Browsing by Author "0450c040dfb1b80c9c3308e40a3eaf5d"
Now showing items 1-11 of 11
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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, Jon; Izagirre, Unai; Serradilla, Oscar; Zugasti, Ekhi; Mendicute, Mikel; Aizpurua Unanue, Jose 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, Íñigo; 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 ... -
Quantitative Analysis of Ambient Temperature Effects on Steptime Variations in Industrial Pneumatic Actuators
Zubieta Ansorregi, Jon; Izagirre, Unai; Eciolaza, Luka (SciTePress, 2025) -
Step-time measurement: A scalable sub-cycle time defining methodology for anomaly detection and predictive maintenance in sequential production lines
Zubieta Ansorregi, Jon; Izagirre, Unai; Eciolaza, Luka; Saez de buruaga Corrales, Asier; GALDOS, Lander (Elsevier, 2025)Sub-cycle time periods from machines in production lines offer valuable insights into component-level health. They enable data-driven condition monitoring without the need for additional sensors. However, the lack of a ... -
Torque-based methodology and experimental implementation for industrial robot standby pose optimization
Izagirre, Unai; Arcin, Gautier; andonegui, imanol; Eciolaza, Luka; Zurutuza, Urko (Springer Nature, 2020)This manuscript reports on a novel methodology and experimental implementation for industrial robot standby pose optimization. First, we analyze the influence of the standby pose of robots in the reduction of their useful ... -
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 ...
