Imagine if your factory could automatically create a digital map of itself just by looking at its own data, without needing expensive consultants to draw it. This system acts like a smart mirror that tracks every product and part as it moves, making it easy to reuse materials. It's like having a GPS for every single piece of scrap metal or plastic to ensure nothing ever hits the landfill.
Companies struggle to adopt circular economy models because creating Digital Twins is too expensive, requires too many specialized skills, and lacks secure data sharing between partners.
An automated method for generating digital twins from data, an IDS-based secure data space, and 'Green Gateway' hardware for waste-reduction decision making.
If you are a producer dealing with high raw material costs and waste — this project developed automated digital twins that track product lifecycles. This allows you to recover valuable components more efficiently to tap into the $4.5 trillion circular economy growth opportunity.
If you are a supplier dealing with complex value networks and data silos — this project developed an IDS-based common data space. This ensures secure and seamless exchange of manufacturing data between different partners in the supply chain.
If you are a manufacturer dealing with a lack of skilled staff to manage digital systems — this project developed augmented intelligence algorithms. These tools reduce the knowledge gap for workers making decisions at Green Gateways.
Based on available project data, specific pricing is not provided, but the project aims to reduce the current implementation costs associated with traditional system-engineering models.
The project is currently in the research and development phase (2022-2025) with 7 industrial partners involved to ensure the results are exploitable in real-world settings.
Based on available project data, licensing terms are not specified; however, the project uses an International Data Space (IDS) standard for secure data exchange.
It uses a process mining approach to automatically discover models from existing data and integrates novel hardware called Green Gateways into the digital thread.
The project period runs until 2025-11-30, at which point the final results and 17 deliverables will be completed.
The consortium is heavily industry-weighted with a 54% industry ratio, comprising 13 partners across 8 countries. With 7 industrial players and 6 SMEs, the project is strongly geared toward commercial application rather than pure academic research, led by Politecnico di Milano.
Contact Politecnico di Milano regarding the AUTO-TWIN project
Contact us to connect with the AUTO-TWIN consortium for early adoption of automated digital twin tools.
