Imagine a digital mirror of a whole factory line that doesn't just track parts, but knows exactly how to reuse every scrap of waste. It's like having a super-intelligent assistant that redesigns products to be eco-friendly before they are even built. This system connects different companies in a supply chain so they can share data and stop wasting materials.
Manufacturing AI is currently fragmented, with tools for maintenance and waste acting in isolation. This prevents companies from seeing the full picture of their waste and sustainability across the entire supply chain.
An AI platform for circular manufacturing that creates interoperable digital twins. It includes tools for AI-based product design and a shared dataspace for sustainability data.
If you are a component manufacturer dealing with high scrap rates in metal stamping — this project developed an AI platform that enables circular twins to maximize the exploitation of production waste.
If you are a hardware brand dealing with difficult product end-of-life recycling — this project developed AI-based product design tools that ensure circularity from the start.
If you are a plant manager dealing with fragmented data across your value chain — this project developed a circular manufacturing dataspace to optimize multi-stage production for sustainability.
Based on available project data, specific pricing or licensing costs are not mentioned as this was an EU-funded research initiative.
Yes, the project collaborated with the Digital Factory Alliance to scale outcomes beyond the initial consortium and launched the Sustainable Manufacturing Initiative for long-term action.
Based on available project data, the specific IP and licensing agreements are not detailed, though it involves a consortium of 21 partners.
The platform uses a circular manufacturing dataspace to combine different data sources from across the entire product life cycle.
The project ran from 2022-07-01 to 2025-06-30, meaning the developed tools are now reaching the end of their primary development phase.
The project shows strong commercial intent with a 52% industry ratio, comprising 11 industrial partners and 7 SMEs across 11 countries. The heavy lean toward industry over academia (only 2 universities) suggests the outputs are designed for immediate factory-floor application rather than theoretical research.
Contact Engineering - Ingegneria Informatica SPA in Italy
Contact us to connect with the Sustainable Manufacturing Initiative for implementation.
