Global sorting solutions provider, TOMRA Recycling, has launched three revolutionary applications to separate food-grade from non-food-grade plastics for PET, PP and HDPE. The breakthrough was made possible by the company’s intensive research and development in deep learning, a subset of artificial intelligence (AI).
Thanks to TOMRA’s continued investment in GAIN – the company’s deep learning-based sorting add-on for its AUTOSORT™ units – it is now possible to quickly and efficiently separate food-grade from non-food-grade plastics for PET, PP and HDPE on a large scale.
TOMRA’s GAIN technology –rebranded GAINnext™ to pay tribute to the product’s significant evolution – resolves these challenges by further enhancing the sorting performance of the company’s AUTOSORT™ units, so they are capable of identifying objects that are hard and, in some cases, even impossible to classify using traditional optical waste sensors.
By combining its traditional near-infrared, visual spectrometry or other sensors with deep learning technology, TOMRA has developed the most accurate solution available on the market today. The degrees of purity that this solution is achieving – upwards of 95 percent for the packaging applications in customers’ plants – will expand opportunities for new revenue streams for TOMRA’s customers.
TOMRA is also launching two non-food applications that complement the company’s existing GAINnext ecosystem: a PET cleaner application for even higher purity PET bottle streams and an application for deinking paper for cleaner paper streams.
Among the early adopters of the brand-new applications are market-leading plants such as Berry Circular Polymers’ flagship facility in Leamington Spa, Viridor Avonmouth in Bristol – the UK’s largest multi-polymer facility – and the French Nord Pal Plast plant, which is owned by the global Dentis Group.