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      E-PreMa | Improved manufacturability assessment of sheet metal parts in the early design phase using machine learning

      Information

      Project name

      E-PreMa | Improved manufacturability assessment of sheet metal parts in the early design phase using machine learning

      Content

      Due to increasing cost pressure and short development cycles in the automotive sector, there is a need to increase the efficiency of processes. This also affects the development of sheet metal parts. When designing new sheet metal parts, various design approaches are pursued in the early development stage whose subsequent manufacturability can hardly be assessed objectively. This leads to high additional costs and time delays due to the further development of parts that cannot be manufactured later. Therefore, a software prototype is to be developed in the E-PreMa project, which can predict the manufacturability already in the early development phase and also shows suitable development approaches. The underlying methodology is a coupling of FEM simulations, machine learning, shape optimization and other data engineering methods. The resulting software is intended to provide design engineers with reproducible assistance in combining all business and technical requirements in a manufacturable sheet metal part. In this way, expensive and time-consuming incorrect developments are to be reduced to a minimum.

      The project is funded by the Central Innovation Program for SMEs (ZIM) of the German Federal Ministry for Economic Affairs and Energy (BMWi).

      Project Coordinator

      Prof. Dr.-Ing. Marcus Wagner

      Project partner

      • SCALE GmbH, Ingolstadt
      • Munich University of Technology

      Duration

      01.10.2021 – 30.09.2023

      Grantor

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