Development of a multi-criteria decision tool for the plastics industry – A case study on post-consumer polypropylene packaging material

The circular economy seeks to retain valuable materials within the recycling loop and aims to minimize resource losses. Packaging materials, due to their short service life, constitute a major portion of the waste stream, while the availability of suitable feedstock for mechanical recycling is subject to geographical and seasonal variability. This study introduces a multi-criteria decision-making tool designed to optimize the mechanical recycling of post-consumer polypropylene (PP) waste into high-quality products. A representative PP bale from a sorting facility was manually analyzed, revealing an 87.5% PP content, with 75% of the material being white or transparent. The recycling process included color-based sorting into three fractions (white, transparent, colored), followed by grinding, three sequential washing steps, flake sorting and granulation. This resulted in six distinct output fractions, each subjected to detailed analysis. The study emphasizes the importance of material flow tracking, process data generation and the integration of environmental impact assessments. Using the Alpha algorithm methodology, a process network was constructed from feedstock to final pellet, identifying critical decision points based on input quality, color and VOC contamination. The results demonstrate that while additional washing steps enhance product quality by reducing contaminants, they also increase the environmental footprint. The developed decision tool supports the optimization of recycling workflows, aiming to preserve material value within primary recycling loops and reduce downcycling. The findings underscore that data availability and quality are essential enablers for advancing circularity in the plastics industry.