The CIRIAMET project develops and evaluates artificial intelligence models on a laboratory scale to identify, sort and recover valuable metals in the end-of-life vehicle recycling process.
The CIRIAMET project, in which the GAIKER Technology Centre, a member of the Basque Research & Technology Alliance, BRTA, is participating, has been created in order to promote circularity in the recycling of hybrid and electric vehicles.
The main objective of this project is to develop technologies based on artificial intelligence to identify, sort and recover valuable metals in the recycling process of the new generation of end-of-life vehicles (ELVs).
The metallic fractions generated in waste recycling processes do not have a homogeneous chemical composition as they are made up of a mixture of different alloys. Therefore, the metallurgical recovery of these fractions results in metal products that do not meet the requirements for certain industrial applications. CIRIAMET was launched in 2024 to address this issue and to recover secondary raw materials of high value to industry.
In this research, high purity concentrates of key metals or streams of improved quality will be obtained by automatically sorting complex metal scrap, using artificial vision, spectroscopic analysis techniques and data analysis algorithms based on artificial intelligence and the subsequent automated separation. This will lay the foundations for the development of more efficient metallurgical processes, enabling the circularity of metal resources contained in waste in high added value applications (upcycling).
Funded by the Basque Government's Department of Industry, Energy Transition and Sustainability as part of its ELKARTEK 2024 aid programme for collaborative research in strategic areas, this project involves seven actors from the Basque Science, Technology and Innovation Network, including GAIKER, whose work will focus on the:
- Automatic sorting of aluminium alloys contained in non-ferrous fragments.
- Intelligent localisation on conveyor belts of scattered unwanted materials in heterogeneous scrap fragmentation flows as a preliminary step to their automated extraction.
- Intelligent location of union elements in out-of-use lithium-ion batteries to support automated disassembly operations.
GAIKER will also participate in the study of the impact that the project's technologies may have on the circularity and sustainability of the processes for recovering metals from end-of-life vehicle scrap and lithium-ion batteries, as well as their effect on the rest of the value chain.
In CIRIAMET, advanced artificial vision, hyperspectral vision and laser-induced plasma spectroscopy solutions combined with image and spectroscopic data analysis models based on machine learning and deep learning algorithms are being researched and evaluated on a laboratory scale to carry out automatic recognition of target materials.
Subsidised by the Basque Government
