AI-powered material sorting
Boosting efficiency in plastic recycling
Recycling plays a key role in creating a functioning circular economy for plastics. One of the biggest challenges lies in the accurate sorting of highly heterogeneous material streams – as only high-quality recyclates can be reused in new products. Modern technologies from Sesotec based on Artificial Intelligence (AI), are now opening up new dimensions in sorting performance.
Intelligent sorting for complex requirements
Conventional sensor technologies often reach their limits, especially when it comes to distinguishing between similar types of plastic or complex material combinations. AI-powered solutions of Sesotec, such as NIR-Ai and OBJECT-Ai enable significantly more precise classification, paving the way for higher-quality recyclates and more efficient processes, says the company.
NIR-Ai analyses the near-infrared (NIR) spectra reflected by plastics and uses AI to accurately assign them to specific materials. This allows for reliable identification of monolayer vs. multilayer trays, detection of PA layers in bottles, and identification of specific additives. This distinction is essential for food-grade recycling and helps to prevent downcycling. In addition, NIR-Ai enables the reliable detection of PET full-sleeve bottles, which previously posed a significant challenge for automated sorting systems due to their visual similarity to other packaging types.
OBJECT-Ai, on the other hand, is based on object recognition using Artificial Intelligence and enhances sorting based on shape, colour, and texture. This technology is claimed to detect the smallest differences, such as contaminants or misclassified items.
A key development is the AI-based classification of PET articles into food-grade and non-food-grade categories. OBJECT-Ai uses key visual features like dosing caps, spray heads, bottle shapes, or label design to differentiate product types. Visually similar objects, such as ketchup and dishwashing liquid bottles can automatically be assigned to the correct material class, ensuring compliance with regulatory thresholds for recycled food-grade PET.
Added value for customers and the environment
By integrating AI into the sorting process, recycling companies benefit from consistently high efficiency and improved material quality. At the same time, valuable resources are conserved – an important step toward a more sustainable circular economy.
The application areas for AI-based sorting technologies are diverse, from polymer differentiation and food/non-food recognition to the detection of colours, metals, and multilayer films.
Looking ahead: more intelligence for sorting
In the future, various sensor technologies could be interconnected via AI to further enhance sorting performance. One promising approach is instance segmentation, which enables individual objects in complex or overlapping scenes to be recognised and treated separately. More precise activation of sorting valves could significantly increase sorting accuracy and efficiency.
“With AI-based systems such as NIR-Ai and OBJECT-Ai, we’re able to significantly increase the accuracy and efficiency of sorting processes,” explains Andreas Hanus, Head of Development AI at Sesotec. “By leveraging machine learning algorithms for spectral and object data analysis, we can reliably differentiate between complex material types and structures, enabling a higher quality recyclate output and optimising the overall process performance.”