A Multi-Institutional Digital Twin and AI Educational Platform for Advanced Microelectronics Fabrication and Device Packaging Training
Authors/Creators
- 1. Department of Computer Science, University of California, Irvine, CA
- 2. Troy High School, Fullerton, CA
- 3. Mercer County Community College, Princeton Junction,
- 4. Department of Electrical Engineering and Computer Science, University of California, Irvine, CA
- 5. Princeton Materials Institute, Princeton University, Princeton, NJ
Description
Technology today is at a crossroad between Industry 4.0 and 5.0, where products and services are manufactured and designed to be ‘human-centered’ and sustainable. Such objectives have always been expected in education, especially in the way the workforce is trained. Leveraging on prior research which was done by a team from Pasadena City College (PCC) and UC Irvine, we have formed a bi-coastal collaborative, including Mercer County Community College (MCCC) and Princeton University, to expand and transcend our earlier AI-powered virtual reality (VR) simulation framework and platform, AI-powered digital twin (DT/AI) for education. This Phase-2 effort demonstrates a working, multi-institution R&D platform with the following capabilities: (a) new training modules with enhanced lithography training and advanced device packaging, (b) better optimized, high-fidelity equipment emulations and process simulations that much closely replicate the physical equipment, (c) adherence to documented facility-specific Standard Operation Procedure (SOP) and manufacturing process flow, (d) a parallel fabricated chip-under-test and its test board for I/O connectivity verification, and last but not the least, (e) a tightly-coupled agentic AI engines available throughout the training session to customize learner-centric experiences to enhance individual knowledge acquisition and retention. The authors also continue to demonstrate the feasibility and scalability benefits of foundational VR/AR-based training for students, technicians, and up-skill learners for whom direct cleanroom or packaging lab access is often unattainable; while with DT/AI, learning and feedback is affordable and widely accessible.
Files
Kristal Hong_DOI_A Multi-Institutional Digital Twin_3-26-26.pdf
Files
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Additional details
Funding
- U.S. National Science Foundation
- The Micro Nano Technology Education Center (MNT-EC) 2000281