晶圆缺陷自动分类:现状及行业需求

Arye Shapiro
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引用次数: 10

摘要

本文描述了作为SEMATECH ADC项目的一部分执行的自动缺陷分类(ADC)测试站点评估。在制造环境中对两种配备ADC软件的光学复查显微镜进行了独立评估。两台显微镜均在白光照明下的亮场模式下操作。ADC性能在随机逻辑器件的三个工艺水平上进行测量:源/漏极、多晶硅栅极和金属。ADC性能指标包括分类准确性、可重复性和速度。特别是,使用包括知识库测试、测量研究和小型被动数据收集在内的协议对ADC软件进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic classification of wafer defects: status and industry needs
This paper describes the Automatic Defect Classification (ADC) beta site evaluations performed as part of the SEMATECH ADC project. Two optical review microscopes equipped with ADC software were independently evaluated in manufacturing environments. Both microscopes were operated in bright-field mode with white light illumination. ADC performance was measured on three process levels of random logic devices: source/drain, polysilicon gate, and metal. ADC performance metrics included classification accuracy, repeatability, and speed. In particular, ADC software was tested using a protocol that included knowledge base tests, gauge studies, and small passive data collections.
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