Efficient derivation of significant results from mechanical processing experiments with mixed solid waste: Coarse-shredding of commercial waste

Deriving significant experiment-based conclusions on mechanical processing of mixed solid waste is challenging: the input material cannot be downscaled in a way that enables drawing transferable conclusions from lab-scale experiments. Hence experiments need to be conducted in industry-scale, using real waste. Besides the enormous resulting experimental efforts and costs, which economically limit the number of experimental runs, identifying and quantifying significant effects is complicated by the distortion of the data introduced by the waste's variability. The distortion is particularly high for cases where sampling is necessary and in experiments where material cannot be re-used from one run to the next. In the latter case, inter-experimental differences of the waste add to the distortion of the data. In this work, a systematic approach for deriving representative and significant results at the minimum possible effort is described and evaluated, based on the method of Design of Experiments. It is applied to a 32 runs D-optimal industry-scale coarse-shredding experiment with mixed commercial solid waste, based on a reduced cubic design model, examining the influence of the gap width, shaft rotation speed, and cutting tool geometry on the throughput behavior and energy demand. The resulting models are highly significant (model p-values < 0.0001), proving the ability to extract reliable information from industry-scale waste processing experiments. Concerning commercial waste shredding, the models provide new insights into process behavior, for example, the quadratic dependence of the mass flow on the shaft rotation speed, with the highest hourly mass flows at 84% of the maximum shaft rotation speed.

Real time material flow monitoring in mechanical waste processing and the relevance of fluctuations

To achieve the goals of the circular economy, significant improvements in non-hazardous solid waste processing/treatment must be made. Large deficits in the digitalization of mechanical waste treatment plants (smart waste factory) offer great potential for improvement. Real-time material flow monitoring is carried out in very few plants, thus wasting considerable potential for improving plant performance. This article describes results from the authors' own practical analyses using sensor-based technologies for monitoring material flows, an on-site investigation in a large waste treatment plant and also in a pilot-scale plant (Technical Line 4.0) using mixed commercial waste (MCW) from Austria. The obtained data shows that the quantitative monitoring of volume and mass flow (via laser triangulation as well as near-infrared (NIR) based monitoring) and material composition (NIR sensor) is possible. The observed fluctuations were categorised in short-, mid- and long-term fluctuations and were led back to their causes, i.e. discontinuous feeding process, material and machine-specific characteristics. Using the quotient of the 90% (Q90) and 10% (Q10) quantiles of time-resolved volume-flow data for the assessment of fluctuations, for the considered time-intervals, resulted in Q90 / Q10 ratios between 3.39 and 4.58. If short-term fluctuations (within the observed time-intervals) are related to the 29.6 s moving average, deviations between 1.8% and 6.8% result. To verify the relevance of such fluctuations, sensor-based sorting (SBS) experiments were conducted, revealing a reduced product purity of 6% due to short-term fluctuations in the feed of the SBS-Machine using light packaging waste (LPW).

Influence of pre-screening on down-stream processing for the production of plastic enriched fractions for recycling from mixed commercial and municipal waste

The use of plastic waste as resource gains more and more attention. In this context, material recycling is especially focused on packaging plastics. Further waste streams that contain a significant amount of plastics are mixed commercial and municipal solid waste. To assess the potential of plastics for recycling and energy recovery from these material streams large-scale experiments were conducted. The potential of mechanical pre-processing with the aim of generating a 3D-plastics pre-concentrate was assessed. The focus of these investigations was put on the relevance of the screening stage and its influence on down-stream material processing via ballistic separation and sensor-based sorting. Results demonstrate not only that the screening of both waste streams leads to enrichment of plastics in coarse particle size ranges (especially >80 mm) and transfer of contaminants, organics and minerals to fine fractions (especially <10 mm), but also that sensor-based sorting performance can be significantly enhanced due to cleaning effects on plastics, induced by the material circulation and the resulting interparticle friction in a drum screen. On the downside, the material rotation in a drum screen leads to tail-formation that can create plant down-time through clogging as well as material losses and impairment of pre-concentrates.

Grain size dependent distribution of different plastic types in coarse shredded mixed commercial and municipal waste

The Waste Framework Directive regulates the recycling of waste in Europe. The definition of waste is specified in different guidelines and regulations. Mixed Commercial Waste is waste from industry which is not collected separately. Currently there is little known about its composition. Mixed Municipal Waste, on the other hand, is household waste that cannot be attributed to any separately collected waste fraction (AdSLR, 2012). Both wastes are currently treated focussing on the generation of refuse-derived fuel rather than on the separation of recyclables (mainly performed for metals). The purpose of this paper is to characterise the amounts of various plastic types contained in different grain sizes of two-dimensional and three-dimensional plastics sorting fractions of both waste types. Nine types of plastics were identified as potential recycling materials for which recycling processes as well as a market are available. Both wastes were shredded, sampled and sieved into nine grain size classes (GSC). Fractions coarser than 20 mm were sorted, generating a 'plastics-2D' and a 'plastics-3D' fraction among others. The two plastics fractions were further characterised as plastic types using a near-infrared sensor and a Fourier-transform infrared spectrometer. The results reveal a potential for plastic recycling through mechanical and feedstock recycling options for the examined wastes. Certain types of plastics, of certain dimensionality, tend to come in certain grain sizes, which is essential for mechanical enrichment and discharge.