Marvin Carl May
Papers
4
Total Citations
72
H-Index
4
About
Marvin Carl May is a rising leader in sustainable manufacturing and circular economy research, focusing on the intersection of remanufacturing, artificial intelligence, and production system optimization. His work addresses critical challenges in disassembly and remanufacturing—key strategies for reducing industrial waste and emissions—by leveraging machine learning and data-driven models. His most cited paper, "Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning" (2022, 51 citations), pioneers the use of reinforcement learning to dynamically manage disassembly lines, a novel approach in production planning. May further advances the field through his survey "Unlocking the Potential of Remanufacturing Through Machine Learning and Data-Driven Models" (2024, 6 citations), which systematically maps how AI can overcome barriers to circular economy adoption. He also contributes to human-centered automation, designing explainable AI interfaces for industrial robotics (2024, 4 citations) to bridge the gap between deep learning and real-world manufacturing. With additional work on robotic assembly line balancing (2024, 11 citations), May’s research is shaping smarter, more sustainable production systems.
Research Focus
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Top Papers
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