Zerrendatu honen arabera: egilea "0450c040dfb1b80c9c3308e40a3eaf5d"
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Active Power Optimization of a Turning Process by Cutting Conditions Selection: A Q-Learning Approach
Duo, Aitor; Reguera-Bakhache, Daniel; Izagirre, Unai; Aperribay Zubia, Javier (IEEE, 2022)In the context of Industry 4.0, the optimization of manufacturing processes is a challenge. Although in recent years many of the efforts have been in this direction, there is still improvement opportunities in these ... -
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
Izagirre, Unai; Serradilla, Oscar; Olaizola, Jon; Zugasti, Ekhi; Aizpurua Unanue, Jose Ignacio (MDPI, 2023)In this paper, a set of best practice data sharing guidelines for wind turbine fault detection model evaluation is developed, which can help practitioners overcome the main challenges of digitalisation. Digitalisation is ... -
An interpretable operational state classification framework for elevators through Convolutional Neural Networks
Olaizola Alberdi, Jon; Izagirre, Unai; Serradilla Casado, Oscar; Zugasti, Ekhi; Mendicute, Mikel; Aizpurua Unanue, José Ignacio (Wiley, 2025)Ensuring the safe, reliable, and cost-efficient operation of transportation systems such as elevators is critical for the maintenance of civil infrastructures. The ability to monitor the health state and classify different ... -
A methodology and experimental implementation for industrial robot health assessment via torque signature analysis
Izagirre, Unai; andonegui, imanol; Egea, Aritz; Zurutuza, Urko (MDPI AG, 2020)This manuscript focuses on methodological and technological advances in the field of health assessment and predictive maintenance for industrial robots. We propose a non-intrusive methodology for industrial robot joint ... -
Novel automated interactive reinforcement learning framework with a constraint-based supervisor for procedural tasks
Elguea Aguinaco, Iñigo; Aguirre, Aitor; Izagirre, Unai; Inziarte Hidalgo, Ibai; Bogh, Simon; Arana-Arexolaleiba, Nestor (Elsevier, 2025)Learning to perform procedural motion or manipulation tasks in unstructured or uncertain environments poses significant challenges for intelligent agents. Although reinforcement learning algorithms have demonstrated positive ... -
A practical and synchronized data acquisition network architecture for industrial robot predictive maintenance in manufacturing assembly lines
Izagirre, Unai; andonegui, imanol; Zurutuza, Urko (Elsevier Ltd., 2021)This manuscript presents a methodology and a practical implementation of a network architecture for industrialrobot data acquisition and predictive maintenance. We propose a non-intrusive and scalable robot signalextraction ... -
Towards data-driven predictive maintenance for industrial robots
Izagirre, Unai; Izagirre, Unai (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2021)The automation of industry in general and the use of industrial robots in assembly lines in particular has considerably increased in the last two decades. Although industrial robots have received significant attention from ... -
Towards manufacturing robotics accuracy degradation assessment: A vision-based data-driven implementation
Izagirre, Unai; andonegui, imanol; Eciolaza, Luka; Zurutuza, Urko (Elsevier, 2021)In this manuscript we report on a vision-based data-driven methodology for industrial robot health assessment. We provide an experimental evidence of the usefulness of our methodology on a system comprised of a 6-axis ...
