Micron
Generative AI for Semiconductor Manufacturing
Micron sought to better understand how generative AI could accelerate analysis of complex semiconductor manufacturing data and help reveal patterns tied to key fab performance metrics. This project investigated the use of generative AI to explore a large manufacturing dataset from one of Micron’s fabs, with the goal of identifying underlying trends, documenting an effective approach for AI-assisted data discovery, and developing possible process improvement recommendations based on the insights found. This work aimed to clarify how this technology could support faster understanding of difficult manufacturing data and inform future engineering decision-making.
Students
Faculty Adviser(s)
Luna Yue Huang, Materials Science & Engineering
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