Imagine a smart factory that can take apart old gadgets like a pro, deciding what to fix and what to recycle. It uses robots that learn how to handle different broken devices and digital passports to track every part. It's like giving a machine the brain and hands of a master technician to breathe new life into old tech.
Companies struggle to profitably recover materials from old electronics because every device is different and disassembly is too slow when done by humans.
A system for robotic disassembly and AI-based product diagnosis, including Digital Product Passports and an educational platform for worker upskilling.
If you are an EV Battery Recycler dealing with inconsistent battery states — this project developed AI-driven diagnosis and robotic disassembly that speeds up component recovery. This reduces manual labor and improves safety during the recycling process.
If you are a Home Appliance Manufacturer dealing with high waste from washing machines — this project developed design guidelines for remanufacturability and robotic inspection. This allows you to refurbish old machines into high-quality second-hand products.
If you are a Network Hardware Provider dealing with outdated modems — this project developed Digital Product Passports and automated disassembly. This ensures secure information flows and efficient recovery of rare materials from old devices.
Based on available project data, specific pricing or implementation costs are not provided.
Yes, the project focuses on industrial automation and will be validated through 4 sectoral pilots, including electric vehicle batteries and industrial robots.
Based on available project data, there are no specific details regarding IP or licensing agreements.
The project uses Digital Product Passports and traceability tools to coordinate supply networks and ensure transparent information flows.
The project runs from 2026-09-01 to 2030-08-31, suggesting that mature solutions will be available toward 2030.
The consortium is heavily weighted toward commercial application, with 7 industry partners (44% ratio) and 3 SMEs. With 16 partners across 11 countries, the project combines academic research from 3 universities and 6 research centers, ensuring a strong bridge between theoretical AI/robotics and real-world industrial deployment.
Contact Technische Universität Dortmund
Contact us to connect with the RESURRECTION consortium for pilot opportunities.
