INFLUENCE OF THROUGHPUT RATE AND INPUT COMPOSITION ON SENSOR-BASED SORTING EFFICIENCY

Abstract

According to Directive (EU) 2018/851 of the European Union, higher recycling rates for municipal waste have to be met in the near future. Besides improvements in the collection systems, the mechanical processing and sorting efficiencies need to be increased to reach the EU´s targets. Sensor-based sorting (SBS) plants constitute an integral part of today's sorting processes. Two main factors influence the sorting performance, namely the throughput rate and the input composition. To improve recycling efficiencies, especially SBS machines must be adjusted accordingly to guarantee the highest possible machine efficiency. Three evaluation criteria, yield/product quantity, product yield, and product purity, are used to describe the performance of these processes. Therefore in this study, 160 sorting trials with 1,000 red and white low-density polyethylene (LDPE) chips were conducted to investigate the influence of the throughput rate and input composition on the sorting processes. For each evaluation criteria, the testing results are plotted in graphs enabling the possibility for process optimization. With increasing throughput rates, the product quantity rises (despite an exponential decrease in yield) in the form of a saturation curve. A higher throughput rate also results in an exponential decrease of the product yield, while a change in the input composition has no effect on the product yield. The third evaluation criteria, the product purity, decreases linearly with an increasing occupation density. The slope of this function depends on the input composition.