Data-driven process, material and structure analysis for additive manufacturing
Funding
Project AMTwin
Additive manufacturing (AM) has the potential to produce optimised, lightweight components. A major challenge in transforming AM into the efficient and reliable commercial application can be seen in the lack of sufficient and systematic knowledge about process-structure-property linkages. Hence, AM components often contain imperfections and inhomogeneities that cause premature failure especially under cyclic loading. Therefore, further development of methods for material qualification, structure and process simulation as well as component construction and quality control is necessary. The advancing digitalisation provides completely new approaches for the analysis of linkages between process parameters, microstructure and properties. By consequently collecting data about the material, process and component a so called digital twin, a digital copy of the AM process, can be created. This digital twin can be used for monitoring and optimisation. Machine learning promises a high potential of innovation which is intended to be used within this project for a quantitative analysis of process-structure-property linkages for AM components under static and cyclic loading.
Objectives
- microstructure characterisation, reconstruction and simulation
- development of data and model based engineering methods for additive manufacturing
- optimisation of the manufacturing process and of the components
Contact Person
Prof. Dr.-Ing. Christoph Leyens
Project Partners
AMTwin is a research cooperation with:
- Prof. Dr.-Ing. habil. Markus Kästner, Chair of Computational and Experimental Solid Mechanics at the Institute of Solid Mechanics
- Prof. Dr.-Ing. habil. Maik Gude, Chair of Lightweight Design and Structural Assessment at the Institute of Lightweight Engineering and Polymer Technology
- Prof. Dr.-Ing. Steffen Ihlenfeldt, Chair of Machine Tools Development and Adaptive Controls at the Institute of Mechatronic Engineering
- Prof. Dr.-Ing. Martina Zimmermann, Department of Materials Characterisation and Testing at Fraunhofer Institute for Material and Beam Technology
- Dr.-Ing. Juliane Thielsch, Forschungsgruppe Werkstoffe in der Abteilung Generative Verfahren am Fraunhofer Institute for Machine Tools and Forming Technology