Hamdan Al-Musaibeli

University of Alberta

Papers

3

Total Citations

53

H-Index

2

About

Hamdan Al-Musaibeli is a researcher at the forefront of intelligent manufacturing and robotic repair systems, with a focus on laser cladding and hybrid manufacturing processes. His work centers on developing autonomous, vision-guided methods for repairing high-value industrial components, directly contributing to the circular economy through remanufacturing. Al-Musaibeli’s most influential contribution is a vision-based spatial damage localization method for robotic laser cladding, which enables precise, automated repair of surface defects—a paper that has garnered 34 citations for its practical impact. He also advanced path planning algorithms for robot-assisted cladding, cited 17 times, and developed a feature extraction algorithm for hybrid additive-subtractive manufacturing. By integrating computer vision with robotic control, Al-Musaibeli’s research addresses critical challenges in restoring damaged parts to like-new functionality, reducing waste and extending product lifecycles. His work is essential reading for engineers and researchers in sustainable manufacturing, robotics, and automated repair, offering scalable solutions for industries seeking to close the supply chain loop through intelligent remanufacturing.

Research Focus

Key Achievements

2
H-Index
3
Papers
53
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Vision-based spatial damage localization method for autonomous robotic laser cladding repair processes
34 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Alberta

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago