Fraunhofer Institute for Production Systems and Design Technology
Fraunhofer Institute for Production Systems and Design Technology

Disassembly, Fully Digitalized

Politicians are calling for a more circular economy. This requires the digitalized, automated disassembly of used parts. And yet innovative, AI-supported solutions are lacking a solid data basis.

Researchers at Fraunhofer IPK have developed a comprehensive and coherent digitalization concept for the disassembly of vehicles. At the heart of this concept is the Circular Economy Assistant, a decision-making tool designed to make companies fit for the circular economy. The CE Assistant also provides a straightforward overview of various disassembly options and their individual carbon footprints, making it stand out thanks to integrated solutions that cover the entire disassembly process.

1. A vehicle that is scheduled for disassembly can be inspected virtually, even before a single part has been removed. By entering the unique identification number of the vehicle that has to be disassembled, data made available within the Catena-X data ecosystem can be retrieved in the form of a digital twin.
2. Using this digitally available data, individual components can be evaluated for reuse or recycling without having to be physically removed. For example, the average service life specified by the manufacturer can help to assess whether a component has been in operation for such a long time that reuse is no longer safe.
© Fraunhofer IPK/Larissa Klassen
3. Using a robotic, intelligent camera system, the visible components of the extracted motor can be recorded and their condition assessed – a fully non-destructive and automated process.
© Fraunhofer IPK/Larissa Klassen
4. A worker dismantles the motor with the help of AR glasses showing her step-by-step instructions for removing the individual parts. At the same time, the glasses are recording the disassembly process.

Next stop: automation

The digitalized disassembly process shown here has not yet reached the end of the road. After all, the demands on disassembly are growing: Increasingly complex vehicle components have to be taken apart so that the individual parts can be recycled. To make this possible even when skilled specialized workers are hard to come by, further automation measures are needed. To accomplish this, AR glasses are used during the disassembly process to capture images that can be used to train an AI. On the basis of this multimodal data recording, robots will be able to perform the strenuous manual work in the future.

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