Sergio Terzi
Papers
5
Total Citations
64
H-Index
4
About
Sergio Terzi is a leading researcher at the forefront of intelligent manufacturing and circular economy, specializing in the disassembly of End-of-Life (EOL) products through advanced Human-Robot Collaboration (HRC). His work is pivotal in addressing the environmental challenges of e-waste, particularly in electric vehicle battery recycling. Terzi’s major contributions lie in developing sophisticated AI-driven frameworks that optimize disassembly processes. He has pioneered the use of Q-learning-based particle swarm optimization for dynamic task allocation (25 citations) and introduced multi-scenario digital twin-driven planning using dynamic time Petri-nets and heterogeneous multi-agent deep Q-learning networks (21 citations). His innovative integration of Large Language Models with Graph Convolutional Networks creates reasoning systems that enable robots to understand complex spatial-temporal disassembly operations (9 citations). Additionally, his knowledge graph-driven process reasoning (6 citations) and digital twin platforms for intelligent disassembly (3 citations) represent groundbreaking steps toward sustainable manufacturing. With a rapidly growing citation impact, Terzi’s work is essential reading for researchers in green manufacturing, AI-driven robotics, and circular economy, offering practical solutions for efficient, automated recycling that reduces environmental harm while maximizing resource recovery.
Research Focus
Key Achievements
Top Papers
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