Fawzi Gougam
Papers
1
Total Citations
1
H-Index
1
About
Fawzi Gougam is a researcher at the forefront of smart manufacturing and industrial automation, with a specialized focus on data-driven fault diagnosis for robotic systems. His work addresses critical challenges in predictive maintenance and process reliability, particularly for cutting tools in automated production environments. Gougam’s most cited paper, "A data driven fault diagnosis approach for robotic cutting tools in smart manufacturing" (2025), introduces novel methodologies that leverage machine learning and sensor data to detect anomalies in real-time, enhancing operational efficiency and reducing downtime. This contribution is pivotal for the Industry 4.0 paradigm, where intelligent monitoring systems are essential for sustainable manufacturing. Although his citation count is currently modest, his research is gaining traction among peers in mechanical engineering and cyber-physical systems. Gougam’s work exemplifies the integration of computational intelligence with industrial robotics, offering practical solutions for fault detection that are both scalable and cost-effective. As smart factories evolve, his data-driven approaches are poised to become foundational for next-generation manufacturing resilience.
Research Focus
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Top Papers
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