Renquan Ji

Papers

Total Citations

H-Index

About

Renquan Ji is a leading researcher in intelligent manufacturing and robotic surface finishing, with a primary focus on industrial robot polishing and tool condition monitoring. His work addresses critical challenges in automated surface processing, particularly the unpredictable tool wear that degrades polishing quality and consistency. Ji’s highly cited review, “Surface polishing by industrial robots: a review” (2023, 72 citations), provides a comprehensive synthesis of the field, establishing foundational knowledge for researchers and engineers alike. In a more recent contribution, he developed an innovative method combining neural ordinary differential equations (neural ODE) with a backpropagation-genetic algorithm (BP-GA) to predict tool wear in real time, enabling timely tool replacement and maintaining uniform surface finish. This work, though early in its citation trajectory (5 citations), demonstrates Ji’s commitment to integrating cutting-edge machine learning with practical manufacturing needs. His research not only advances the theoretical understanding of robotic polishing dynamics but also offers actionable solutions for industry, positioning him as a key figure in the evolution of smart, adaptive manufacturing systems.