Aritz Egea
Papers
1
Total Citations
13
H-Index
1
About
Aritz Egea is a leading researcher in industrial robotics, with a primary focus on predictive maintenance, health assessment, and condition monitoring of robotic systems. His most cited work, "A Methodology and Experimental Implementation for Industrial Robot Health Assessment via Torque Signature Analysis" (2020, 13 citations), introduces a groundbreaking non-intrusive methodology that leverages torque sensor data to create digital signatures for joint health assessment. This approach enables early detection of degradation in industrial robots, significantly reducing downtime and maintenance costs. Egea’s contributions are pivotal in advancing the field of industrial automation, offering practical, data-driven solutions for real-time robot health monitoring. His work has been recognized for its methodological rigor and experimental validation, making it a key reference for researchers and engineers in predictive maintenance. By bridging the gap between theoretical frameworks and industrial implementation, Egea continues to shape the future of smart manufacturing and robotic reliability.
Research Focus
Key Achievements
Top Papers
- 1