Advancing data-driven process modeling in metal forming

Abstract

The production of metal forming technology products until now requires substantial expertise from specialists in product, process, and equipment design. Particularly important is the ability to compensate for stochastic, unpredictable process deviations. Given this context, a newly established Priority Program 2422 (PP 2422) by the German Research Foundation (DFG) aims to enhance the current FEM-simulation-based design of the active surfaces of metal forming tools with data-driven modeling. The present paper firstly summarizes the current state of the art in data-based process modelling in this technology. Subsequently, the research questions addressed by the PP 2422 and the concept of interdisciplinary cooperation between metal forming, automation and data science are explained.