This repository is maintained by the Digitalisation Group from the CFAA, a research centre from the University of the Basque Country. Currently, the research group is formed by Dr. Unai López-Novoa, Associate Professor of Computer Science at the University of the Basque Country; Dr. Leonardo Sastoque-Pinilla, doctoral researcher and coordinator of IT and R&D projects; and BsC. Endika Tapia-Fernández, researcher on big-data and data systems management topics.
- High performance computing
- Scalable data processing systems
- Industrial communication protocols
- Cloud and edge computing
- Heterogeneous and emerging architectures
- Energy efficient computing
2024
- Tapia, E., Lopez-Novoa, U., Sastoque-Pinilla, L., & López-de-Lacalle, L. N. (2024). Implementation of a scalable platform for real-time monitoring of machine tools. Computers in Industry, 155, 104065.
- Sendino, S., Sastoque-Pinilla, L., del Olmo, A., & de Lacalle, L. N. L. (2024). Tool Fracture Detection in Electromechanical Broaching Through Machine Sensor. Procedia CIRP, 122, 994-999.
2023
- Aldekoa, I., del Olmo, A., Sastoque-Pinilla, L., Sendino-Mouliet, S., Lopez-Novoa, U., & de Lacalle, L. N. L. (2023). Early detection of tool wear in electromechanical broaching machines by monitoring main stroke servomotors. Mechanical Systems and Signal Processing, 204, 110773.
- Tapia, E., Sastoque-Pinilla, L., Lopez-Novoa, U., Bediaga, I., & López de Lacalle, N. (2023). Assessing industrial communication protocols to bridge the gap between machine tools and software monitoring. Sensors, 23(12), 5694.
- Sen, S., Nielsen, S. M., Husom, E. J., Goknil, A., Tverdal, S., & Pinilla, L. S. (2023, May). Replay-driven continual learning for the industrial internet of things. In 2023 IEEE/ACM 2nd International Conference on AI Engineering–Software Engineering for AI (CAIN) (pp. 43-55). IEEE.
2022
- Tapia, E., Sastoque-Pinilla, L., De Lacalle, N. L., & Lopez-Novoa, U. (2022, July). Towards real time monitoring of an aeronautical machining process using scalable technologies. In 2022 7th International Conference on Smart and Sustainable Technologies (SpliTech) (pp. 1-6). IEEE.
- Del Olmo, A., De Lacalle, L. L., De Pissón, G. M., Pérez-Salinas, C., Ealo, J. A., Sastoque, L., & Fernandes, M. H. (2022). Tool wear monitoring of high-speed broaching process with carbide tools to reduce production errors. Mechanical Systems and Signal Processing, 172, 109003.
2021
- Del Olmo, A., de Pissón, G. M., Sastoque, L., Fernández, A., Calleja, A., & De Lacalle, L. L. (2021, October). Merging complex information in high speed broaching operations in order to obtain a robust machining process. In IOP Conference Series: Materials Science and Engineering (Vol. 1193, No. 1, p. 012079). IOP Publishing.
- Machine consumption models for energy efficiency.
- Virtual sensors for machine monitoring.
- Deployment of an architecture for the homogenization of manufacturing data.
- Embedded systems for monitoring cooling systems for machining processes.
- Machine learning for automatic tool wear monitoring.
- Big data platform for distributed processing systems (EDM, Broaching, etc.)
- Study of industrial communication protocols (Profinet, Profibus, MQTT, etc.)
- Big data for technology monitoring.
- Sustainability and Environmental Impact Study of the CFAA using an Intelligent Sensor-based Approach.
