13 Zentrale Universitätseinrichtungen

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/14

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Start date: 2021End date: 2024Subject: search.filters.subject.670Subject: search.filters.subject.620

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    Micro-twinning in IN738LC manufactured with laser powder bed fusion
    (2023) Megahed, Sandra; Krämer, Karl Michael; Kontermann, Christian; Heinze, Christoph; Udoh, Annett; Weihe, Stefan; Oechsner, Matthias
    Components manufactured with Metal Laser Powder Bed Fusion (PBF-LB/M) are built in a layerwise fashion. The PBF-LB/M build orientation affects grain morphology and orientation. Depending on the build orientation, microstructures from equiaxed to textured grains can develop. In the case of a textured microstructure, a clear anisotropy of the mechanical properties affecting short- and long-term mechanical properties can be observed, which must be considered in the component design. Within the scope of this study, the IN738LC tensile and creep properties of PBF-LB/M samples manufactured in 0° (perpendicular to build direction), 45° and 90° (parallel to build direction) build orientations were investigated. While the hot tensile results (at 850 °C) are as expected, where the tensile properties of the 45° build orientation lay between those of 0° and 90°, the creep results (performed at 850 °C and 200 MPa) of the 45° build orientation show the least time to rupture. This study discusses the microstructural reasoning behind the peculiar creep behavior of 45° oriented IN738LC samples and correlates the results to heat-treated microstructures and the solidification conditions of the PBF-LB/M process itself.
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    A universal framework for skill-based cyber-physical production systems
    (2024) Hossfeld, Max; Wortmann, Andreas
    In the vision of smart manufacturing and Industry 4.0, it is vital to automate production processes. There is a significant gap in current practices, where the derivation of production processes from product data still heavily relies on human expertise, leading to inefficiencies and a shortage of skilled labor. This paper proposes a universal framework for skill-based cyber-physical production systems (CPPS) that formalizes production knowledge into machine-processable formats. Key contributions include a novel conceptual model for skill-based production processes and an automated method to derive production plans from high-level CPPS skills for production planning and execution. This framework aims to enhance smart manufacturing by enabling more efficient, transparent, and automated production planning, thereby addressing the critical gap in current manufacturing practices. The framework’s benefits include making production processes explainable, optimizing multi-criteria systems, and eliminating human biases in process selection. A case study illustrates the framework’s application, demonstrating its current capabilities and potential for modern manufacturing.