Te-Jen Chang
Papers
1
Total Citations
13
H-Index
1
About
Te-Jen Chang is a leading researcher in electromechanical integration, industrial IoT, and intelligent control systems, with a focus on advancing smart factory automation. His most-cited work, a 2022 study, introduces a low-cost, high-efficiency framework for unmanned chemical factories, combining convolutional neural networks (CNNs) and fractional-order PID (FOPID) controllers to enhance operational safety and productivity during the COVID-19 pandemic. This paper, with 13 citations, demonstrates his ability to address real-world industrial challenges by integrating ultra-low-cost IoT technologies with a three-layer blockchain network architecture for secure, private data management. Chang’s contributions lie in bridging theoretical control design with practical, cost-effective implementations, offering scalable solutions for resilient manufacturing. His work has been recognized for its timely relevance, particularly in pandemic-era industrial automation, and continues to influence research on decentralized, AI-driven factory systems. By prioritizing affordability and efficiency, Chang’s innovations pave the way for broader adoption of smart technologies in resource-constrained settings, making him a notable figure in the evolution of Industry 4.0.
Research Focus
Key Achievements
Top Papers
- 1