PETnology Europe 2024_summiteer

AUTOSORT TM with GAINnext TM. Photo credit: TOMRA

Deep Learning

TOMRA achieves worldwide industry first with groundbreaking food-grade plastics sorting solution

3:50 min Sorting and collection
Mülheim-Kärlich, Germany

TOMRA Recycling has announced the launch of 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 AI.

Thanks to TOMRA’s continued investment in GAIN – the company’s deep learning-based sorting add-on for its world-renowned AUTOSORT™ units – it is now 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 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.

However, TOMRA’s GAIN technology – today rebranded GAINnext™ to pay tribute to the product’s significant evolution – resolves all of 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.​

Purity levels of over 95%

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. And the degrees of purity that this solution is achieving – upwards of 95% for the packaging applications in customers’ plants across UK and Europe – will open up opportunities for new revenue streams for TOMRA’s customers.  

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

Bottle-to-bottle quality

Dr. Volker Rehrmann, EVP, Head of TOMRA Recycling, comments: “We have used AI technology to improve sorting performance for decades, but this latest groundbreaking application marks another industry first for us. 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. With its sophisticated use of deep learning, GAINnextTM enables food-grade sorting and bottle-to-bottle quality, tasks that have posed significant challenges for our industry for many years. 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. At TOMRA, we're proud to be driving the change in sorting.”

Solving the most complex sorting tasks

Indrajeed Prasad, Product Manager Deep Learning at TOMRA Recycling, adds: “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, GAINnextTM  solves even the most complex sorting tasks. 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.”

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