Intelligent data-guided process design for fatigue-resistant steel components using the example of bainitic microstructure

Project runtime: 01.03.2021 – 28.02.2023

Using artificial intelligence to optimise durable steel components

Artificial intelligence is revolutionising many areas of our daily lives, from personalised internet advertising to self-driving cars and self-optimising industrial plants. The iBain project aims to establish artificial material intelligence for optimising high-strength steels. Bainite, a specific steel structure, has outstanding mechanical properties due to its complex inner structure, which can be deliberately adjusted during production. This internal structure already places the highest demands on analysis and interpretation. Therefore, automatic pattern recognition and simulations are used to complement experimental findings. Statistical methods of experimental design (so-called "Design of Experiments") help to plan experiments and simulations, as well as to avoid redundancies. Finally, an automated control of the workflow and data flow is established: "automated workflow". As a result, a customised production flow is proposed to produce optimised products with superior properties. Accelerated and simplified product development thus contributes to securing jobs in Germany as a high-wage location and to sustainable industrial production.

Tasks within the project Location
Ruhr-University Bochum
Phase-field simulation, data-driven methods and material intelligence
Fraunhofer Institute for Mechanics of Materials IWM
Micro-experiments, multimodal registration of material data, AI-supported predictions, integration of knowledge in knowledge graphs, material ontologies
RWTH Aachen University
Training and verification of AI concepts