{"id":88040,"date":"2023-11-22T10:45:00","date_gmt":"2023-11-22T09:45:00","guid":{"rendered":"https:\/\/packaging-journal.de\/?p=88040"},"modified":"2023-11-21T14:50:17","modified_gmt":"2023-11-21T13:50:17","slug":"artificial-intelligence-sorts-plastic","status":"publish","type":"post","link":"https:\/\/packaging-journal.de\/en\/kuenstliche-intelligenz-sortiert-kunststoff\/","title":{"rendered":"Artificial intelligence sorts plastic"},"content":{"rendered":"
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Recycleye, Valoplast and TotalEnergies want to improve the recyclability of polypropylene food packaging. To this end, the companies have launched the joint OMNI research project. The technology is based on artificial intelligence and computer vision.<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The OMNI project is an innovative project that aims to achieve this, AI and machine learning for the identification and separation of PPs<\/strong> food-grade paper from household waste. It is one of seven projects that were successfully selected in October 2020 by Citeo, a company that reduces the environmental impact of household packaging and paper, as part of a call for projects.<\/p>

\u201eThe ability to recycle food-grade PP is a key factor in creating a circular economy for PP packaging. AI is a promising way to achieve this goal.\u201c<\/p>

Alban Cotard<\/strong>, Sales Quality and Development Manager at Valorplast<\/p><\/blockquote>

After 18 months of research, the OMNI project has resulted in an alternative to digital and physical labelling solutions that require system-wide packaging changes. In a demonstration plant, Recycleye developed and trained an AI model<\/strong> based on waste collected from five sites across France, supplied and characterised by Valorplast.<\/p>

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\u201eWe are very excited about the successful application of our robust AI-powered sorting technology on a semi-industrial scale. This application opens up the opportunity to create new markets for recycled plastics and ultimately change the economics of recycling.\u201c<\/p>

Victor Dewulf<\/strong>, CEO of Recycleye<\/p><\/blockquote>

The AI and robot sorting achieved a successful Detection rate of 50 per cent of food-safe material<\/strong> with a purity level of over 95 per cent. This sorting yielded material that was used for further decontamination in a semi-industrial pilot project based on commercially available mechanical recycling technologies. TotalEnergies<\/a> then used its expertise in polymers to produce odourless, clean rPP suitable for high-quality packaging applications.<\/p>

The newly developed process has demonstrated the efficient decontamination of food-grade PP waste sorted using AI and computer vision and opens up new possibilities for the recycling of polypropylene packaging. Nathalie Brunelle<\/strong>, Senior Vice President, Polymers at TotalEnergies, said:<\/p>