Technical assessment of processing plants as exemplified by the sorting of beverage cartons from lightweight packaging wastes

Feil, Alexander; Velzen, E.U. Thoden van; Jansen, Michael; Vitz, Philipp; Go, N.; Pretz, Thomas

doi:10.1016/j.wasman.2015.10.023

Cited by 23 publications

(23 citation statements)

References 2 publications

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“…The yield (R w ) is based on the amount of the desired component (eject) in the feed material and calculated from the ratio of the mathematical product of determined mass flow (m output ) and substance concentration (c output ) of the respective sorting product (output) to the respective product of mass (m input ) and substance concentration (c input , defined as the content of eject material in the input material) of the feed material (input). It is calculated as follows (Feil et al, 2016):…”

Section: Evaluation Of Resultsmentioning

confidence: 99%

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Influence of Throughput Rate and Input Composition on Sensor-Based Sorting Efficiency

et al. 2020

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According to the Directive (EU) 2018/851 of the European Union, higher recycling rates for municipal waste will have to be met in the near future. Beside improvements to the collection systems, the efficiency of mechanical processing and sorting will have 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 determine the sorting performance: throughput rate and input composition. To improve recycling efficiencies, especially SBS machines need to be optimized. Three evaluation criteria are used to describe the performance of these processes: recovery (content of input material -both eject and reject material discharged into the product fraction) or product quantity (amount of product generated via sorting within a specific interval -calculated by multiplying throughput rate and yield), yield (amount of eject material discharged into the product fraction), and product purity. For this study, 160 sorting experiments each with 1,000 red and white low-density polyethylene (LDPE) chips were conducted to investigate the effects of throughput rate and input composition on sorting processes. This simplified approach reduced the influence of other factors on the sorting performance, giving precise information on the effect of throughput rate and input composition. The testing results can enter process optimization. With increasing throughput rates, product quantity rises following a saturation graph (despite exponential decrease in recovery). In the experiments a higher throughput rate also resulted in an exponential decrease of the yield while a change to the input composition had no such effect. The third evaluation criteria, product purity, decreases linearly with increasing occupation density. The slope of this function depends on the input composition.

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Section: Evaluation Of Resultsmentioning

confidence: 99%

“…According to Feil et al (2016), the purity (P m ) of a material is defined as the content of correctly ejected material in the sorting product. It is calculated as follows:…”

Section: Evaluation Of Resultsmentioning

confidence: 99%

Influence of Throughput Rate and Input Composition on Sensor-Based Sorting Efficiency

et al. 2020

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“…In the following, instructions are presented based on the results of Feil et al (2016) and on the previous section to serve as guidance for the samplers and plant operators. Although the results presented refer to separating BCs in LP Plants, this principle can be applied to other materials and sorting systems.…”

Section: Discussionmentioning

confidence: 99%

“…The sampling results of the final product from Feil et al (2016) have shown that 51.1 wt. % of the BC fraction in the input was sorted into the BC products; 38.4 wt.…”

Section: Plant IIImentioning

confidence: 99%

“…In addition, the highest CIs with values >4% were determined here. The requirements for sampling and the implementation have been elaborately discussed by Feil et al (2016); besides conforming to the number of samples and the sampling quantities, for example, by complying to appropriate guidelines, such as from LAGA PN 98, 2004 andLAGA PN 2/78 K, 1983, it should be investigated in advance whether the stream can actually be sampled without restriction under the regular conditions at the sampling sites. Restricted accessibilities (e.g.…”

Section: Numbermentioning

confidence: 99%

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A methodical approach for the assessment of waste sorting plants

et al. 2017

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A techno-economical evaluation of the processing result of waste sorting plants should at least provide a realistic assessment of the recovery yields of valuable materials and of the qualities of the obtained products. This practical data is generated by weighing all the output products and sampling these products. Due to the technological complexity of sorting plants, for example, lightweight packaging waste treatments plants and the high expenditures concerning time and costs of sampling with subsequent manual sorting for quality determination, usually only final products undergo such an investigation. Thereby, the transferability of the results depends decisively on the boundary conditions (extent, throughput of the plant, process parameterization). Given that the process is too complex, not all relevant information of the process steps can be determined by sampling. By model calculations and/or adjustment of reasonable assumptions, information concerning weak points in the process can be identified, which can be used for further plant optimization. For the example of the recovery of beverage cartons from co-collected and mechanically recovered mixtures of lightweight packaging waste, a methodical approach for the assessment of processing results will be presented.

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A method for assessing the performance of sorting unit operations in a material recovery facility based on waste characterizations

et al. 2022

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The determination of the separation efficiencies of mechanical sorting equipment is essential to improve the performance of material recovery facilities (MRFs). However, it is often a challenge to obtain these efficiencies due to the high complexity of MRFs, which often comprise several recirculation streams. In this paper, a methodology to determine the equipment separation efficiencies of a complex MRF is described and applied to an actual sorting centre located in the province of Quebec, Canada. Transfer coefficients for every unit operation and several material types, together with all material flows within the facility, have been determined for an MRF processing a stream of commingled recyclable materials.This work also provides a rare dataset of separation efficiencies for several mechanical sorting unit operations. The methodology is validated by comparing experimental data and model predictions for the recovery and purity of all main output streams. The results contribute to identify several avenues for process performance improvement, like adding a magnetic separation at the beginning of the sorting sequence or improving the separation of the 2D-type materials collected from the second ballistic separator by changing the operation conditions or adding a quality control step. Moreover, the results also provide valuable information about material recovery and purity to help managers improve the process performance. Finally, a scenario analysis demonstrates that the performance of a second ballistic separator has an important impact on the sorting process's global efficiency and that recirculating a fraction of the rejects output stream has a negligible impact on the global performance.

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Technical assessment of processing plants as exemplified by the sorting of beverage cartons from lightweight packaging wastes

Cited by 23 publications

References 2 publications

Influence of Throughput Rate and Input Composition on Sensor-Based Sorting Efficiency

Influence of Throughput Rate and Input Composition on Sensor-Based Sorting Efficiency

A methodical approach for the assessment of waste sorting plants

A method for assessing the performance of sorting unit operations in a material recovery facility based on waste characterizations

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