Bosch leads €35m software defined manufacturing project

November 26, 2021 // By Nick Flaherty
Bosch leads €35m software defined manufacturing project
The three year, €35m SDM4FZI project aims to provide the foundation of software defined manufacturing in Europe using digital twin technology

The SDM4FZI research project (Software-Defined Manufacturing for the Vehicle and Supplier Industry) is led by Bosch, the University of Stuttgart, and the Karlsruhe Institute of Technology (KIT) and brings together a total of thirty companies.

The goal is to design software that can flexibly plan, manage, and modify everything from individual components to entire factories, based around digital twins and virtual models. In the automotive industry, this will pave the way for more variants and faster model and product changes. BMW for example is already working on digital twin versions of its factories with the Omniverse software from Nvidia. The aim is to take this technology from the automotive market and apply it to geneal industrial manufacturing.

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Many machines are designed and built specifically for a single new product and the software is usually inextricably coupled to particular machinery and products and is not transferable to other processes. SDM4FZI now aims to create a uniform framework for factories that will enable new products to be manufactured in existing operating environments without major retooling times.

“By linking various Industry 4.0 approaches, we are getting one step closer to adaptable manufacturing,” said Matthias Meier, project manager at Bosch. “An ecosystem for software-defined manufacturing allows us to bring the benefits of cloud technology to production. Software makes it possible to use automation technology and IT systems for individual, specific applications without having to build the hardware from scratch.”

The project partners are developing prototypes for machinery and production lines that are largely defined by software. Such prototypes are based on digital twins, which make it possible to plan, build, and test production systems virtually. This conserves resources and saves on energy and costs. During production this makes the individual manufacturing stages more versatile, so they can be adapted more quickly to new market conditions and use AI to analyze the process.

Next: Project focus


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