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

  • Bastian Küppers - Department of Environmental and Energy Process Engineering, Montanuniversitaet Leoben, Austria
  • Irina Seidler - Department of Environmental and Energy Process Engineering, Montanuniversitaet Leoben, Austria
  • Gerald Rudolf Koinig - Department of Environmental and Energy Process Engineering, Montanuniversitat Leoben, Austria
  • Roland Pomberger - Department of Environmental and Energy Process Engineering, Montanuniversitat Leoben, Austria
  • Daniel Vollprecht - Department of Environmental and Energy Process Engineering, Montanuniversität Leoben, Austria

DOI 10.31025/2611-4135/2020.13906

Released under CC BY-NC-ND

Copyright: © 2019 CISA Publisher

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.

Keywords

Editorial History

  • Received: 22 Jul 2019
  • Revised: 26 Nov 2019
  • Accepted: 20 Dec 2019
  • Available online: 11 Feb 2020

References

Alaya, M.A., Tóth, Z. and Géczy, A. (2019), “Applied Color Sensor Based Solution for Sorting in Food Industry Processing”, Periodica Polytechnica Electrical Engineering and Computer Science, Vol. 63 No. 1, pp. 16–22

Cubero, S., Aleixos, N., Moltó, E., Gómez-Sanchis, J. and Blasco, J. (2011), “Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables”, Food and Bioprocess Technology, Vol. 4 No. 4, pp. 487–504

Dalm, M., Buxton, M.W.N., van Ruitenbeek, F.J.A. and Voncken, J.H.L. (2014), “Application of near-infrared spectroscopy to sensor based sorting of a porphyry copper ore”, Minerals Engineering, Vol. 58, pp. 7–16

Eurostat (2019), “Packaging waste statistics. Statistics Explained”, available at: https://ec.europa.eu/eurostat/statistics-explained/pdfscache/10547.pdf (accessed 17 July 2019)

Feil, A., Thoden van Velzen, E. U., Jansen, M., Vitz, P., Go, N. and Pretz, T. (2016), “Technical assessment of processing plants as exemplified by the sorting of beverage cartons from lightweight packaging wastes”, Waste Management, Vol. 48, pp. 95–105

Gundupalli, S.P., Hait, S. and Thakur, A. (2017), “A review on automated sorting of source-separated municipal solid waste for recycling”, Waste Management, Vol. 60, pp. 56–74

International Organization for Standardization (2008), Plastics - Guidelines for the recovery and recycling of plastics waste No. 15270:2008

Jansen, M., Feil, A. and Pretz, T. (2012), “Recovery of Plastics from Household Waste by Mechanical Separation”, in Thomé-Kozmiensky, K.J. and Thiel, S. (Eds.), Waste management: Volume 3, Recycling and Recovery, TK-Verl. Thomé-Kozmiensky, Neuruppin

Knapp, H., Neubert, K., Schropp, C. and Wotruba, H. (2014), “Viable Applications of Sensor-Based Sorting for the Processing of Mineral Resources”, ChemBioEng Reviews, Vol. 1 No. 3, pp. 86–95

Küppers, B., Chen, X., Seidler, I., Friedrich, K., Raulf, K., Pretz, T., Feil, A., Pomberger, R. and Vollprecht, D. (2019a), “Influences and consequences of mechanical delabelling on PET recycling”, Detritus, No. 0, p. 8

Küppers, B., Schloegl, S., Oreski, G., Pomberger, R. and Vollprecht, D. (2019b), “Influence of surface roughness and surface moisture of plastics on sensor-based sorting in the near infrared range”, Waste Management & Research

Lessard, J., Bakker, J. de and McHugh, L. (2014), “Development of ore sorting and its impact on mineral processing economics”, Minerals Engineering, Vol. 65, pp. 88–97

Mesina, M.B., Jong, T.P.R. de and Dalmijn, W.L. (2007), “Automatic sorting of scrap metals with a combined electromagnetic and dual energy X-ray transmission sensor”, International Journal of Mineral Processing, Vol. 82 No. 4, pp. 222–232

Rahman, M.O., Hussain, A. and Basri, H. (2014), “A critical review on waste paper sorting techniques”, International Journal of Environmental Science and Technology, Vol. 11 No. 2, pp. 551–564

The European Parliament and of the Council of the European Union (2018), Directive (EU) 2018/ of the European Parliament and of the Council of 30 May 2018 amending Directive 2008/98/EC on waste

Tu, S.S., Choi, Y.J., McCarthy, M.J. and McCarthy, K.L. (2007), “Tomato quality evaluation by peak force and NMR spin–spin relaxation time”, Postharvest Biology and Technology, Vol. 44 No. 2, pp. 157–164

Workman, J. and Springsteen, A.W. (1998), Applied spectroscopy: A compact reference for practitioners, Academic Press, San Diego

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