Industry 4.0

innovation procceses


Industry 4.0


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.

Activity fields

  • 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


  • 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.

Reference clients:


Fernando Gayubo Rojo

Fernando Gayubo Rojo

Head of Industrial and Digital Systems Division
Aníbal Reñones Domínguez

Aníbal Reñones Domínguez

Head of Industry 4.0 Area

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