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.
- Diagnosis and prognosis of failures in industrial processes.
- Artificial Intelligence for manufacturing.
- Simulation of production processes through discrete events systems.
- Advanced automatic process control (MPC).
- Traceability in the food industry.
- Advanced sensorization of productive processes.
- Performance optimization of control systems in process industry plants.
- Enablers for the factories of the future.
- Development of predictive maintenance systems.
- 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, 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
Director of Industrial and Digital Systems Division
Aníbal Reñones Domínguez
Industry 4.0 Area Director
AI4EU project aims to make available to users resources based on Artificial Intelligence (AI) that facilitate scientific research and innovation.
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.
The 3DCONS Project (New Construction Processes by means of 3D Printing) focuses on 3D printing technologies in the construction industry and covers several areas: robotics, the search for new materials, process automation, the technological drive of building and the development of design tools based on Building Information Modelling (BIM).
The SHERIFF Project (Hybrid and Economic System of Flexible Integral Facade Rehabilitation) new tools for the energy rehabilitation of buildings.