Fraunhofer Institute for Mechanics of Materials IWMStahlDigital has developed digital, ontology-based workflows to optimize steel materials in order to improve traceability and efficiency along the entire processing chain. The project enables innovative approaches to material development and crash safety through structured data analysis and semantic material maps.
Ontology-based interoperable workflows for the development and optimization of steel materials for component use: From semi-finished sheet metal production to crash safety
Completed research project
Project description
Against the backdrop of sustainability, resource scarcity and the circular economy, steel production and processing in Europe are facing a major upheaval. The aim of the StahlDigital project was to develop new digital strategies for the production of steel materials and steel products so that in the future they could be developed faster and more accurately. Innovative methods of digital knowledge and data processing were used to utilize all material and process data along the value and process chains. As part of the project, technologies for an application-specific data space and the mapping of data processing workflows were developed and established using the process chain of sheet steel materials as an example. The performance of these digital tools was demonstrated using industrial application scenarios as part of an end-to-end digital representation of a sheet steel forming process chain, including simulation and experimental data. The entire manufacturing process from the production of semi-finished products to the manufacture of components, including component properties (crash safety), was included.
Fraunhofer IWM subproject:
The task of compiling material and process data along value and process chains for comprehensive utilization presents companies with an enormous challenge. Process data, simulation data and experimental measurements are typically very heterogeneous and can only be summarized in conventional databases with great effort. With the Dataspace Management System (DSMS) developed at Fraunhofer IWM, which is based on innovative data management concepts, material and process data of different types can be stored interoperably in a data space platform and linked with each other, i.e. put in relation to each other. DSMS is unique in that it allows complex process chains to be mapped and analyzed in a simple way. Thanks to an integrated app concept, applications (e.g. scripts, simulation software, machine learning) can be executed manually or automatically on the stored data to generate new knowledge. DSMS impresses with its user-friendliness and our claim to make the complex technologies of modern data management available to the end user in an accessible form. This means that companies do not have to replace previously established databases, but can implement DSMS on top and enjoy all the benefits of modern data management. In StahlDigital, process chains and typical data processing workflows in sheet metal forming were digitalized and evaluated. The application of the DSMS was demonstrated using practical use cases, e.g. in the form of automated workflows for the evaluation of experimentally determined material data and for the creation of material cards and direct integration into a forming simulation.
Transfer of project results to the following Fraunhofer IWM R&D services for companies:
- Support in the development of ontologies as a basis for the use of semantic technologies
- Data management according to the FAIR principles (Findable, Accessible, Interoperable, Reusable)
- Customizable apps and automizable data processing workflows
- Development and implementation of applications and automated workflows for data evaluation
- Support with the virtual mapping of your own production processes
- Extended AI compatibility as a basis for applying AI methods to material and process data
- Future-proof scalability and seamless integration with existing systems
- Additional training opportunities: Data and workflow management for data refinement, data utilization and knowledge generation for metal processing and component use
