Yasmina Hani
Papers
2
Total Citations
17
H-Index
2
About
Dr. Yasmina Hani is a leading researcher in the intersection of industrial robotics, predictive maintenance, and smart manufacturing. Her work focuses on developing machine learning models that enable real-time health assessment and failure prediction for robotic systems, a critical need in the era of Industry 4.0. Her most-cited paper, "A predictive maintenance model for health assessment of an assembly robot based on machine learning in the context of smart plant" (2024, 14 citations), introduces a novel framework for monitoring assembly robots in smart factories, demonstrating how data-driven algorithms can preemptively identify degradation and reduce unplanned downtime. This work is complemented by her study on packaging robots (2023, 3 citations), which extends her approach to different industrial contexts. Dr. Hani’s contributions are particularly notable for bridging theoretical machine learning techniques with practical, deployable solutions for manufacturing environments. Her research has direct implications for improving operational efficiency, reducing maintenance costs, and enhancing the reliability of automated production lines. As a rising voice in predictive maintenance, Dr. Hani is helping shape the future of autonomous, self-aware industrial systems.
Research Focus
Key Achievements
Top Papers
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