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About

Chang-Ha Lee is a leading researcher in advanced manufacturing systems, with a focus on the automotive industry’s transition toward Industry 4.0. His work centers on the design, scheduling, and intelligent reconfiguration of flexible production environments, particularly Matrix Manufacturing Systems and Reconfigurable Assembly Systems. Lee’s major contributions include pioneering multi-objective optimization for layout planning in matrix systems, developing a Deep Q-Network approach for dynamic scheduling with Autonomous Mobile Robots (AMRs), and applying genetic algorithms to enable intelligent layout reconfiguration. His most cited paper (2025, 6 citations) addresses the strategic layout of matrix systems to meet diverse customer needs, while his subsequent works (2024) advance real-time scheduling and reconfigurability. Though early in its citation trajectory, Lee’s research is gaining traction for its practical impact on automotive manufacturing flexibility. His integration of AI-driven methods—such as reinforcement learning and evolutionary algorithms—with modular, AMR-based systems positions him at the forefront of smart factory innovation, offering scalable solutions for the rapidly evolving production landscape.