Project Description
Data analytics and machine learning are used in manufacturing operations to improve efficiency and provide greater visibility into production-line health. Large volumes of data are generated from electrical tests, physical tests, and manufacturing measurements, creating opportunities for faster analysis and earlier detection of abnormal performance.
This internship project focuses on developing an end-to-end analytical solution covering data querying, preprocessing, feature engineering, modelling, and results visualization. The intern will apply advanced analytics and machine learning techniques to manufacturing data to improve metrics analysis and identify potential performance drift.
Through this project, the intern will gain exposure to industrial data analytics, predictive modelling, simulation, optimization, and visualization techniques used in semiconductor manufacturing.