Papers
6
Total Citations
89
H-Index
4
About
Maolin Yang is a leading researcher at the intersection of intelligent manufacturing, robotics, and industrial informatics. His work focuses on solving critical challenges in automated production systems, particularly in harsh industrial environments. Yang’s most influential contribution is his pioneering method for image positioning and identification in coal and gangue sorting robots (69 citations), which addresses a key bottleneck in coal production automation under complex, heterogeneous conditions. He has also made significant advances in knowledge graph modeling for smart and connected industrial products, and in expert systems for analyzing printability in design for additive manufacturing. Yang’s research extends to industrial product-service systems (IPS²), where he has developed reinforcement learning-based approaches for robot-driven sanding and polishing lines, and to digital twin modeling for remote monitoring and intelligent maintenance of industrial equipment. His work is notable for its practical industrial applications, demonstrated through case studies in robot-driven polishing service systems under Industry 4.0 contexts. Yang’s contributions are shaping the future of smart manufacturing by enabling more autonomous, efficient, and sustainable production systems.
Research Focus
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