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Using AI to facilitate the transition to a long-term sustainable model

The Endesa Chair in Artificial Intelligence Applications to Data-Driven Maintenance organised the 3rd Technical Conference for the Presentation of Research Results

Promotional banner for the 3rd Technical Day of Research Results Presentation, scheduled for July 10th from 11:00 to 13:00, at Aula 404 of the Superior Technical School of Engineering.

15 July 2024

The Endesa Chair for Applications of Artificial Intelligence to Data-Based Maintenance from ICAI and Endesa held the 3rd Technical Conference for the Presentation of Research Results, a meeting dedicated to disseminating some of the results obtained in the various Master's degree and doctoral thesis projects associated with the Chair and developed during the 2023/2024 academic year.

The director of the chair, Miguel Angel Sanz Bobi, was in charge of inaugurating a conference in which the main results of works on issues such as the current state of development of a Digital Twin for the maintenance management of feedwater pumps based on Machine Learning techniques, the application of Artificial Intelligence techniques to the diagnosis and maintenance of power plants, the characterisation of the behaviour of circulating water pumps using Machine Learning techniques or adversarial neural networks in the IoT world were addressed.


In all the works presented, Artificial Intelligence techniques have been applied to detect and diagnose possible anomalies in the expected behaviour in certain processes and real industrial components that can serve as a basis for rethinking or confirming the current guidelines of the maintenance plans applied.

Endesa and Comillas Pontifical University created the Endesa Chair for Applications of Artificial Intelligence to Data-Based Maintenance with the aim of helping Endesa, in particular, and the energy sector, in general, to take advantage of the opportunities offered by artificial intelligence by generating knowledge and disseminating it to society. Its main objective is to research and disseminate AI applications in the field of maintenance and management of generation assets, with the aim of facilitating the energy transition towards a long-term sustainable model, in line with the United Nations Sustainable Development Goals (SDGs).

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