One of the key issues that is currently affecting the Waste Electrical and Electronic Equipment (WEEE) management chain is that of battery-caused fires, costing waste management facilities millions of euros every year and acting as a strong barrier to making Europe circular and carbon neutral. Some battery types located inside discarded WEEE, in particular lithium-ion (Li-ion) and nickel-metal hydride (NiMH), can ignite or explode when damaged (e.g., when entered an electronic scrap recycling shredder within a recycling facility).
The GRINNER project, funded through the European Union’s Horizon Europe programme aims at commercialising an autonomous AI-enabled robotic sorting system capable of detecting and removing waste containing batteries from current waste streams before they enter inhospitable-to-battery machines that crush and consolidate waste. The system will comprise:
– the fastest Energy-resolved X-Ray detectors in the market,
– an ML-enabled software module that will analyse X-Ray data and effectively detect waste containing batteries while passing through the waste flow and vision-based pick-and-place robot(s) that will remove the flagged WEEE.
• Build an X-Ray data set of WEEE scrap
• Customisation of the X-Ray system
• Develop the AI software module for detection of batteries within WEEE using X-Ray data.
• Deploy a vision-based robotic solution capable of Picking-and-Placing WEEE
• Develop, integrate and install a prototype system in a WEEE facility
environment to conduct live trials and validate GRINNER
• Explore the potential exploitation of GRINNER as an economically viable, stand-alone product for recycling facilities.