AI breakthrough allows separation of food- and non-food grade packaging

TOMRA Recycling, has announced the launch of three new applications to separate food-grade from non-food-grade plastics for PET, PP and HDPE.

The breakthrough was made possible by the company’s deep learning technology, a subset of artificial intelligence (AI). GAIN – the company’s deep learning-based sorting add-on for its AUTOSORT units – is making it possible for the first time to quickly and efficiently separate food-grade from non-food-grade plastics for PET, PP and HDPE on a large scale.

Until now, food-grade sorting has proved a real challenge for the industry as food and non-food
packaging are often made of the same material and visually very similar, which makes it difficult for
any traditional sorting system on the market today to differentiate and separate. Hygiene concerns
and increasingly stringent industry regulations add a further layer of complexity to handling food
waste in recycling.

“The use of deep learning technology not only automates manual sorting but also enables the industry to achieve high-quality recyclates through more granular sorting. Thanks to its ability to detect thousands of objects by material and shape in milliseconds, GAINnext solves even the most complex sorting tasks,” said Indrajeed Prasad, product manager deep learning at TOMRA Recycling.

“Plus, with its integrated deep learning software, it offers the opportunity to adapt to future
demands. We are delighted to be able to launch these innovative and much-needed solutions to
meet the ever more stringent quality requirements for sorting outputs, driven by the increasing
demand from consumer brands for more high purity recycled content.”

However, TOMRA’s GAIN technology – rebranded GAINnext – resolves these challenges by 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.​The degrees of purity that this solution is achieving – upwards of 95% for the packaging applications in
customers’ plants – will expand opportunities for new revenue streams for users.

TOMRA is also launching two non-food applications that complement the company’s existing GAINnext solution: a PET cleaner application for even higher purity PET bottle streams and an application for deinking paper for cleaner paper streams.

“We have used AI technology to improve sorting performance for decades, but this latest groundbreaking application marks another industry first for us,” said Volker Rehrmann, EVP, head of TOMRA Recycling.

“AI has the power to transform resource recovery as we know it, and our latest sophisticated applications of deep learning and AI reinforce our position as a pioneer in this field. The use of AI is driving material circularity at a time when it is needed most, with tightening regulations and increasing customer demand for technologically advanced solutions.”

GAINnext’s deep learning technology has been proven in the field. TOMRA was the first in the industry to introduce deep learning technology in 2019 with an application to identify and remove PE-silicon cartridges from polyethylene (PE) streams. An application for wood chip classification soon followed. To date, more than 100 AUTOSORT units with GAINnext are installed at material recovery facilities across the globe.

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.

Feedback from the market on the latest GAINnext developments has been positive. Edward Kosior, founder and CEO of Nextek Ltd and its NEXTLOOPP initiative that aims to create food-grade recycled polymer from advanced mechanical recycling, was among the most recent visitors to TOMRA’s test centre and confirmed: “TOMRA’s ground-breaking AI system has propelled the recycling industry to an exciting pivotal juncture in plastic packaging sorting and creates new opportunities for closing the loop on many plastics in food-grade applications.”