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Project

COGNITWIN

Cognitive Digital Twin

Cognitive Digital Twin

This project aims to develop the next generation of the digital twin, which is self-learning and proactive. This means firstly, it learns from existing, real data to run like processes. Secondly, it can adapt to changes in the process through self-learning. And thirdly, it recognizes problems before they arise, so that all processes always work at approximately the optimum. To achieve this, the latest technologies from the fields of Big Data, Databases, IoT, Smart Sensors, Hybrid Modelling, Machine Learning and AI are used. The main objective is to support the process optimization of the European industry. And also to further promote technology in Europe.

Partners

SINTEF AS, Hydro Aluminium Deutschland GmbH, SHI FW Energia Oy, Sidenor Aceros Especiales Europa S.L., Elkem ASA, Saarstahl AG, Noksel Steel Pipe Company, DFKI, Fraunhofer Gesellschaft, University of Oulu, Cybernetica AS, Nissatech Innovation Centre, TEKNOPAR Industrial Automation, Scortex

Sponsors

EU - European Union

EU - European Union

Publications about the project

Maria Luschkova; Christian Schorr; Tim Dahmen

In: Proceedings of the International Conference on NDE 4.0. International Conference on NDE 4.0 (NDE 4.0), October 24-27, Berlin, Germany, DGzfP, 2022.

To the publication

Christian Schorr; Payman Goodarzi; Fei Chen; Tim Dahmen

In: Antonio Fernández-Caballero (Hrsg.). Applied Sciences, Vol. 11 - Special Issue on Explainable AI, No. 5, Pages 2199-2215, MDPI, Basel, 3/2021.

To the publication

Pierre Gutierrez; Maria Luschkova; Antoine Cordier; Mustafa Shukor; Mona Schappert; Tim Dahmen

Quality Control by Artificial Vision 2021, 2021.

To the publication