Development of a multi-criteria decision tool for the plastics industry – A case study on post-consumer PP packaging material
Description
Circular economy aims to retain valuable materials in the recycling loop and reduce losses. Packaging materials, owing to their short market lifetimes, dominate the waste stream, and feedstock for mechanical recycling remains a fluctuating geographical and seasonal factor. This study presents a decision tree for a mechanical recycling process to transform a post-consumer polypropylene (PP) waste stream into a high-quality product. Initial manual analysis of a representative PP bale from a sorting plant revealed an 87.5% PP content, with 75% being white or transparent. The recycling process involved color-based sorting into three different color fractions (white, transparent, and colored), grinding, multiple washing steps, flake sorting, and granulation to produce six distinct fractions. This study highlights the importance of tracking material flow, generating process data, and linking it to environmental impacts. Using the Alpha Algorithm, a process network from feedstock to final pellets was developed to identify key decision points based on feedstock quality, color, and volatile organic compounds (VOC) contamination. These findings demonstrate that cleaning reduces contaminants and improves product quality. The developed tool aids in optimizing recycling processes with the aim of retaining valuable materials in primary recycling loops and minimizing downcycling.