Modelling of Post-Fragmentation Waste Stream Processing Within UK Shredder Facilities,

Research Area:
Remanufacturing and Recycling

Year:
2009

Publication:
International Journal of Integrated Waste Management

SMART Authors:
Shahin Rahimifard


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With the introduction of producer responsibility legislation within the UK (i.e waste electrical and electronic equipment directive and end-of-life vehicles directive), specific recycling and recovery targets have been imposed to improve the sustainability of end-of-life products. With the introduction of these targets, and the increases investment in pos-fragmentation facilities, automated material separation technologies are playing an integral role within the UK's end-of-life waste management strategy. Post-fragmentation facilities utilise a range of purification technologies that target certain material attributes (e.g. density, magnetism, volume) to isolate materials from the shredded waste stream. High ferrous prices have historically meant that UK facilities have been primarily interested in recovering iron and steel, establishing processing routes that are very effective at removing these material types, but as a consequence are extremely rigid and inflexible. With the proliferation of more exotic materials within end-of-life products, combined with more stringent recycling targets, there is therefore a need to optimise the current aste reclamation processes to better realise effort-to-value returns. 

This paper provides a background as to the current post-fragmentation processing adopted within the UK, and describes the development of a post-fragmentation modelling approach, capable of simulating the value-added processing that a piece of automated separation equipment can have on a fragmented waste stream. These include the modelling of the inefficiences of the technology, the effects of material entanglement on separation, determination of typical material sizing and an appreciation for compositional value. The implementation of this approach within a software decision-suuport system is described, before the limitations, calibration and further validation of the approach are discussed. 

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