Samuel Ayankoso
Papers
2
Total Citations
16
H-Index
2
About
Samuel Ayankoso is a rising researcher at the forefront of smart manufacturing, specializing in the condition monitoring and predictive maintenance of industrial collaborative robots (cobots). His work directly addresses a critical industry challenge: ensuring the reliability and safety of cobots as they become central to flexible, human-centric production lines. Ayankoso’s major contributions lie in developing cutting-edge, data-driven frameworks that integrate digital twins and artificial intelligence. His 2024 paper, “A Hybrid Digital Twin Scheme for the Condition Monitoring of Industrial Collaborative Robots,” proposes a novel approach for real-time health assessment, while his companion work, “Artificial-Intelligence-Based Condition Monitoring…,” focuses on robust anomaly detection that can adapt to changing robot trajectories. Both papers have already garnered 8 citations each, signaling strong early impact in this fast-moving field. By pioneering these intelligent prognostic systems, Ayankoso is paving the way for more autonomous, resilient, and safer manufacturing environments, marking him as a key emerging voice in the future of Industry 4.0.
Research Focus
Key Achievements
Top Papers
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