单元内机器学习解决复杂的FinFET缺陷机制与体积扫描诊断

Manish Sharma, Yan Pan
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摘要

本文介绍了在半导体FA中使用机器学习的最新突破。这是第一次,finfet的细胞内部缺陷不仅被检测和诊断,而且还通过细胞感知诊断和根本原因反褶积(RCD)技术进行了细化、澄清和解决。作者描述了该方法的发展,并评估了每一步所做的增量改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Inside the Cell to Solve Complex FinFET Defect Mechanisms with Volume Scan Diagnosis
This article presents a recent breakthrough in the use of machine learning in semiconductor FA. For the first time, cell-internal defects in FinFETs have not only been detected and diagnosed, but also refined, clarified, and resolved using cell-aware diagnosis along with root cause deconvolution (RCD) techniques. The authors describe the development of the methodology and evaluate the incremental improvements made with each step.
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