ANR GEMINI3D
Digital Twins for 3D Printing
| Acronym | GEMINI3D |
| Title | Digital Twins for 3D Printing |
| Funding | France 2030 (ANR-BPI France) |
| Start | avril 2024 |
| End | avril 2026 |
| Budget | 1.5 million € |
| Partners | Université de Bretagne Sud (UBS) - ENSIBS, IMT Atlantique, ENSTA Bretagne, EdgeMind, UBS - ComposiTIC Technological Platform |
| Coordinator | Université de Bretagne Sud (UBS) - ENSIBS |
| ANR Link | https://anr.fr/ProjetIA-23-INDF-0001 |
The GEMINI3D project aims to develop a prototype platform, GEMINI3D, dedicated to the demonstration, experimentation, and training for digital twins and 3D printing technologies. This initiative is a collaborative effort between academic institutions and industry partners, leveraging their respective expertise to create a comprehensive and dynamic environment for exploring and validating digital twin technologies. The project is strategically positioned to complement existing initiatives and address the growing need for advanced, interactive, and real-time modeling solutions in the industry.
Challenges
The primary challenges addressed by the GEMINI3D project include the complexity of integrating diverse models and tools, ensuring real-time interaction and feedback, and managing the heterogeneity of data sources and formats. The project must also overcome the technical hurdles of developing a user-friendly interface that can accommodate both novice and expert users, while ensuring the platform’s scalability and adaptability to various industrial applications. Additionally, the project aims to foster collaboration and knowledge sharing among partners, ensuring that the developed solutions are both innovative and practical for real-world applications.
WP4: Model Interoperability for Digital Twins
Work Package 4 (WP4) focuses on defining the interoperability of models within the digital twin framework. This involves creating a common ontology and data architecture that allows different models and data sources to communicate seamlessly. The goal is to ensure that the digital twin can integrate various data streams and models, providing a coherent and unified view of the system being modeled. This interoperability is crucial for the effective functioning of the digital twin, enabling real-time simulations, predictions, and decision-making support. The outcomes of WP4 will include a robust framework for model interoperability, based on the mature OpenFlexo technology, guidelines for data integration, and demonstrations of the integrated digital twin.
