Sustainable injection moulding - inline process monitoring during the processing of PCR

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07.04.2025 | Awards
The 29ᵗʰ national SAMPE Symposium highlighted composite technologies for a sustainable future

Around 80 experts from science and industry came together in the university’s main building to discuss current developments in the field of composite materials. The event was organized by RWTH Aachen University in cooperation with SAMPE

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Bachelor’s thesis or Master’s thesis

As part of the project, the processing behavior of PCR and virgin material will be investigated for different process settings in a fully automated injection molding production cell. Through integrated sensors in the production cell, inline process data and quality parameters of the component can be recorded.

Leitthemen-Kreislaufwirtschaft-3 eng — Post-consumer recyclate

In the interests of a sustainable circular economy, the use of recyclates must be increased. In particular, the processing of post-consumer recyclate (PCR) poses a number of challenges such as process fluctuations due to impurities and degradation. Existing control approaches are reaching their limits due to the strong fluctuations in PCR. In order to compensate for the fluctuations, a process control system based on an AI model is therefore being set up at IKV. Due to the multidimensionality of the process, an AI model can regulate the parameters to be optimised to compensate for process fluctuations in the processing of PCR. This data-driven approach makes it necessary to generate a large amount of data to train the model.

The work is related to this research project:

In the “KIOptiPack” project of the AI Application Hub: Plastic Packaging (BMBF), the processing of recyclates for injection moulding is being optimized on the basis of AI models as part of the German government’s sustainability and AI strategy. Around 50 partners from the chemical industry (Evonik, LyondellBasell), processors (Pöppelamnn), system manufacturers (Arburg, Sumitomo) and various research institutes are working together in “KIOptiPack”.

Objective:

The project aims to investigate the processing behavior of PCR and virgin material for different process settings in a fully automated injection molding production cell. Inline process data and quality parameters of the component can be recorded via sensors integrated into the production cell.

For a Bachelor's thesis you will work on the following tasks	For a Master's thesis you will work on the following tasks
Carrying out tests with a state-of-the-art injection molding machine	also with special injection molding processes	Carrying out tests with a state-of-the-art injection molding machine	also with special injection molding processes
Variation of materials (virgin material/PCR) for different packaging geometries	analysis of the influence of the test parameters on process and component properties
Analysis of the influence of the test parameters on the process and component properties	use of existing AI tools for process optimisation and transfer of the results
Use of existing AI tools for process optimization and transfer of results	validation of the AI models built using the generated data