Automatic Sorting of mixed scrap Metals

Our project is concluded, but we are always open to collaboration !!  

Project Duration:

10/01/2020 – 31/12/2022tin

About Us

AUSOM consists of a consortium of  7 expert organisations from industry, education institutes and research centers from 4 European member states.


The project aims at bringing a robust cost effective sorting technique based on laser induced breakdown spectroscopy (LIBS) for sorting of shredded scrap metal, to the market.

Work Packages

AUSOM is divided into 8 work packages which aims at up-scaling results from past and ongoing research and innovation activities. 

Latest News

 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 article is out, and you can read it in the following link for the first 50 days “Classification of aluminum scrap by laser-induced breakdown spectroscopy (LIBS) and RGB + D image fusion using deep learning approaches.”

By Dillam Diaz | January 9, 2023

Integrating multi-sensor systems to sort and monitor complex waste streams is one of the most recent innovations in the recycling industry. The complementary strengths of Laser-Induced Breakdown Spectroscopy (LIBS) and computer vision systems offer a novel multi-sensor solution for the complex task of sorting aluminum (Al) post-consumer scrap into alloy groups. This study presents two […]

Our New pre-printed: Deep Learning Regression for Quantitative LIBS Analysis of Aluminium Scrap

By Dillam Diaz | November 28, 2022

This study presents two novel methods for fusing RGB and Depth images with LIBS using Deep Learning models. The first method is a single-output model that combines LIBS UNET and two DenseNets in a late fusion framework. The second method is a multiple-output model that uses the structure of the single-output model to enhance learning […]

Our new pre-printed paper, “Classification of Aluminum Scrap by Laser Induced Breakdown Spectroscopy (LIBS) and RGB+D Image Fusion Using Deep Learning Approaches” is out 🙂

By Dillam Diaz | November 9, 2022

We are focusing to show how #rgb + #3d and #libs systems can be fused to improve the classification of scrap #aluminium. This presents a new multi inputs and outputs #deeplearning structure that encompasses the excellent potential for sorting #postconsumer aluminum scrap.    

Automatic Reliable Sorting System



Testing at recycling plant.

Ku Leuven

LCC and LCA analysis, robotic picking, and education component.

LTU Business AB:

Go-to-market strategy


Development of feeding, Development of sorting, and integration of LIBS sensor in sorting equipment.

Spectral Industries BV:

Development of LIBS-sensor, commercialization actor for LIBS-sensor, and system integrator.

Swerim AB:

Coordinator Development of LIBS-sensor and data-analysis solutions, Test-bed provider for sensor and sorting.


Development of the hardware sensing solution.

Contact Information

If you have question, get in contact with Us today! We are looking forward to hearing from you.



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