Indirect Estimation of the Volumetric Throughput Performance in the Shredding of Solid Waste

Christoph Feyerer, Karim Khodier, Tatjana Lasch, Roland Pomberger and Renato Sarc ()
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Christoph Feyerer: Komptech GmbH, 8130 Frohnleiten, Austria
Karim Khodier: Chair of Waste Processing Technology and Waste Management, Montanuniversität Leoben, 8700 Leoben, Austria
Tatjana Lasch: Chair of Process Engineering for Industrial Environmental Protection, Montanuniversität Leoben, 8700 Leoben, Austria
Roland Pomberger: Chair of Waste Processing Technology and Waste Management, Montanuniversität Leoben, 8700 Leoben, Austria
Renato Sarc: Chair of Waste Processing Technology and Waste Management, Montanuniversität Leoben, 8700 Leoben, Austria

Clean Technol., 2025, vol. 7, issue 2, 1-19

Abstract: The volume or mass throughput of a mechanical treatment plant for commercial waste represents a key performance parameter. This measurement parameter is often unavailable, as the sensor technology required is often expensive or does not provide accurate data. The first process stage is usually a shredding machine, converting the waste into a transportable and separable fraction size. Here, a methodical approach is pursued which enables an indirect estimation of the volume throughput capacity based on further machine parameters, such as the drum speed and the drum torque. Based on 32 test data sets, two models were developed to approximate the volume throughput rate. The two models developed are the regression model and the displacement model. Furthermore, two reference models were defined to evaluate the accuracy of the two approaches developed: the so-called mean value model and the ANOVA model. When looking at the 80th percentile of the sign-adjusted relative deviation, the results show that the regression model, with ±40%, followed by the displacement model, with ±42%, enable significantly more accurate estimates of the volumetric throughput performance than the two reference models, with ±63% and ±71%, respectively.

Keywords: waste treatment; mixed solid waste; mechanical treatment; shredding; throughput; measurement technology; intelligent plant (search for similar items in EconPapers)
JEL-codes: Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2025
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