Baotong Chen

South China University of Technology, Wuhan University of Science and Technology

Papers

Total Citations

348

H-Index

About

Baotong Chen is a leading researcher in smart manufacturing, with a focus on fog computing, multirobot collaboration, and knowledge-driven automation for industrial assembly systems. Their foundational work, "Fog Computing for Energy-Aware Load Balancing and Scheduling in Smart Factory" (2018), has garnered 323 citations, establishing a quantitative energy-aware model that leverages fog computing to enhance computational power and efficiency in smart factories—a critical contribution to sustainable Industry 4.0. Chen further advanced the field with "Knowledge Sharing Enabled Multirobot Collaboration for Preventive Maintenance in Mixed Model Assembly" (2022, 23 citations), integrating IoT and AI to enable intelligent equipment management and flexible production lines. Most recently, their 2025 paper on "Knowledge sharing-enabled low-code program for collaborative robots in mix-model assembly" (2 citations) pioneers accessible, low-code frameworks for robot collaboration, promising to democratize automation. Chen’s work bridges theoretical energy models with practical, scalable solutions for mixed-model assembly, demonstrating significant impact through high citation counts and a trajectory toward user-friendly, collaborative manufacturing systems. Their research is essential for engineers and scholars advancing smart, energy-efficient, and adaptive industrial environments.