GAIKER develops smart AI-based technologies for recycling metals from end-of-life vehicles
The CIRIAMET project develops and evaluates, on a laboratory scale, artificial intelligence models to identify, classify and recover valuable metals in the recycling process of end-of-life vehicles
The CIRIAMET project, in which the GAIKER Technology Centre, a member of the Basque Research & Technology Alliance (BRTA), is participating, has been launched with the aim of promoting 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, classify and recover valuable metals in the recycling process of the new generation of end-of-life vehicles (ELVs).
The metal fractions generated in waste recycling processes do not have a homogeneous chemical composition, as they are composed of a mixture of different alloys. As a result, the metallurgical recovery of these fractions produces metal products that do not meet the requirements for certain industrial applications. To change this and achieve the recovery of high-value secondary raw materials for industry, CIRIAMET was launched in 2024.
In this research, through the automatic classification of complex metal scrap, applying artificial vision, spectroscopic analysis techniques and data analysis algorithms based on artificial intelligence, and subsequent automated separation, high-purity concentrates of key metals or improved quality flows will be obtained. 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 programme of grants for collaborative research in strategic areas, this project involves the participation of seven agents from the Basque Science, Technology and Innovation Network, including GAIKER, whose work will focus on:
- Automatic classification of aluminium alloys contained in non-ferrous scrap.
- Intelligent location on conveyor belts of unsuitable materials dispersed in heterogeneous scrap fragmentation flows as a preliminary step to their robotic extraction.
- Intelligent location of connecting elements in end-of-life lithium-ion batteries to support robotic 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 metal recovery processes from end-of-life vehicle scrap and lithium-ion batteries, as well as their effect on the rest of the value chain.
CIRIAMET is researching and evaluating advanced solutions for artificial vision, hyperspectral vision and laser-induced plasma spectroscopy combined with image analysis and spectroscopic data models based on machine learning and deep learning algorithms to carry out automatic recognition of target materials on a laboratory scale.
