Overview
The AutoWert project aims to significantly increase the recycling rate of end-of-life vehicles. To this end, computer-aided methods for assessment, dismantling, and worker instruction are being developed.
Grantor:
Sächsische Aufbaubank - Development Bank - SAB
Funding code:
100741774
Term:
01.01.2026 – 30.06.2028
Project content
The AutoWert project is developing a hybrid-autonomous recycling system with a digital twin to significantly increase the recycling rate of end-of-life vehicles. The goal is to identify, evaluate, and dismantle components with residual value. To this end, computer-aided methods for assessment, disassembly, and worker instruction are being developed using simulation and a management shell (VWS). The project is investigating both whole-vehicle recycling and the assessment of components from already disassembled vehicle parts.
Target
Against the backdrop of rapidly rising demand for strategic raw materials—particularly due to the electrification of powertrains—the »AutoWert« project focuses on innovative technologies to increase recycling and recovery rates. The goal is to make a measurable contribution to the circular economy in the automotive sector.
To this end, the project pursues two complementary research approaches that address different stages of utilization:
- First, the automated dismantling of vehicles is being studied. This involves the use of industrial robots and new technologies for identifying and processing vehicle structural components to enable precise and efficient material recovery.
- In addition, the established business of dismantling parts and reselling them is being further developed. A new, hybrid recycling system combines cost-effective dismantling processes—which can be evaluated using a digital twin—with technologies such as 3D scanning, AI-based image processing, and augmented reality.
Research focus imk
The imk’s research focuses on the development of methods and their software implementation in the emaSWS. The functions to be developed are intended, on the one hand, to enable the rapid modeling and evaluation of a wide variety of disassembly processes within a digital model and, on the other hand, to support workers in learning the disassembly processes.
For example, the digital model can be used to determine whether it is better to install one or more disassembly lines with buffer stations between the stations, or to organize the disassembly process similarly to a workshop production setup. In addition, the functions to be developed for virtual worker training and the digital assistance environment will make it possible to train and guide workers more quickly through disassembly processes involving a wide variety of configurations.
Project partner
