This course aims to equip students with advanced statistical learning tools and methodologies essential for monitoring and improving quality in manufacturing processes within the big data era. Topics covered include manufacturing quality control, foundational quality improvement philosophies, manufacturing process optimization and statistical process control charts. Additionally, students will learn about essential ideas of statistical learning and machine learning for a more advanced measurement system analysis to improve quality engineering practices related to additive manufacturing and semiconductor manufacturing, such as variability quantification of additively manufactured parts, defect detection of photovoltaic silicon wafers, and control of etching process.

Continuous Assessment: 70%

Examination: 30%

Examination Duration: 2 hours