The Challenge of High-Purity rPET Production
Producing food-grade recycled PET (rPET) requires a highly precise sorting of post-consumer PET bottles, ensuring that only food-contact approved plastics are reprocessed. Contamination from non-food PET, coloured plastics, and foreign polymers significantly impacts the safety, performance, and regulatory compliance of rPET. Traditional sorting methods often struggle with accuracy and scalability, making AI-based automation a game-changing solution.
AI-Driven Sorting: A Technological Breakthrough
AI-powered sorting systems analyse bottle characteristics in real-time, dramatically improving sorting precision. Advanced machine learning algorithms and near-infrared (NIR) detection enable:
- Polymer Identification – Distinguishing PET from other plastics such as HDPE and PP.
- Colour Sorting – Enhancing stream efficiency by accurately separating clear, blue, and green PET bottles.
- Food vs. Non-Food Differentiation – Ensuring compliance with food-contact safety standards by eliminating non-food PET contamination.
These advancements significantly improve the quality of rPET feedstock, enabling the production of high-IV, food-grade recycled materials suitable for beverage bottles, pharma, and food packaging applications.
