Papers
4
Total Citations
39
H-Index
4
About
Moncef Soualhi’s research lies at the intersection of smart manufacturing, robotics, and prognostics and health management (PHM), with a focus on ensuring reliability and precision in Industry 4.0 systems. His major contributions center on developing data-driven methods for condition monitoring and fault diagnostics, particularly for multi-axis robots and rotating machinery. In his most-cited work, "Intelligent monitoring of multi-axis robots for online diagnostics of unknown arm deviations" (2022, 16 citations), Soualhi addresses a critical challenge in smart manufacturing: detecting small axis deviations that can cascade into significant production errors. He further advances this field with "Health Indicator Construction for System Health Assessment in Smart Manufacturing" (2019, 12 citations), which provides frameworks for assessing overall system health. His work on "Open Heterogeneous Data for Condition Monitoring of Multi Faults in Rotating Machines" (2023, 6 citations) extends these techniques to diverse applications, from railways to renewable energy. By combining real-time diagnostics with robust data-driven models, Soualhi’s research directly supports the high reliability and safety demanded by modern automated production, making his contributions essential for researchers and engineers working toward resilient, intelligent manufacturing systems.
Research Focus
Key Achievements
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