Tomra harnesses AI for food-grade plastic sorting tech amid hygiene and regulatory demands
28 Mar 2024 --- Tomra’s Recycling business unit has unveiled a trio of “breakthrough” applications designed to separate food-grade plastics from non-food-grade counterparts for PET, PP and HDPE. The “groundbreaking” achievement, proclaimed as an industry first, results from R&D leveraging deep learning, a subset of AI.
Tomra’s solution, powered by its proprietary deep learning-based “GAINnext” technology, enhances the sorting capabilities of its Autosort units, enabling swift and efficient differentiation on a large scale.
The company combined its traditional near-infrared, visual spectrometry or other sensors with deep learning technology to develop the “most accurate solution available on the market today.”
Traditional sorting systems have grappled with the distinction between food-grade and non-food-grade, compounded by hygiene concerns and stringent regulatory standards governing food waste management in recycling. Tomra’s GAINnext technology boasts purity levels exceeding 95% in packaging applications, asserts the company.
The company’s recycling unit is also launching two non-food applications that complement the company’s existing GAINnext ecosystem: An application for deinking paper for cleaner paper streams and a PET cleaner application for even higher purity PET bottle streams.
Dr. Volker Rehrmann, executive vice president and head of Tomra Recycling, states: “We have used AI technology to improve sorting performance for decades, but this latest 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.”
Material circularity
The applications of Tomra’s technology extend beyond food-grade sorting, encompassing solutions for deinking paper to yield cleaner paper streams and enhancing PET bottle purity for high-quality recycled content. With a focus on achieving bottle-to-bottle quality, Tomra’s innovations signal a step forward in material circularity.
Autosort with GAINnext combines object recognition with traditional sensor-based sorting.“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,” says Rehrmann.
Indrajeed Prasad, product manager for 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, GAINnext solves even the most complex sorting tasks.”
“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.”
Industry testimony
Field-proven over years of deployment, GAINnext technology has garnered acclaim from industry leaders worldwide. More than 100 Autosort units with GAINnext are installed at material recovery facilities worldwide.
Early adopters such as Berry Circular Polymers, Viridor Avonmouth and Nord Pal Plast have embraced these advancements.
Professor Edward Kosior, CEO of Nextek, lauds Tomra’s innovation, recognizing its pivotal role in advancing plastic packaging sorting and fostering opportunities for circularity in food-grade applications.
“Tomra’s groundbreaking AI system, GAINnext, 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. GAINnext is poised to accelerate the most simplified, cost-effective and highly efficient sorting system on the market. We’re immensely proud to see our industry moving forward on this transformational journey,” says Kosior.
Edited by Radhika Sikaria
