FORCuDE@BEV

BAVARIAN RESEARCH ASSOCIATION FOR CUSTOMIZED DIGITAL ENGINEERING FOR BAVARIAN SMES USING THE EXAMPLE OF THE DRIVE TRAIN OF BATTERY ELECTRIC VEHICLES

The association

The increasing digitalization changes many areas of life, which on the one hand offers great opportunities for a better quality of life, revolutionary business models and more efficient economic activity. On the other hand, small and medium-sized enterprises in particular have a special need for support and advice. According to a survey of high-ranking decision-makers in 1,061 companies, only 7% of companies in Germany are considered "digital pioneers". The early implementation of digitalization measures in product development not only offers enormous advantages for large companies, but also enables small and medium-sized companies to considerably increase their efficiency and competitiveness.

The advantages of digitalization in service processes or in production can be seen very quickly, but the introduction of digital engineering for the development in mechanical engineering also offers numerous decisive advantages over previous procedures in the development departments of industry. It is therefore necessary to supply methods along the entire product development process with data, to pass on requirements along the entire tool chain in a traceable way and to promote the efficient cross-linking of different methods.

The motivation of this research association is to build up a continuous digital engineering process adapted to the development of electrified powertrains for SMEs and to transfer the potentials of digitalization into development business processes. To achieve this, individual methods along the product development chain have to be optimised and linked with each other. This is based on the use of data and the application of machine learning algorithms. Furthermore, the developed methods should also be transferable to other challenges in product development and accordingly implemented or demonstrated in a usability study.

Information

Launching date

04.2020

End

04.2023

Funded by

Bayerische Forschungsstiftung