Real-Time Particle Measurement and Artificial Intelligence-Based Correlation Analysis of Wafer Defect in Semiconductor Plasma-Enhanced Chemical Vapor Deposition Process

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Key Points

This research aims to explore the effectiveness of real-time particle measurement and AI in analyzing wafer defects during the semiconductor manufacturing process.
Utilized real-time particle measurement techniques to detect defects in wafers.
Applied artificial intelligence algorithms to perform correlation analysis of defects.
Examined the plasma-enhanced chemical vapor deposition process in semiconductor manufacturing.
AI analysis significantly improved the correlation between particle counts and defect rates.
Real-time measurements detected defects more effectively compared to traditional methods.
Findings indicate that integrating AI in the process may enhance overall semiconductor quality.

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Tests real-time particle measurement and AI correlation for wafer defects, suggesting improved semiconductor quality control.

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Jung et al. (2026) studied this question.

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