Digital twins enable organizations to understand, analyze, and optimize complex technical systems using data-driven models. At the Scheer Group stand, the August-Wilhelm Scheer Institute demonstrates how digital twins can support decision-making across the entire value chain – from early product development to the operation of high-performance systems.
An automotive use case from motorsports illustrates how a real racing vehicle can be continuously analyzed and optimized through its digital twin. Technical states, operational contexts, and driving behavior are integrated and evaluated using AI algorithms. Large and heterogeneous data sets are transformed into reliable insights that support performance optimization, improved efficiency, and increased operational reliability.
In addition, the research project ProDiNA demonstrates how digital twins can already be applied during early development phases. Using pumps and drive systems as examples, parameters such as pressure, temperature, forces, wear, and aging are digitally modeled. This enables predictions regarding energy efficiency, expected lifetime, and potential weaknesses before physical prototypes are built.
The demonstrator highlights how digital twins transform data into actionable knowledge and support companies in operating complex systems efficiently, reliably, and sustainably throughout their lifecycle.
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