TY - JOUR A1 - Oster, Simon A1 - Fritsch, Tobias A1 - Ulbricht, Alexander A1 - Mohr, Gunther A1 - Bruno, Giovanni A1 - Maierhofer, Christiane A1 - Altenburg, Simon T1 - On the Registration of Thermographic In Situ Monitoring Data and Computed Tomography Reference Data in the Scope of Defect Prediction in Laser Powder Bed Fusion JF - Metals N2 - The detection of internal irregularities is crucial for quality assessment in metal-based additive manufacturing (AM) technologies such as laser powder bed fusion (L-PBF). The utilization of in-process thermography as an in situ monitoring tool in combination with post-process X-ray micro computed tomography (XCT) as a reference technique has shown great potential for this aim. Due to the small irregularity dimensions, a precise registration of the datasets is necessary as a requirement for correlation. In this study, the registration of thermography and XCT reference datasets of a cylindric specimen containing keyhole pores is carried out for the development of a porosity prediction model. The considered datasets show variations in shape, data type and dimensionality, especially due to shrinkage and material elevation effects present in the manufactured part. Since the resulting deformations are challenging for registration, a novel preprocessing methodology is introduced that involves an adaptive volume adjustment algorithm which is based on the porosity distribution in the specimen. Thus, the implementation of a simple three-dimensional image-to-image registration is enabled. The results demonstrate the influence of the part deformation on the resulting porosity location and the importance of registration in terms of irregularity prediction. KW - Selective laser melting (SLM) KW - Laser powder bed fusion (L-PBF) KW - Additive manufacturing (AM) KW - Process monitoring KW - Infrared thermography KW - X-ray computed tomography (XCT) KW - Defect detection KW - Image registration PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-549412 DO - https://doi.org/10.3390/met12060947 VL - 12 IS - 6 SP - 1 EP - 21 PB - MDPI AN - OPUS4-54941 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Charmi, Amir A1 - Falkenberg, Rainer A1 - Ávila, Luis A1 - Mohr, Gunther A1 - Sommer, Konstantin A1 - Ulbricht, Alexander A1 - Sprengel, Maximilian A1 - Saliwan Neumann, Romeo A1 - Evans, Alexander A1 - Skrotzki, Birgit T1 - Mechanical anisotropy of additively manufactured stainless steel 316L: An experimental and numerical study JF - Materials Science and Engineering: A N2 - 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. KW - Mechanical anisotropy KW - Residual stress KW - Crystal plasticity KW - Selective laser melting (SLM) KW - Laser beam melting (LBM) PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-511719 DO - https://doi.org/10.1016/j.msea.2020.140154 SN - 0921-5093 VL - 799 SP - 140154 PB - Elsevier B.V. AN - OPUS4-51171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Mohr, Gunther A1 - Altenburg, Simon A1 - Ulbricht, Alexander A1 - Heinrich, Ph. A1 - Baum, D. A1 - Maierhofer, Christiane A1 - Hilgenberg, Kai T1 - In-Situ Defect Detection in Laser Powder Bed Fusion by Using Thermography and Optical Tomography—Comparison to Computed Tomography JF - Metals N2 - 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. KW - Laser powder bed fusion (L-PBF) KW - Selective laser melting (SLM) KW - Additive manufacturing (AM) KW - Process monitoring KW - Infrared thermography KW - Optical tomography KW - Computed tomography (CT) KW - Data fusion KW - Lack-of-fusion PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-502417 DO - https://doi.org/10.3390/met10010103 VL - 10 IS - 1 SP - 103 PB - MDPI CY - Basel, Schweiz AN - OPUS4-50241 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -