Yong-keun Park

Papers

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About

Yong-keun Park is a leading researcher in sustainable manufacturing and laser-based assembly processes, with a particular focus on energy-efficient production systems for the automotive industry. His work addresses the critical challenge of reducing energy consumption in advanced manufacturing technologies, most notably remote laser welding—an innovative but energy-intensive assembly method. Park’s most cited paper, “Deep Learning Approach of Energy Estimation Model of Remote Laser Welding” (2019), with 11 citations, pioneers the use of deep learning to predict and optimize energy usage in robotic welding systems, moving beyond the average consumption data provided by robot manufacturers. This contribution provides a data-driven framework for manufacturers to achieve significant energy savings without compromising productivity. Park’s research bridges the gap between artificial intelligence and industrial sustainability, offering practical solutions for smart factories. His work is particularly impactful for students and researchers interested in green manufacturing, Industry 4.0, and the application of machine learning to real-world production challenges.