Abstract
Sensor-based sorting (SBS) has been widely applied in the recycling industry for various waste types for more than two decades. Compared to manual sorting, SBS achieves higher throughputs, reproducible sorting results, and higher automation degrees. While the sortable particle features of traditional sorting methods (e.g., wind sifting or magnetic separation) are limited by the underlying separation forces (e.g., magnetic force), SBS methods are characterized by the independence of detected particle features (e.g., color and chemical structure) and the applied separation forces (e.g., air valves). Thus, a variety of different particle features can be used and combined for corresponding sorting tasks, and the sorting process can be easily adjusted by the applied sorting program. Therefore, sorting tasks such as sorting according to different colors or polymer types that were difficult or impossible to achieve with traditional sorting equipment can be achieved by SBS. Currently, sensor-based sorters are applied to various material flows, and SBS (cascades) represent a central element of many modern sorting processes.