- Data-driven process modelling in stamping and bending technology
Prof. Dr.-Ing. Matthias Althoff, Dr.-Ing. Christoph Hartmann, Prof. Dr.-Ing. Wolfram Volk - Derivation of cause-effect relationships for effective surface design on the basis of data-driven process modelling for fineblanking
Univ.-Prof. Dr.-Ing. Thomas Bergs, Prof. Dr. Peer Kröger, Prof. Dr. Sebastian Trimpe - Optimisation of the die face design of high-speed progressive dies using machine learning algorithms
Prof. Dr.-Ing. Dipl.-Wirtsch.-Ing. Peter Groche, Prof. Dr. Kristian Kersting - Data-driven modelling of multi-stage stamping and bending processes
Prof. Dr. Barbara Hammer, Prof. Dr.-Ing. Werner Homberg, Prof. Dr.-Ing. habil. Ansgar Trächtler - Process data-driven modelling for the robustification of shear-cutting-collar-drawing processes by means of effective tool surface design under consideration of edge crack sensitivity
Prof. Dr. Agnes Koschmider, Prof. Dr.-Ing. habil. Verena Kräusel - Development of a data-driven model for the evaluation and improvement of process robustness in the die face design of deep-drawing dies
Prof. Dr. Noomane Ben Khalifa, Prof. Dr.-Ing. Jens Heger - AI-based set-up assistance system for transfer presses
Dr.-Ing. Lennart Hinz, Dr.-Ing. Richard Krimm - Data-based tool processing in sheet metal forming
Prof. Dr.-Ing. Steffen Ihlenfeldt, Univ.-Prof. Dr. Oliver Niggemann - Robust active surface design for multi-stage sheet metal forming processes based on data- and calculation-based equivalent modelling of component springback
Univ.-Prof. Dr.-Ing. Dr. h. c. Mathias Liewald MBA, Univ.-Prof. Dr.-Ing. Dr. h. c. Michael Weyrich - Method for the design of forming tools for rotary-draw bending of bend-in-bend geometries
Univ.-Prof. Dr.-Ing. Bernd Engel, Prof. PhD Kristof Van Laerhoven - Data-supported determination and prediction of the effective surface condition and intervention in conveyor belt flow processes
Prof. Dr.-Ing. habil. Marion Merklein, Prof. Dr.-Ing. Birgit Vogel-Heuser - Transparent AI-supported process modelling in drop forging
Dr.-Ing. Kai Brunotte, Univ. Prof. Dr.-Ing. Marco Huber - DatProForge data-driven process modelling of drop forging processes to increase productivity using adaptive tool design methodology
Prof. Dr.-Ing. Markus Gardill, Prof. Dr.-Ing. Sebastian Härtel
Contact
Mathias Liewald MBA
Univ.-Prof. Dr.-Ing. Dr. h. c.Head of Institute
Adrian Schenek
Dr.-Ing.Research Assistant
Theresa Scholl
B.Sc.Coordination Assistant SPP 2422