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Home   /   Post Doctorat   /   Development of a digital twin of complex processes

Development of a digital twin of complex processes

Artificial intelligence & Data intelligence Factory of the future incl. robotics and non destructive testing Technological challenges


The current emergence of new digital technologies is opening up new opportunities for industry, making production more efficient, safer, more flexible and more reliable than ever. The application of these technologies to the vitrification processes could improve the knowledge of the processes, optimise their operation, train operators, help with predictive maintenance and assist in the management of the process.
The SOSIE project aims at providing a first proof of concept for the implementation of digital technologies in the field of vitrification processes, by integrating virtual reality, augmented reality, IoT (Internet of Things) and Artificial Intelligence.
This project, carried out in collaboration between the CEA and the SME GAMBI-M, is a READYNOV project. GAMBI-M is a company specialised in the reconstruction of complex environments and in digital engineering. The work will be carried out in close collaboration with the CEA teams developing the vitrification processes for nuclear waste.
The project consists of developing a digital twin of 2 vitrification processes, and will be implemented on 2 platforms in parallel, one in a conventional zone, the other in a high activity zone. The first step will be to develop a visual digital twin, the virtual 3D model of each cell, which will allow the user to visit the cells and access any point virtually. Based on this reconstructed model, an "augmented" twin will be developed and connected to the supervisory controller. Finally, the last step will be to develop the "intelligent twin" by exploiting existing databases on the operation of the process. By training machine learning algorithms on these data, a predictive model of nominal operation will be generated.
Publications are expected on the implementation of virtual reality and augmented reality tools on shielded chain operations, as well as on the development of deep learning methods for the assistance to the control of such complex processes.


Département de recherche sur les technologies pour l’enrichissement, le démantèlement et les déchets
Service d’études des technologies pour l’assainissement - démantèlement et l’étanchéité
Laboratoire de la Simulation et des Techniques de Démantèlement
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