基于先进技术节点缺陷自动分类的设计:DI:缺陷检测和减少

Jay K Shah, Abhinav Jain, F. Levitov, Shay Yasharzade, J. G. Sheridan, Vu Nguyen, Hoang Nguyen
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引用次数: 3

摘要

随着半导体行业继续向越来越小的节点推进,缺陷审查扫描电子显微镜(DR-SEM)和ADC(自动缺陷分类)面临着越来越困难的挑战。感兴趣缺陷(DOI)随着特征的缩小而缩小,导致单纯基于尺度的成像困难。此外,对于在多个模式步骤中形成的DOI或在前面步骤中创建的DOI,需要进行更复杂的缺陷分析。必须采用一种智能的ADC方法,以便在短周期内进行高质量的缺陷分类,重点是根本原因分析和良率预测。在本文中,我们提出了一种新的方法:基于设计的ADC (DBA)。在这里,设计信息与当前DR-SEM和ADC平台相结合,从而实现卓越和稳健的分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design based automatic defect classification at advanced technology nodes: DI: Defect inspection and reduction
As the semiconductor industry continues to advance to smaller and smaller nodes, Defect Review Scanning Electron Microscopy (DR-SEM) and ADC (Automatic Defect Classification) face increasingly difficult challenges. The Defects of Interest (DOI) shrink as the features shrink, leading to imaging difficulty purely based on scale. Also, more complex defect analysis is required for DOI's formed during multiple patterning steps or DOI's created in previous steps. A smart approach to ADC must be adopted which allows for high quality defect classification focused on root cause analysis and yield prediction in short cycle times. In this paper, we present results from novel approach: Design Based ADC (DBA). Here, design information with current DR-SEM and ADC platforms is combined, leading to superior and robust classification.
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