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ENGEL Supports Upcycling Research at TH Rosenheim

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Chandana Patnaik

Senior Strategist (Content)

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The ENGEL Group, Europe's leading provider of injection moulding technologies, has provided the Rosenheim University of Applied Sciences with a state-of-the-art injection moulding cell. This system, comprising an ENGEL insert 500V/130 vertical injection moulding machine, an ENGEL infrared oven, and an ENGEL easix KR-10 articulated arm robot, is being used in the university's teaching and research with a particular focus on the processing of thermoplastic, recyclable composites and the application of natural fibres.

A key research focus at TH Rosenheim is on composite materials. The project 'Wood-Based Bioeconomy' deals with the production and processing of new materials from cellulose fibres and polypropylene (PP). Particularly noteworthy is the upcycling approach of the project "ZIM - ReProHybrid": materials from decommissioned car bumpers are shredded and processed into new organosheets, which can be back-injected in the injection moulding process with other recycled materials from bumpers.

Dr.-Ing. Johannes Kilian, Head of Process and Application Technology at the ENGEL Group, said: "TH Rosenheim plays a significant role in research and development, especially in the development of sustainable injection moulding solutions and new materials. The collaboration is of great importance to us, as the university is not only known for its research strength in the field of plastics processing but also for its practice-oriented education."

Prof. Dr.-Ing. Norbert Müller, Dean of Studies for the degree programs in Plastics Engineering and Sustainable Polymer Technology, emphasized: "The new facility enables us to conduct practical investigations and further explore the use of sustainable materials in technical applications and in construction."

Digitalisation also plays a central role: by utilising ENGEL's iQ process observer, the university gathers valuable data that allows for insights applicable to other uses through semantic processing, representing a significant step towards machine learning and AI-supported applications in plastics processing.

Source: engelglobal.com