Machine Learning Inside the Cell to Solve Complex FinFET Defect Mechanisms with Volume Scan Diagnosis

Abstract

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.