OMR SIGNED
X-Ray Fluorescence, Shape recognition & Machine Learning for Efficient and Economic Recycling of Mixed Metals from Co-mingled Waste.
Total Cost €
0EC-Contrib. €
0Partnership
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0OMR project word cloud
Explore the words cloud of the OMR project. It provides you a very rough idea of what is the project "OMR" about.
Project "OMR" data sheet
The following table provides information about the project.
| Coordinator |
RECRESCO LIMITED
Organization address contact info |
| Coordinator Country | United Kingdom [UK] |
| Total cost | 3˙002˙468 € |
| EC max contribution | 2˙101˙728 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-EIC-SMEInst-2018-2020-3 |
| Funding Scheme | SME-2b |
| Starting year | 2020 |
| Duration (year-month-day) | from 2020-04-01 to 2022-03-31 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | RECRESCO LIMITED | UK (NOTTINGHAM) | coordinator | 2˙101˙728.00 |
Map
Project 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.
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The information about "OMR" are provided by the European Opendata Portal: CORDIS opendata.