Ingenieurwissenschaften und zugeordnete Tätigkeiten
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The underlying cause of mechanical anisotropy in additively manufactured (AM) parts is not yet fully understood and has been attributed to several different factors like microstructural defects, residual stresses, melt pool boundaries, crystallographic and morphological textures. To better understand the main contributing factor to the mechanical anisotropy of AM stainless steel 316L, bulk specimens were fabricated via laser powder bed fusion (LPBF). Tensile specimens were machined from these AM bulk materials for three different inclinations: 0◦, 45◦, and 90◦ relative to the build plate. Dynamic Young’s modulus measurements and tensile tests were used to determine the mechanical anisotropy. Some tensile specimens were also subjected to residual stress measurement via neutron diffraction, porosity determination with X-ray micro-computed tomography (μCT), and texture analysis with electron backscatter diffraction (EBSD). These investigations revealed that the specimens exhibited near full density and the detected defects were spherical. Furthermore, the residual stresses in the loading direction were between −74 ± 24 MPa and 137 ± 20 MPa, and the EBSD measurements showed a preferential ⟨110⟩ orientation parallel to the build direction. A crystal plasticity model was used to analyze the elastic anisotropy and the anisotropic yield behavior of the AM specimens, and it was able to capture and predict the experimental behavior accurately. Overall, it was shown that the mechanical anisotropy of the tested specimens was mainly influenced by the crystallographic texture.
A finite element method based three-dimensional heat transfer model with adaptive remeshing is presented to simulate the building of multiple tracks and layers in laser powder bed fusion of metallic powders with enhanced computational competence. A dimensional analysis is undertaken to define the heat source dimensions as function of laser parameters and properties of alloy powder. The computational model is used to calculate the melt pool cross sections for multiple combinations of laser power and scanning velocities considering multi-track-multi-layer builds of SS316L powder. The computed results are verified extensively with the corresponding experimentally measured ones. The model is utilized further to examine its ability to predict defects such as melt track discontinuity and incomplete fusion between neighboring tracks and layers. Overall, the adaptive remeshing and the proposed heat source expression could significantly enhance the model competence by reducing the computational time and memory while maintaining the accuracy of results in simulating laser powder bed fusion of multiple tracks and layers.
Laser powder bed fusion (L-PBF) is the most prominent additive manufacturing (AM) technology for metal part production. Among the high number of factors influencing part quality and mechanical properties, the inter layer time (ILT) between iterative melting of volume elements in subsequent layers is almost completely unappreciated in the relevant literature on L-PBF. This study investigates the effect of ILT with respect to build height and under distinct levels of volumetric energy density (VED) using the example of 316L stainless steel. In-situ thermography is used to gather information on cooling conditions during the process, which is followed by an extensive metallographic analysis. Significant effects of ILT and build height on heat accumulation, sub-grain sizes, melt pool geometries and hardness are presented. Furthermore, the rise of defect densities can be attributed to a mutual interplay of build height and ILT. Hence, ILT has been identified as a crucial factor for L-PBF of real part components especially for those with small cross sections.
Among additive manufacturing (AM) technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components. The layer-wise build-up of components and the complex process conditions increase the probability of the occurrence of defects. However, due to the iterative nature of its manufacturing process and in contrast to conventional manufacturing technologies such as casting, L-PBF offers unique opportunities for in-situ monitoring. In this study, two cameras were successfully tested simultaneously as a machine manufacturer independent process monitoring setup: a high-frequency infrared camera and a camera for long time exposure, working in the visible and infrared spectrum and equipped with a near infrared filter. An AISI 316L stainless steel specimen with integrated artificial defects has been monitored during the build. The acquired camera data was compared to data obtained by computed tomography. A promising and easy to use examination method for data analysis was developed and correlations between measured signals and defects were identified. Moreover, sources of possible data misinterpretation were specified. Lastly, attempts for automatic data analysis by data Integration are presented.