@article{UlbrichtMohrAltenburgetal.2021, author = {Ulbricht, Alexander and Mohr, Gunther and Altenburg, Simon J. and Oster, Simon and Maierhofer, Christiane and Bruno, Giovanni}, title = {Can potential defects in LPBF be healed from the laser exposure of subsequent layers?}, series = {Metals : open access journal}, volume = {11}, journal = {Metals : open access journal}, number = {7}, publisher = {MDPI}, address = {Basel}, issn = {2075-4701}, doi = {10.3390/met11071012}, pages = {14}, year = {2021}, abstract = {Additive manufacturing (AM) of metals and in particular laser powder bed fusion (LPBF) enables a degree of freedom in design unparalleled by conventional subtractive methods. To ensure that the designed precision is matched by the produced LPBF parts, a full understanding of the interaction between the laser and the feedstock powder is needed. It has been shown that the laser also melts subjacent layers of material underneath. This effect plays a key role when designing small cavities or overhanging structures, because, in these cases, the material underneath is feed-stock powder. In this study, we quantify the extension of the melt pool during laser illumination of powder layers and the defect spatial distribution in a cylindrical specimen. During the LPBF process, several layers were intentionally not exposed to the laser beam at various locations, while the build process was monitored by thermography and optical tomography. The cylinder was finally scanned by X-ray computed tomography (XCT). To correlate the positions of the unmolten layers in the part, a staircase was manufactured around the cylinder for easier registration. The results show that healing among layers occurs if a scan strategy is applied, where the orientation of the hatches is changed for each subsequent layer. They also show that small pores and surface roughness of solidified material below a thick layer of unmolten material (>200 mu m) serve as seeding points for larger voids. The orientation of the first two layers fully exposed after a thick layer of unmolten powder shapes the orientation of these voids, created by a lack of fusion.}, language = {en} } @article{OsterFritschUlbrichtetal.2022, author = {Oster, Simon and Fritsch, Tobias and Ulbricht, Alexander and Mohr, Gunther and Bruno, Giovanni and Maierhofer, Christiane and Altenburg, Simon}, title = {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}, series = {Metals : open access journal}, volume = {12}, journal = {Metals : open access journal}, number = {6}, publisher = {MDPI}, address = {Basel}, issn = {2075-4701}, doi = {10.3390/met12060947}, pages = {21}, year = {2022}, abstract = {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.}, language = {en} }