Professorship for Manufacturing – Innovative Manufacturing
Organisational unit: Professoship
Main research areas
The professorship for manufacturing technology – which takes the form of a shared professorship with the Helmholtz-Zentrum hereon GmbH – covers a wide spectrum of manufacturing processes, both in regard to research and in regard to teaching. In doing so, research work focuses primarily on forming technology and the integration of additional manufacturing technologies, such as additive manufacturing. In terms of research and teaching, the key specialisations of this group are light construction and the conservation of resources, the adaptation of process- and material-induced product properties, components and processes for electric mobility, Industry 4.0, and networked and digitalised processes. These fields are researched from a manufacturing technology point of view and furthered through cooperations with other disciplines.
What’s more, one of the key activities carried out by this professorship is the transfer of this knowledge into regional, national and international industry. In addition, the professorship represents Leuphana University and the Helmholtz-Zentrum hereon GmbH national and international committees for manufacturing technology, such as the AGU (German Metal Forming Association) or CIRP (the International Academy for Production Engineering).
- Published
Thermal Analysis and Production of As-Cast Al 7075/6060 Bilayer Billets
Greß, T., Mittler, T., Schmid, S., Chen, H., Ben Khalifa, N. & Volk, W., 01.10.2019, In: International Journal of Metalcasting. 13, 4, p. 817-829 13 p.Research output: Journal contributions › Journal articles › Research › peer-review
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Towards 3D Process Simulation for In Situ Hybridization of Fiber-Metal-Laminates (FML)
Poppe, C. T., Werner, H. O., Kruse, M., Chen, H., Ben Khalifa, N., Henning, F. & Kärger, L., 22.07.2022, In: Key Engineering Materials. 926, p. 1399-1412 14 p.Research output: Journal contributions › Conference article in journal › Research › peer-review
- Published
Using Decision Trees and Reinforcement Learning for the Dynamic Adjustment of Composite Sequencing Rules in a Flexible Manufacturing System
Voß, T., Heger, J. & Zein El Abdine, M., 09.2022, In: Simulation Notes Europe. 32, 3, p. 169-175 7 p.Research output: Journal contributions › Conference article in journal › Research › peer-review
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Werkzeugkonzepte und Methoden für das Strangpressen
Ben Khalifa, N., Isakovic, J. & Bohlen, J., 28.04.2022, IPC No. B21C25/02, Deutsches Patent- und Markenamt, Patent No. 10 2020 128 163.3, 27.10.2020Research output: Patents › Patent