Yuqian Yang
Papers
4
Total Citations
19
H-Index
3
About
Yuqian Yang is a rising researcher at the forefront of smart manufacturing and industrial digitalization, specializing in the design and operation of intelligent, connected industrial systems. Their work centers on integrating cyber-physical systems with advanced service models, particularly through the development of knowledge graphs and Industrial Product Service Systems (IPS2) for smart and connected industrial products. Yang’s major contributions include pioneering a novel knowledge graph framework for configuring and operating these complex systems, and designing integrated monitoring and maintenance strategies for newly developed equipment, such as industrial robots used in carbon block grinding and polishing. Their research has demonstrated significant practical impact, with studies on robot-driven polishing service systems under Industry 4.0 contexts achieving up to 6 citations each. Notably, Yang has applied reinforcement learning to optimize IPS2 design for sanding processing lines, showcasing a forward-looking approach to adaptive, data-driven manufacturing. With a focus on bridging theoretical models with real-world industrial case studies, Yang’s work is shaping the future of reliable, efficient, and intelligent production environments.
Research Focus
Key Achievements
Top Papers
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