Imagine if different factories could share a digital 'instruction manual' for their products and machines without worrying about their secrets being stolen. It's like a secure social network for industrial data that helps companies quickly find new suppliers or fix production lines when a crisis hits. This ensures that if one part of the chain breaks, the rest can adapt instantly using shared digital twins.
Manufacturing companies struggle to maintain production when supply chains break because their data is siloed and they lack secure ways to share real-time information with partners without losing control of their intellectual property.
A set of open-source toolkits for 'Data as a Product' management and a Digital Twin Ops framework for optimizing cognitive twins in multi-cloud environments.
If you are an EV manufacturer dealing with battery supply chain disruptions — this project developed a data-driven value ecosystem that allows for rapid reorganization of supply chains and faster decision-making to maintain production continuity.
If you are a component supplier dealing with strict data sovereignty and privacy requirements — this project developed a legal and technical framework for 'Data as a Product' that ensures secure, transparent data management across multi-cloud environments.
If you are an SME dealing with the high cost of implementing AI and digital twins — this project developed open-source toolkits and upskilling programs that democratize access to cognitive digital twin operations.
Based on available project data, specific pricing for the end-user is not listed, but the project utilizes open-source toolkits to lower the barrier for SME adoption.
Yes, the project is designed for large-scale trials across various sectors including automotive and aeronautics, utilizing multi-cloud and edge environment deployments.
The project emphasizes the use of open-source toolkits and establishes a legal framework for data ownership and protection within the data ecosystems.
The system is built to respect European digital values regarding privacy, trust, and sovereignty through a dedicated legal framework for data ecosystems.
The project provides data connection profiles, containers, and a reference framework for big data pipelines to ensure interoperability across different factory environments.
The consortium is heavily weighted toward industrial application, with 18 industry partners representing 53% of the 34 total members. This strong private-sector presence, combined with 9 research entities and 6 universities across 13 countries, suggests the project is driven by commercial viability and real-world industrial requirements rather than pure academic theory.
Contact ASOCIACION DE EMPRESAS TECNOLOGICAS INNOVALIA in Spain
Contact us to find the specific open-source toolkits developed by RE4DY for your factory.
