Jun-Hua Duan

Papers

Total Citations

283

H-Index

About

Dr. Jun-Hua Duan is a leading researcher at the forefront of intelligent manufacturing and industrial digitalization, with a primary focus on predictive maintenance and digital twin technology. His seminal 2023 work, "Overview of predictive maintenance based on digital twin technology," has garnered over 283 citations, establishing him as a pivotal voice in transforming how industries approach equipment reliability. Duan’s major contribution lies in systematically bridging the gap between traditional, reactive maintenance strategies and the emerging paradigm of data-driven, real-time virtual modeling. By synthesizing how digital twins can simulate, monitor, and forecast asset degradation, his research provides a foundational framework for reducing downtime and operational costs across manufacturing sectors. This work has become essential reading for engineers and scholars seeking to implement Industry 4.0 solutions. Beyond this landmark review, Dr. Duan continues to advance the integration of cyber-physical systems, shaping how factories leverage simulation and sensor data for proactive decision-making. His insights are driving a critical shift from periodic maintenance to condition-based, intelligent asset management.