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Project Title: Workstation performance acceleration with AI-driven root cause analysis tool to bridge human insight with machine learning •
Project Description:To maintain Micron’s technological leadership, speed to root cause analysis and solution is essential.
This project focuses on developing an AI-drivenroot cause analysis tool that automates the diagnosis of process and hardware-related issues—transforming raw incident data into actionable insights.•In this project, an AI-driven tool will be developed intelligently dissect incident data into Pareto buckets, providing clear direction for engineering teams to address chronic failures.
It will leverage AI and machine learning to interpret human-written inputs from the Equipment Tracking Interface (ETI), validate incidents via integration with Microsoft Teams, and analyze historical data to uncover recurring failure patterns.•Students will be involved in both AI model simulation and validation, as well as hands-on tool-side investigations where issues originate.
This cross-functional effort spans production, hardware, process, and planning teams—offering the opportunity to work across the full spectrum of semiconductor operations experts•
Scope:Explore andtrain AI models to dissect ETI big data inputs from multiple source (Tool alarm, FaultDetection, SPC) and understand human verbiage in ETI logs.
Integrate ETI with Teams for incident validation.
Identify and analyze chronic failure patterns with correlation study to uncover opportunities to accelerate workstation performance.
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Deliverable: AIModeltointerpret human-written incident logs from the Equipment Tracking Interface (ETI), link ETI to Microsoft Teams for incident validation, and perform data analytics to uncover patterns in chronic failures.•
Impact of Project: 12 man-hours per week productivity improvement, eliminate gaps in incident validation, accelerate learning cycles by 2–3 weeks per chronicissues•.
Skillset Require: Problem-solving and critical thinking, data analytics, programming; Bonus: Familiar with NLP / Automation workflows•
Course of interests: Data analytics related courses, , Engineering,, Data Science, Computer Science