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We use MixedWM38, the mixed-type wafer defect pattern dataset for wafer defect pattern regcognition with visual transformers.
Practical example from the SPIE short course "Data Analytics and Machine Learning in Semiconductor Manufacturing: Applications for Physical Design, Process and Yield Optimization"
Lithography defect prediction for microchip manufacturing optimization with machine learning model
MEMS patent
Calculating semiconductor chip yield against defect density using a Monte Carlo simulation is a common approach to assess the impact of defects on chip manufacturing. In this simulation, we'll randomly generate defect locations and evaluate chip yield based on specified criteria.
Data-Driven Optimization of Semiconductor Processes and Forecasting
Semiconductor Process Control (ECE6455-A) @ Georgia Institute of Technology, Atlanta, GA, USA
A Minecraft mod adding realistic semiconductor manufacturing.