Under Review

Diagnostic analysis for failures in semiconductor fabrication based on Random Forest

Semiconductor Fabrication Random Forest Machine Learning Statistical Analysis

Cite as:

Zhenhan Huang (2019). Diagnostic analysis for failures in semiconductor fabrication based on Random Forest. RESEARCHERS.ONE, https://www.researchers.one/article/2019-11-12.

Abstract:

I implemented the data from a significant semiconductor fabrication company. Through supervised machine learning, I build a Random Forest classifier with up to 96% accuracy to detect defective wafers/lots after they have been produced, and I study which particular signals indicate the most to faults in fabricating. This research can provide information and support to prevent future failures in semiconductor fabrication.