Soo‐Hong Min

Papers

Total Citations

279

H-Index

About

Soo-Hong Min is a leading researcher in intelligent manufacturing, with a primary focus on smart machining processes and the integration of machine learning into industrial production. His most influential work, the 2018 review "Smart Machining Process Using Machine Learning: A Review and Perspective on Machining Industry," has garnered 279 citations, establishing a foundational framework for how data-driven algorithms can optimize tool wear monitoring, surface quality prediction, and process parameter selection. Min’s contributions bridge the gap between traditional mechanical engineering and modern artificial intelligence, demonstrating how machine learning models can reduce downtime, improve precision, and enable adaptive control in real-time machining environments. Beyond this seminal paper, his research explores sensor fusion, digital twins, and cyber-physical production systems, offering practical roadmaps for Industry 4.0 adoption. Recognized for his ability to synthesize complex technical landscapes into actionable insights, Min’s work is widely referenced by both academic researchers and industry practitioners seeking to automate and enhance manufacturing efficiency. His perspective pieces are particularly valued for their critical evaluation of emerging technologies, making him a key voice in the ongoing transformation of the machining industry.