In today's industry, efficiency and flexibility are decisive factors in remaining competitive. Simulations, virtualisation and digital twins make it possible to digitally map and test products and processes in the planning phase before they are physically implemented. This can shorten development times, reduce costs and minimise errors. The ability to test different scenarios and optimisation potential virtually reduces risks and ensures a faster market launch of new products or production systems.

A demonstrator with new approaches to visualising the material flow of piece goods in production plants shows the added value of these technologies. The movement of these goods is often inadequately visualised in conventional simulations. The demonstrator presented here goes one step further by using a physics-based model for the exact simulation of individual piece goods. For larger quantities, a macroscopic flow model based on a conservation equation is also used. A material flow model supported by AI models, such as Graph Neural Networks, also ensures faster calculations, even with a large number of goods. This combination enables the material flow in various production scenarios to be analysed in a situation-specific and realistic manner.

The combination of virtualisation and digital twins also offers great advantages in production, for example with CNC milling machines. A digital twin can monitor process data in real time, adapt itself and thus ensure better quality assurance. The demonstrator shows this by linking different technologies: a simulation of the 5-axis milling machine, a self-adaptive digital twin and the administration shell for self-description. This interlinking enables precise monitoring of the machine and its processes, which leads to higher product quality, reduced downtimes and optimised production.