Papers
13
Total Citations
454
H-Index
10
About
Fei Tao is a prominent researcher at the forefront of smart manufacturing, digital twins, and human-robot collaboration, whose work has fundamentally shaped how industries conceptualize intelligent production systems. With contributions spanning cloud manufacturing, robotic disassembly, and augmented reality-driven assembly, Tao has consistently bridged the gap between cutting-edge computational methods and real-world industrial applications. Among his most influential contributions is his work on Digital Twin frameworks for smart manufacturing and Industry 4.0, which has garnered 48 citations, alongside pioneering research on human-centric collaborative assembly systems integrating wearable AR devices and Digital Twins, cited 77 times. His robotic disassembly re-planning research, employing a novel two-pointer detection strategy and super-fast bees algorithm, has accumulated 81 citations, reflecting its practical significance in end-of-life product recycling. Tao's research increasingly explores the intersection of artificial intelligence and systems engineering within Industry 5.0 and the industrial metaverse, demonstrating remarkable forward-thinking vision. His deep learning-based auto-sorting systems and biologically inspired smart product design further illustrate the breadth of his expertise. Collectively, his body of work represents a vital intellectual foundation for researchers and engineers navigating the evolving landscape of intelligent, human-centered manufacturing.
Research Focus
Key Achievements
Top Papers
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- 4A consistency method for digital twin model of human-robot collaboration53 citations · 2022
- 5Digital twin towards smart manufacturing and industry 4.048 citations · 2020
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- 7Biologically Inspired Design of Context-Aware Smart Products25 citations · 2019
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