Literature DB >> 32605436

Influence of material alterations and machine impairment on throughput related sensor-based sorting performance.

Bastian Küppers1, Sabine Schlögl1, Karl Friedrich1, Laura Lederle1, Celestine Pichler1, Julia Freil1, Roland Pomberger1, Daniel Vollprecht1.   

Abstract

Experiments with sensor-based sorting (SBS) machinery provide insight into the effect of throughput rate and input composition on the sorting performance. For this purpose, material mixtures with certain compositions and particle size distributions were created from waste fractions and sorted at various throughput rates. To evaluate the sorting performance of the SBS unit (using near infrared technology) in dependence of the applied load, four assessment factors concerning the output fractions were studied: yield, product purity, recovery/product quantity and incorrectly discharged share of reject particles. The influences on the assessment parameters of light twodimensional (2D) particles in the input of a sorting stage and failing air valves in an SBS unit were evaluated for various input compositions at different throughput rates. It was found that a share of approximately 5 wt% 2D particles in the input had a similar negative effect on the yield as the malfunction of 20% of all air valves in an SBS machine at high throughput rates. Additionally, the failure of the air valves reduced the product purity of the sorting stage at increased throughput rates. Furthermore, qualitative observations concerning systematic effects of prior studies could be confirmed. Resulting graphs for a specific input composition of an SBS unit at varying throughput rates could be used to adjust the throughput rate to meet the exact demands for a sorting stage.

Entities:  

Keywords:  NIR; Sensor-based sorting; input composition; purity; recovery; sorting performance; throughput rate; yield

Year:  2020        PMID: 32605436     DOI: 10.1177/0734242X20936745

Source DB:  PubMed          Journal:  Waste Manag Res


  1 in total

1.  Qualitative analysis of post-consumer and post-industrial waste via near-infrared, visual and induction identification with experimental sensor-based sorting setup.

Authors:  K Friedrich; G Koinig; R Pomberger; D Vollprecht
Journal:  MethodsX       Date:  2022-04-02
  1 in total

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