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[Keynote] Physical AI for Dark Factories: Sim-to-Real Orchestration of Heterogeneous Robot Fleets Using Digital Twin Intelligence

10:05 am - 10:40 am

This presentation introduces Physical AI for dark factories, enabling autonomous orchestration of heterogeneous robot fleets, including AMRs, OHTs, 3D shuttles, and humanoid robots. Using a sim-to-real learning framework based on high-fidelity digital twins, robot intelligence is trained in virtual environments and seamlessly transferred to real manufacturing systems, significantly reducing deployment risk and commissioning time. Industrial case studies demonstrate large-scale fleet coordination, real-time optimization, and substantial improvements in throughput, congestion mitigation, and operational stability. The proposed framework establishes a practical pathway toward fully autonomous and scalable manufacturing systems. 

Featured Speakers

Young Jae Jang

Prof. Young Jae Jang (invited)

Professor, KAIST

Young Jae Jang received his Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology (MIT) in 2007, and dual M.S. degrees in Mechanical Engineering and Operations Research from MIT in 2001. He earned his B.S. in Aerospace Engineering from Boston University in 1997. 

He is currently a Professor in the Department of Industrial and Systems Engineering at the Korea Advanced Institute of Science and Technology (KAIST) and the Founding Director of the Center for KAIST Manufacturing Physical AI, where he leads research on next-generation autonomous manufacturing systems. 

In parallel, he is the CEO and Co-founder of DAIM Research Corp., the leading startup commercializing AI-based manufacturing powered by Physical AI technology. DAIM’s platforms have been successfully deployed by major global manufacturers, including Samsung Electronics, LG Electronics, SK On, and LG Energy Solution, demonstrating large-scale industrial adoption and real-world impact.