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Automated tool-path generation for rapid manufacturing and numerical simulation of additive manufacturing LMD geometries

2019 , Biegler, Max , Wang, Jiahan , Graf, Benjamin , Rethmeier, Michael

In additive manufacturing (AM) Laser Metal Deposition (LMD), parts are built by welding layers of powder feedstock onto a substrate. Applications for steel powders include forging tools and structural components for various industries. For large parts, the choice of tool-paths influences the build-rate, the part performance and the distortions in a highly geometry-dependent manner. With weld-path lengths in the range of hundreds of meters, a reliable, automated tool path generation is essential for the usability of LMD processes. In this contribution, automated tool-path generation approaches are shown and their results are discussed for arbitrary geometries. The investigated path strategies are the classical approaches: ""Zig-zag-"" and ""contour-parallel-strategies"". After generation, the tool-paths are automatically formatted into g-code for experimental build-up and ASCII for a numerical simulation model. Finally, the tool paths are discussed in regards to volume-fill, microstructure and porosity for the experimental samples. This work presents a part of the IGF project 18737N ""Welding distortion simulation"" (FOSTA P1140)

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Assessing the predictive capability of numerical additive manufacturing simulations via in-situ distortion measurements on a LMD component during build-up

2018 , Biegler, Max , Graf, Benjamin , Rethmeier, Michael

Due to rapid, localized heating and cooling, distortions accumulate in additive manufactured laser metal deposition (LMD) components, leading to a loss of dimensional accuracy or even cracking. Numerical welding simulations allow the prediction of these deviations and their optimization before conducting experiments. To assess the viability of the simulation tool for the use in a predictive manner, comprehensive validations with experimental results on the newly-built part need to be conducted. In this contribution, a predictive, mechanical simulation of a thin-walled, curved LMD geometry is shown for a 30-layer sample of 1.4404 stainless steel. The part distortions are determined experimentally via an in-situ digital image correlation measurement using the GOM Aramis system and compared with the simulation results. With this benchmark, the performance of a numerical welding simulation in additive manufacturing is discussed in terms of result accuracy and usability.