recognition and Test Characteristics for Test-Induced Defect Diagnosis

Ken Chau Cheung Cheng, Katherine Shu-Min Li, Andrew Yi Ann Huang, Ji Wei Li, Leon Li Yang Chen, Nova Cheng-Yen Tsai, Sying Jyan Wang, Chen Shiun Lee, Leon Chou, Peter Yi Yu Liao, Hsing Chung Liang, Jwu E. Chen

研究成果: 書貢獻/報告類型會議論文篇章同行評審

4 引文 斯高帕斯(Scopus)

摘要

Wafer defect maps provide precious information of fabrication and test process defects, so they can be used as valuable sources to improve fabrication and test yield. This paper applies artificial intelligence based pattern recognition techniques to distinguish fab-induced defects from test-induced ones. As a result, test quality, reliability and yield could be improved accordingly. Wafer test data contain site-dependent information regarding test configurations in automatic test equipment, including effective load push force, gap between probe and load-board, probe tip size, probe-cleaning stress, etc. Our method analyzes both the test paths and site-dependent test characteristics to identify test-induced defects. Experimental results achieve 96.83% prediction accuracy of six NXP products, which show that our methods are both effective and efficient.

原文???core.languages.en_GB???
主出版物標題Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
編輯Giorgio Di Natale, Cristiana Bolchini, Elena-Ioana Vatajelu
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1710-1711
頁數2
ISBN(電子)9783981926347
DOIs
出版狀態已出版 - 3月 2020
事件2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020 - Grenoble, France
持續時間: 9 3月 202013 3月 2020

出版系列

名字Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020

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???event.eventtypes.event.conference???2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
國家/地區France
城市Grenoble
期間9/03/2013/03/20

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