Chengwei Jin

Papers

Total Citations

H-Index

About

Chengwei Jin is a researcher focused on advanced manufacturing and intelligent machining, with a particular emphasis on robotic stone processing. His work integrates machine learning and optimization algorithms to enhance precision and stability in industrial automation. In his most cited study, Jin developed an improved Quantum Particle Swarm Optimization (QPSO) approach to optimize Support Vector Machine (SVM) parameters for predicting milling forces in white marble during robot stone machining. This contribution is critical for improving product quality and process stability, addressing a key challenge in the machining of natural stone materials. By combining soft computing techniques with traditional manufacturing, Jin’s research offers practical solutions for real-time force prediction and adaptive control. With 6 citations, his work has laid a foundation for further innovations in intelligent machining systems. His achievements highlight the growing intersection of artificial intelligence and mechanical engineering, making him a notable contributor to the field of smart manufacturing.