SHREDDERSORT · SELECTIVE RECOVERY OF NON-FERROUS METAL AUTOMOTIVE SHREDDER BY COMBINED ELECTROMAGNETIC TENSOR SPECTROSCOPY AND LASER-INDUCED PLASMA SPECTROSCOPY

Every year, more than 50 million vehicles reach the end of their service life throughout the World. In the EU, the amount of waste generated by the automotive industry raised up to 10 million tonnes in 2010, and it is foreseen that it will increase by 40% until 2015. Thus, the appropriate recycling of this waste has important implications from the environmental point of view.About 8% of the total weight in the automotive shredder corresponds to non-ferrous metals, which is often processed by Heavy Media Separation, and handsorting. Vision systems can be used to separate metals based on their colour. However this requires thermal and chemical etching treatments of the shredder to remove coatings, and to induce surface colour modifications, resulting in substantial operational costs, higher energy and water consumption and associated waste and GHG emissions. Moreover, none of current sorting technologies is still able to successfully sort the light fraction of the metals (Al and Mg) into individual alloys, which consequently must be downgraded to produce cast aluminium. In the next years, unless new technologies enable the recovery of Al in the form of wrought alloys (“cradle-to-cradle” approach), secondary Al will not be completely absorbed by the market, and the production of primary Al will increase by 25%. This represents a major environmental concern due to the much higher energy and emissions of primary production process.This project aims at developing a new dry sorting technology for non-ferrous automotive shredder. First, shredder will be separated into different metals, based on their conductivity. To this end, a new electromagnetic sensing technique combined with a vision system will be used. In a next step, the light fraction (Al and Mg alloys, with overlapping conductivities), will be alloy-sorted using LIBS. A novel LIBS system design is proposed, enabling upscaling the sorting throughput by one order of magnitude with respect to existing systems.