Automatic Sorting of mixed scrap Metals
We are proud to announce the first release of our AUSOM website. We’re very anxious to your reaction. If you have any comments or questions concerning the website or the AUSOM project, please contact us.
Our new conference article is out : Assessing the efficiency of Laser-Induced Breakdown Spectroscopy (LIBS) based sorting of post-consumer aluminium scrap !!
The life cycle engineering (LCE) research group (SIM² – KU Leuven) of the KU Leuven has demonstrated the capability of LIBS in combination with machine learning techniques to sort aluminium post-consumer scrap into commercially interesting fractions. The proposed sorting targets enable increased wrought-to-wrought recycling and are an alternative for the current downcycling dynamic of aluminium scrap. https://www.sciencedirect.com/science/article/pii/S2212827122000464
Our new article: Simultaneous Mass Estimation and Class Classification of Scrap Metals using Deep Learning
The KU Leuven’s lifecycle engineering (LCE) research group (SIM² – KU Leuven) and EAVISE Research Group have explored a new methodology for mass estimation and classification of scrap metals using Deep Learning. The presented research is an essential step towards improved metal sorting and recycling. The proposed research developed is capable of monitoring the composition […]
The lifecycle engineering (LCE) research group (SIM² – KU Leuven) of the KU Leuven allows to estimate that the global aluminium scrap surplus will emerge soon and reach a size of 5.4 million tonnes by 2030 and 8.7 million tonnes by 2040, if currently adopted aluminium sorting and recycling methods are not improved. Here is […]