AI-Driven Project Enhances Plastic Recycling through Advanced Sorting Technologies
The K3I-Cycling project, led by Fraunhofer LBF and 16 partners, employs AI to improve the sorting and recycling of post-consumer plastics, crucial for enhancing material quality. This initiative aims to strengthen the European circular economy by ensuring reliable recyclability and reducing CO₂ emissions.
Theia Market Signal Identification - AI Assisted
The K3I-Cycling initiative is focused on developing AI methods for sorting mixed lightweight packaging waste (LVP), which presents challenges due to its variable composition. The project is funded by the Federal Ministry of Research, Technology, and Space (BMFTR) and targets the optimization of recyclate quality through the Artificial Neural Twin (ANT), mapping the sorting chain from collection to end-user.
Machine learning techniques are used to classify polyolefin recyclates based on aging and impurities, allowing for the creation of quality clusters. Furthermore, DangerSort technology enhances safety by detecting lithium batteries in sorting facilities, enabling more effective recycling and supply of secondary raw materials, which supports environmental goals and the circular economy.
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