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Data-driven inline process monitoring of highly filled polymer systems in filament-based material extrusion

21.11.2025

In the ""AiProMex"" project a systematic approach to the in-line recording of rheology is being developed consisting of sensory recording and its evaluation using machine learning (soft sensor technology) which should enable process control. In addition, we expect to gain a detailed understanding of the relationships between material, process parameters and product quality, which in turn will allow the (offline) optimisation of the process with regard to material properties. This has a positive effect on the print defect balance and material consumption increases the quality and performance of the components and thus leads to a broader applicability of the technology.

Further informations can be found in:

https://www.tckt.at/en/3d-print/aipromex-2
https://projekte.ffg.at/projekt/5121023

Speaker: Christoph Strasser, Scientific researcher, TCKT Transfercenter für Kunststofftechnik