Modern machine tools produce increasing amounts of data.
Digital twins use this data to reason about the state of the production process and thus provide a powerful means to optimise production efficiency and quality.
However, the development of such digital twins is challenging and usually tailored to a specific machine.
Flexible SDM through Continuously Quality-Aware Digital Twins (SDMflex) investigates digital twins able to make quality predictions and optimisation decisions for entire ranges of similar machine tools.
The project is part of the Innovation Campus Future Mobility (ICM), an interdisciplinary initiative of the University of Stuttgart and the Karlsruhe Institute of Technology (KIT).
In the context of SDMflex, ISTE SQA researches ways of connecting generic digital twins with their physical counterparts without requiring programming knowledge on the part of the engineer.
Simple languages specific to the manufacturing domain are being developed, enabling engineers to easily define mappings between heterogeneous data models and define various parameters, such as sampling rates for the requested machine data.
This project is funded by the Baden-Württemberg Ministry of Science, Research and the Arts in the context of the “InnovationCampus Future Mobility".
Patrick SpaneyM. Sc.
Research Assistant, Doctoral Researcher
[Photo: Thomas Düllmann]