For CARTIF, the fourth industrial revolution allows the production assets to be interconnected in the factory and in the value chain (suppliers, customers, logistics, etc.) so that responsible managers of the factory can give an agile response to different changes such as unexpected breakdowns or variations in product specifications by the customer.
CARTIF, as a technology transfer center, works on the development of innovative enabling technologies that allow manufacturing companies to advance in the application of the “Industry 4.0” philosophy in their production processes, with the ultimate goal of improving the efficiency of their processes and not simply as a mere application of “cool” technologies.
- Research in modelling and diagnosis in predictive maintenance of actives under varying operating conditions.
- Research in prediction of actives life cycle models under constant operating speeds.
- Development of data acquisition systems for the supervision of processes.
- Development of new sensors addressed to IoT.
- Optimisation of operations management in manufacturing.
- P201030006: Dispositivo robotizado para la inspección de conductos.
- P201430965: Sistema para control y gestión de carga de vehículos eléctricos.
- P201430972: Dispositivo y procedimiento para medición de vibraciones.
Networks and Platforms
- A.SPIRE: A.SPIRE.
- BDVA: Big Data Value Associaton.
- CIGRE Comité España: International Council of Large Electric Systems. Comité España.
- EFFRA: European Factories of the Future Research Association.
- euRobotics AISBL: euRobotics aisbl (Association Internationale Sans But Lucratif).
- Reñones, A; Vega, C.; de la Rosa, M. Vibration-Based Smart Sensor for High-Flow Dust Measurement. Sensors 2023, 23, 5019. https://doi.org/10.3390/s23115019
- Cristina Vega, Daniel Gomez, Aníbal Reñones, Cognitive Solutions in Process Industry: H2020 CAPRI Project, Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics – ETCIIM, pag 267-278, 2022, ISBN 978-989-758-612-5; ISSN 2184-9285; DOI 10.5220/0011562 https://www.scitepress.org/PublicationsDetail.aspx?ID=qgHFkJiaFgs=&t=1
- Marta Galende y Aníbal Reñones; Ai4Manufacturing toolkit: la colección de tecnologías, herramientas y plataformas de inteligencia artificial del proyecto Ai Regio para la industria manufacturera; Proceedings of the V Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation; 2023-01-15, DOI: 10.14201/0aq03374352
- Laura Sanz, Marta Galende, Aníbal Reñones, Antonio Corral; Visualización inteligente para máquinas-herramienta: soporte a la toma de decisiones; V Taller sobre Tecnologías de la Información y la Comunicación Disruptivas para la Innovación y la Transformación Digital; DOI: https://doi.org/10.14201/0AQ03376981
- Reñones, A., & Galende, M. (2020). F.A.I.R. open dataset of brushed DC motor faults for testing of AI algorithms. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 9(4), 83-94. https://doi.org/10.14201/ADCAIJ2020948394
- Reñones, Anibal & Dalle Carbonare, Davide & Gusmeroli, Sergio. (2018). European Big Data Value Association Position Paper on the Smart Manufacturing Industry: Smart Services and Business Impact of Enterprise Interoperability. 10.1002/9781119564034.ch22.
- M.I. Rey, M. Galende, M.J. Fuente, G.I. Sainz-Palmero, Multi-objective based Fuzzy Rule Based Systems (FRBSs) for trade-off improvement in accuracy and interpretability: A rule relevance point of view., Knowledge-Based Systems, Volume 127, 2017, Pages 67-84.
- Saludes-Rodil, S.; Baeyens, E.; Rodríguez-Juan, C.P. Unsupervised Classification of Surface Defects in Wire Rod Production Obtained by Eddy Current Sensors. Sensors 2015, 15, 10100-10117.
- Villa Montoya, Luisa & Reñones, Anibal & Perán, José & Miguel, Luis. (2012). Statistical fault diagnosis based on vibration analysis for gear test-bench under non-stationary conditions of speed and load. Mechanical Systems and Signal Processing. 29. 436–446. 10.1016/j.ymssp.2011.12.013.
- Villa Montoya, Luisa & Reñones, Anibal & Perán, José & Miguel, Luis. (2011). Angular resampling for vibration analysis in wind turbines under non-linear speed fluctuation. Mechanical Systems and Signal Processing. 25. 2157-2168. 10.1016/j.ymssp.2011.01.022.
Fernando Gayubo Rojo
Head of Industrial and Digital Systems Division
Aníbal Reñones Domínguez
Head of Industry 4.0 Area
PREDICTIVOdB seeks to develop an innovative solution for the maintenance of wind farms that is quick to implement and has low energy and economic requirements.
INTELIFER consists of the optimisation of the process and products of a granulated NPK fertiliser manufacturing line with the support of Artificial Intelligence.
The overall objective of s-X-AIPI (self-X Artificial Intelligence for European Process Indsutry digital transformation) is to research, develop, test and experiment an innovative toolset of custom trustworthy self-X AI technologies and applications.
PhotonHub Europe is the unique european Hub (DIH) in photonic that integrates the best technologies, facilities and knowledge in photonics as well as the experience of 53 partners of all Europe. The result is the creation of a unique window that offers a huge variety of support resources for industry to accelerate the integration of photonic in its products and processes.
AI REGIO project aims at supporting AI-driven Digital Transformation of European Manufacturing SMEs, by up-scaling and coordinating different regional smart specialization strategies, by integrating DMPs and DIHs.
Transforming Transport project demonstrated, in a realistic, measurable an replicable wway the transformations that Big Data can bring to the mobility and logistics market. TT adress 13 pilots in 7 domains.
AI4EU project aims to make available to users resources based on Artificial Intelligence (AI) that facilitate scientific research and innovation.
Lashare conducted 28 Laser-based Equipment Assessments (LEA-Laser-based Equipment Assessments) addressing a broad range of laser applications.
Smart Factory project has addressed industrial research and technological validation of advanced data and information management systems for manufacturing industries in Castilla y León.
DISRUPTIVE is a cross-border cooperation project which strives to promote and strengthen the collaboration, exchange and scientific production of the Digital Innovation Hubs (DIHs) located in Castilla y León and in the North of Portugal.