Collaborative research project OMNI directed by Recycleye, Valorplast, and TotalEnergies to enhance the circularity of polypropylene (PP) food packaging led to ground-breaking results. The new technology based on Artificial Intelligence (AI) and computer vision, coupled with an efficient decontamination process, provides a high-performing marketable solution to tackle the challenge of mechanically recycling polypropylene for food-contact applications.
Project OMNI is an innovative project aiming to leverage AI and Machine Learning for the identification and separation of food-grade PP from household post-consumer wastes. It is one of the 7 projects successfully selected in October 2020 by CITEO, a mission-led company reducing the environmental impacts of household packaging and paper, in the framework of a call for projects.
After 18 months of research, Project OMNI led to an alternative to digital and physical marking solutions which require system-wide packaging changes. In a demonstration unit, Recycleye built and trained an AI model based on wastes collected from 5 locations across France supplied and characterized by Valorplast. The AI and robotic sorting achieved a successful pick rate of 50% of the food-grade material, with >95% purity. This sorting activity produced material used for further decontamination on a semi-industrial pilot based on off-the-shelf mechanical recycling technologies. TotalEnergies then leveraged its polymer expertise to produce odorless, clean rPP suitable for high-end packaging applications.
The novel developed process has demonstrated the efficient decontamination of food-grade PP waste sorted by AI and computer vision and opens new opportunities for circularity of polypropylene packaging.
