Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Automated Tool-Path Generation for Rapid Manufacturing of Additive Manufacturing Directed Energy Deposition Geometries
    ( 2020)
    Biegler, Max
    ;
    Wang, Jiahan
    ;
    Kaiser, Lukas
    ;
    Rethmeier, Michael
    In additive manufacturing (AM) directed energy deposition (DED), parts are built by welding layers of powder or wire feedstock onto a substrate with applications for steel powders in the fields of forging tools, spare parts, and structural components for various industries. For large and bulky parts, the choice of tool-paths influences the build rate, the mechanical 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 DED processes. This contribution presents automated tool-path generation approaches and discusses the results for arbitrary geometries. So-called “zig-zag” and “contour-parallel” processing strategies are investigated and the tool-paths are automatically formatted into machine-readable g-code for experimental validation to build sample geometries. The results are discussed in regard to volume-fill, microstructure, and porosity in dependence of the path planning according to photographs and metallographic cross-sections.
  • Publication
    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.
  • Publication
    In-situ distortions in LMD additive manufacturing walls can be measured with digital image correlation and predicted using numerical simulations
    ( 2018)
    Biegler, Max
    ;
    Graf, Benjamin
    ;
    Rethmeier, Michael
    Distortions in Additive Manufacturing (AM) Laser Metal Deposition (LMD) occur in the newly-built component due to rapid heating and solidification and can lead to shape deviations and cracking. This paper presents a novel approach to quantify the distortions experimentally and to use the results in numerical simulation validation. Digital Image Correlation (DIC) is applied together with optical filters to measure in-situ distortions directly on a wall geometry produced with LMD. The wall shows cyclic expansion and shrinking with the edges bending inward and the top of the sample exhibiting a slight u-shape as residual distortions. Subsequently, a structural Finite Element Analysis (FEA) of the experiment is established, calibrated against experimental temperature profiles and used to predict the in-situ distortions of the sample. A comparison of the experimental and numerical results reveals a good agreement in length direction of the sample and quantitative deviations in height direction, which are attributed to the material model used. The suitability of the novel experimental approach for measurements on an AM sample is shown and the potential for the validated numerical model as a predictive tool to reduce trial-and-error and improve part quality is evaluated.