SemImmerse: Smart Immersive Training Ecosystem for Semiconductor Manufacturing

E. Azimi, R. Lan, C. Wang, K. A. Knudson, T. Peterson, Z. Mutlu
University of Arizona,
United States

Keywords: Mixed Reality, Immersive Learning, Virtual Reality, Semiconductor Manufacturing

Summary:

The SemImmerse project aims to transform workforce development training in semiconductor manufacturing systems by enhancing immersion and hands-on learning experiences, thereby improving the learning curve and ensuring instantaneous operability. Leveraging eXtended Reality (XR) and advanced AI-based smart assessment the project streamlines tutorial generation and trainee evaluation. The objectives include revolutionizing workforce training through immersive experiences, reducing training costs, and increasing retention and motivation. Prototypes and platforms for XR-based training have been developed, promising scalable solutions for assessing skills efficiently and accurately. The project's success is measured by its tangible impact on workforce deployment and system efficiency compared to conventional training methods, with broader implications for various industries as XR becomes increasingly indispensable. SemImmerse adopts an innovative approach to immersive training by integrating AI for real-time assessment and guidance. This approach addresses the challenge of creating immersive educational content and aims to close the gap between smart assessment and human expertise. Modules for tutorial generation, smart assessment, and procedure analysis enhance realism and collaboration across expertise levels, from K-12 to advanced graduate levels. Key components include leveraging sensory inputs such as eye gaze and gestures for customized feedback, haptic rendering for increased realism, and remote monitoring for expert assistance and tele-education. By utilizing both mixed reality and virtual reality technologies, SemImmerse creates an immersive experience of the cleanroom and hands-on training with the actual device for enabling an interactive digital twin, enhancing the effectiveness of the training program. The system not only improves training efficiency but also addresses the shortage of experts and inefficiencies in the educational system, offering remote presence through mixed reality. Overall, SemImmerse represents a novel approach to workforce training, promising significant improvements in learning outcomes, cost-effectiveness, and expert availability. By harnessing XR and AI technologies, the project aims to revolutionize training across industries, paving the way for more effective and accessible education and workforce development.