刮擦
薄脆饼
计算机科学
人工智能
可靠性(半导体)
模式识别(心理学)
过程(计算)
质量(理念)
工程制图
工程类
电气工程
操作系统
功率(物理)
哲学
物理
认识论
量子力学
作者
Katherine Shu-Min Li,Peter Yi-Yu Liao,Ken Chau-Cheung Cheng,Leon Li-Yang Chen,Sying-Jyan Wang,Andrew Yi-Ann Huang,Leon Chou,Gus Chang-Hung Han,Jwu E. Chen,Hsing-Chung Liang,Chung-Lung Hsu
标识
DOI:10.1109/tsm.2020.3040998
摘要
Wafer map defect pattern recognition provides useful clues to yield learning. However, most wafer maps have no special spatial patterns and are full of noises, which make pattern recognition difficult. Especially, recognizing scratch and line types of defect patterns is challenging for process and test engineers. It takes a lot of manpower to identify such patterns, as hidden defective dies may exist on the scratch contour and become discontinuity points. Hidden scratch defective dies may suffer from latent and leakage faults, which usually deteriorate quickly and need to be screened by burn-in test to improve quality. A possible solution is to locate the obscure defective dies in scratch patterns and mark them as faulty. As a result, the quality and reliability of products is significantly improved and cost of final test is reduced. In this article, we propose a systematic methodology to search for potential hidden scratch/line defects in wafers. A five-phase method is developed to enhance wafer maps such that automatic hidden scratch defect pattern recognition can be carried out with high accuracy. Experimental results show the proposed method achieves higher than 89% recognition rate for scratch/line patterns, and higher than 94% for all common wafer defect pattern types.
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