Lin Ling

Papers

Total Citations

117

H-Index

About

Lin Ling is an emerging researcher at the intersection of artificial intelligence and advanced manufacturing systems, with a focused expertise in predictive maintenance and intelligent industrial automation. Their most notable contribution, the 2023 paper "Data-driven and Knowledge-based predictive maintenance method for industrial robots for the production stability of intelligent manufacturing," has already accumulated an impressive 117 citations in a short period, signaling significant influence within the field. This work presents a hybrid methodological framework that integrates data-driven techniques — such as machine learning and sensor analytics — with structured domain knowledge to anticipate and prevent failures in industrial robotic systems. By addressing production stability challenges in intelligent manufacturing environments, Lin Ling's research directly bridges the gap between theoretical AI approaches and real-world industrial application. The rapid uptake of this work by the broader research community reflects the urgency and relevance of robust maintenance strategies as smart factories become increasingly prevalent. Lin Ling's contributions position them as a promising voice in the ongoing evolution of Industry 4.0 and cyber-physical production systems.