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X-Ray Fluorescence, Shape recognition & Machine Learning for Efficient and Economic Recycling of Mixed Metals from Co-mingled Waste.

Project description

Finally, an automated system to separate co-mingled metals for recycling

Modern recycling has its roots in the environmental awareness of the 1960s and 1970s, although historically the practice has existed in various forms for thousands of years. Countries have had varying success in trying to organise the separation of materials before pickup to facilitate the process. Despite much progress, high-value metals that are infinitely recyclable are often returned to landfills or lost in the manual sorting process, the only available means to separate the metals so that they can be reused. The EU-funded OMR project is developing a sophisticated identification and separation system for co-mingled waste based on X-ray technology, shape recognition and machine learning. It could revolutionise recycling and rapidly move the EU towards a truly circular economy while saving the energy and natural resources required to mine the metals from the ground.

Objective

Recycling is a key battleground in combating climate change. By reducing the volume of materials that need to be removed from the ground and then processed significant emissions reductions can be achieved. Metals such as Copper, Tin, Aluminium, Gold, Silver and Zinc are infinitely recyclable if properly separated and are key elements in the global economy. Currently these metals cannot be economically recovered from mixed recycling as most recyclers do not have a sustainable solution for separation and recovery of these valuable resources. Therefore, these mixed metals currently either end up being exported to be manually sorted, sent to landfill or lost in the sorting process.
As a result, recycling rates for these crucial materials are far lower than they need to be if the EU is to meet its recycling targets and kickstart the circular economy. The OMR project will create a unique combination of X-Ray Fluorescence (XRF), shape recognition and Machine Learning (ML) techniques to enable efficient and economic recycling of mixed non-ferrous metals from co-mingled waste. This will turn a low value feedstock into several high value output streams which will further increase the advantages of co-mingled collection and allow it to be rapidly rolled out across the EU to help meet the EU’s ambitious 65% recycling target.
Furthermore the project will deliver a sustainable market for mixed metals, provide aerospace and automotive manufacturers with a new source of guaranteed quality non-ferrous metals, divert material from landfill, preserve natural resources, increase recycling rates and create employment opportunities as new facilities are rolled out across the EU. Recresco aim to operate 3 new sorting facilities by year 4 post project, generating €12.1m in additional turnover and creating 106 new direct jobs over the same time period.
The OMR project will therefore transform the recyclability of the non-ferrous metal containing products.

Call for proposal

H2020-EIC-SMEInst-2018-2020

See other projects for this call

Sub call

H2020-EIC-SMEInst-2018-2020-3

Coordinator

RECRESCO LIMITED
Net EU contribution
€ 2 101 728,00
Address
URBAN ROAD 37
NG17 8AP Nottingham
United Kingdom

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
East Midlands (England) Derbyshire and Nottinghamshire North Nottinghamshire
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
€ 3 002 468,75