Student Created AI-powered Digital Twin for Semiconductor Workforce Training

I. Jha, A. Ashcroft, D. Kelley, J. Zhu, A. Rodriguez, A. Dong, F. Chen, K. Hong, G. Codina
Micro Nano Technology Education Center,
United States

Keywords: Semiconductor, Virtual Reality, Undergraduate Research


Simulation-based learning is a technique that aims to replicate the effects of real-life learning in the digital world. This is often through the use of “digital twins,” which are virtual clones of real spaces that can habituate the training of workers prior to entering a real factory. The Semiconductor Industry Association (SIA) reports a growing gap in semiconductor technicians, engineers and scientists, all amidst the nationwide effort to onshore production of semiconductors. Traditional methods of training appear to be inadequate for preparing the workforce in such a short period of time and new approaches need to be explore. This poster presents an immersive simulation to enable learners to explore a semiconductor fabrication plant (fab) using eXtended Reality (XR), a technology that has recently become available. In addition, we apply artificial intelligence (AI) models to make the training adaptive to each learner for increased engagement and learning. Learners can also ask questions and get accurate answers from the AI. Simulation based learning has shown favorable results in the medical industry and in machine operator training in naval, aviation and manufacturing industries which suggests that it can also be successfully applied in semiconductor industry. We present our simulation design and creation approach and preliminary results from pilot testing with a group of students.