Digital material analysis along the entire value chain for steel components to increase efficiency, predict service life and determine the carbon footprint

Project runtime: 01.01.2025 - 31.12.2028

Contact Person(s)

• Allgemein | Alexander Dyck | ...@de.bosch.com

Publications

• Mining Multimodal Fatigue Data Using Reasoning Foundation Models and Formalized Domain Knowledge | Jyoti Prakash Mohanty; Akhil Thomas; Tresa M. Pollock; Ali Riza Durmaz (2025) | DOI: 10.26434/chemrxiv-2025-xwd6c

• Recycling-Induced Copper Contamination of a 42CrMo4 Quench and Tempering Steel—Scaling and Susceptibility to Hot Shortness | Alexander Gramlich, Sindokht Shayan, Nima Babaei, Aleksei Klubakov, Lena Patterer, Ulrich Krupp, Hauke Springer (2026) | DOI: https://doi.org/10.1002/srin.202400844

• Influence of Steel Recycling on Phase Transformation in Medium-Manganese Third-Generation Advanced High-Strength Steels | Anindita Chakraborty, Radhakanta Rana, Ulrich Krupp, Alexander Gramlich (2026) | DOI: https://doi.org/10.1002/srin.202400841

• Circular Steel for Fast Decarbonization: Thermodynamics, Kinetics, and Microstructure Behind Upcycling Scrap into High-Performance Sheet Steel | Dierk Raabe, Matic Jovičević-Klug, Dirk Ponge, Alexander Gramlich, Alisson Kwiatkowski da Silva, A. Nicholas Grundy, Hauke Springer, Isnaldi Souza Filho and Yan Ma (2026) | DOI: https://doi.org/10.1146/annurev-matsci-080222-123648

PMD Vollversammlung 26.11. - 28.11.2025

2025-11-26_DiStEL_VV_Präsentation

The production 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 holistic optimization of the process chain with regard to material properties, energy consumption, CO2 emissions, reuse / recycling capacity. There is no cross-scale ontological description of the processes and materials.

The project lays the foundation for the use of ontology-based data flows in production, quality assurance, product development and recycling/reuse in the industrial practice. The partners Bosch, Schäffler, BMW, DECOIT, LRP and Smoods see the digital transformation for describing the system and component life cycle as a decisive element for securing the future of Germany as an industrial location in international competition. If successful, the ontology-based automated workflow to be developed here will become an industrial standard.