Fraunhofer Institute for Mechanics of Materials IWMThe DiStEL project aims to establish comprehensive digital materials analysis across the entire value chain of steel components. The use of ontology-based data flows will enable more efficient control of materials properties, energy consumption, and CO₂ emissions, thereby making a significant contribution to the optimization of steel production.
Digital materials analysis along the entire value chain for steel components to increase efficiency, predict service life, and determine the carbon footprint
Ongoing research project
Project description
The manufacture of typical steel components is characterized by a large number of energy-intensive process steps that have a significant influence on the resulting material and component properties. However, due to a lack of data and data links, there is currently no comprehensive overview of this relationship and therefore no possibility of holistically optimizing the process chain in terms of materials properties, energy consumption, CO2 emissions, reuse/recycling potential. There is a lack of a cross-scale ontological description of the processes and materials.
The DiStEL project lays the foundation for the use of ontology-based data flows in production, quality assurance, product development, and recycling/reuse in industrial practice. The aim is to optimize the process chain, extend the service life of components, and reduce the CO₂ footprint. This is to be achieved through the structured collection and AI-based/supported linking of relevant data throughout the entire life cycle of components and materials using a cross-scale simulative and experimental methodological approach. If successful, the ontology-based automated workflow to be developed here will become an industrial standard.
Fraunhofer IWM subproject:
Within the DiStEL project, Fraunhofer IWM is responsible for several key research areas and tasks.
Fraunhofer IWM is involved in work package 3, which deals with materials and fatigue characterization. This includes analyzing the fatigue behavior of a rotor shaft and a bearing inner ring, whereby fatigue strength tests and crack propagation investigations are carried out.
In addition, Fraunhofer IWM is responsible for work package 5, which is dedicated to artificial intelligence for fatigue prediction. In this work package, multimodal models for feature extraction from microstructure images are being developed and methods for determining service life using machine learning and hybrid approaches are being developed.
In addition, Fraunhofer IWM contributes to software integration and workflow development by participating in the development of workflow tools for integrating simulations as part of work package 7. This includes ontology integration into the software platform and the development of evaluation methods for the entire life cycle.
Finally, Fraunhofer IWM is also responsible for digitalization, in particular for the development of ontologies and the establishment of a data space in work package 8. This involves implementing a knowledge graph that enables the linking of materials science information and promotes data exchange along the value chain.
These tasks and focal points illustrate the central role of Fraunhofer IWM in the project and its contribution to the digitalization of materials research in Germany.
Transfer of project results to the following Fraunhofer IWM R&D services for companies:
- Automated workflow for materials-process systems, applicable without expert knowledge.
- Process chain optimization: A holistic view of materials identifies potential for improvement in materials flow and production steps, which increases efficiency and cost-effectiveness.
- Reusability: Digital materials analysis enables the evaluation of the (remaining) service life of components, which promotes safe and simplified reuse.
- CO₂ footprint reduction: By collecting and analyzing data along the value chain, energy consumption, emissions, and resource consumption can be identified and reduced.
