TY - JOUR A1 - Mohr, Gunther A1 - Sommer, Konstantin A1 - Knobloch, Tim A1 - Altenburg, Simon A1 - Recknagel, Sebastian A1 - Bettge, Dirk A1 - Hilgenberg, Kai T1 - Process Induced Preheating in Laser Powder Bed Fusion Monitored by Thermography and Its Influence on the Microstructure of 316L Stainless Steel Parts JF - Metals N2 - Undetected and undesired microstructural variations in components produced by laser powder bed fusion are a major challenge, especially for safety-critical components. In this study, an in-depth analysis of the microstructural features of 316L specimens produced by laser powder bed fusion at different levels of volumetric energy density and different levels of inter layer time is reported. The study has been conducted on specimens with an application relevant build height (>100 mm). Furthermore, the evolution of the intrinsic preheating temperature during the build-up of specimens was monitored using a thermographic in-situ monitoring set-up. By applying recently determined emissivity values of 316L powder layers, real temperatures could be quantified. Heat accumulation led to preheating temperatures of up to about 600 °C. Significant differences in the preheating temperatures were discussed with respect to the individual process parameter combinations, including the build height. A strong effect of the inter layer time on the heat accumulation was observed. A shorter inter layer time resulted in an increase of the preheating temperature by more than a factor of 2 in the upper part of the specimens compared to longer inter layer times. This, in turn, resulted in heterogeneity of the microstructure and differences in material properties within individual specimens. The resulting differences in the microstructure were analyzed using electron back scatter diffraction and scanning electron microscopy. Results from chemical analysis as well as electron back scatter diffraction measurements indicated stable conditions in terms of chemical alloy composition and austenite phase content for the used set of parameter combinations. However, an increase of the average grain size by more than a factor of 2.5 could be revealed within individual specimens. Additionally, differences in feature size of the solidification cellular substructure were examined and a trend of increasing cell sizes was observed. This trend was attributed to differences in solidification rate and thermal gradients induced by differences in scanning velocity and preheating temperature. A change of the thermal history due to intrinsic preheating could be identified as the main cause of this heterogeneity. It was induced by critical combinations of the energy input and differences in heat transfer conditions by variations of the inter layer time. The microstructural variations were directly correlated to differences in hardness. KW - Additive manufacturing KW - Laser powder bed fusion KW - In-situ process monitoring KW - Thermography KW - Heat accumulation KW - Inter layer time KW - Cellular substructure PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-529240 DO - https://doi.org/10.3390/met11071063 VL - 11 IS - 7 SP - 1063 PB - MDPI CY - Basel, Schweiz AN - OPUS4-52924 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ulbricht, Alexander A1 - Mohr, Gunther A1 - Altenburg, Simon A1 - Oster, Simon A1 - Maierhofer, Christiane A1 - Bruno, Giovanni ED - Czujko, T. ED - Benedetti, M. T1 - Can Potential Defects in LPBF Be Healed from the Laser Exposure of Subsequent Layers? A Quantitative Study JF - Metals N2 - 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 µm) 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. KW - Computed tomography KW - Laser Powder Bed Fusion KW - In situ monitoring KW - infrared Thermography KW - Optical Tomography KW - Additive manufacturing KW - AISI 316L PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-528778 DO - https://doi.org/10.3390/met11071012 VL - 11 IS - 7 SP - 1012 PB - MDPI CY - Basel AN - OPUS4-52877 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 - Oster, Simon A1 - Breese, Philipp Peter A1 - Ulbricht, Alexander A1 - Mohr, Gunther A1 - Altenburg, Simon T1 - A deep learning framework for defect prediction based on thermographic in-situmonitoring in laser powder bed fusion JF - Journal of Intelligent Manufacturing N2 - The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers. Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity. KW - Laser Powder Bed Fusion (PBF-LB/M, L-PBF) KW - Selective Laser Melting (SLM) KW - SWIR thermography KW - Online monitoring KW - Flaw detection KW - Machine learning KW - Convolutional neural networks (CNN) PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-575148 DO - https://doi.org/10.1007/s10845-023-02117-0 SN - 0956-5515 SP - 1 EP - 20 PB - Springer AN - OPUS4-57514 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Mohr, Gunther A1 - Altenburg, Simon A1 - Hilgenberg, Kai T1 - On the limitations of small cubes as test coupons for process parameter optimization in laser powder bed fusion of metals JF - Journal of Laser Applications N2 - The capability to produce complexly and individually shaped metallic parts is one of the main advantages of the laser powder bed fusion (PBF LB/M) process. Development of material and machine specific process parameters is commonly based on results acquired from small cubic test coupons of about 10 mm edge length. Such cubes are usually used to conduct an optimization of process parameters to produce dense material. The parameters are then taken as the basis for the manufacturing of real part geometries. However, complex geometries go along with complex thermal histories during the manufacturing process, which can significantly differ from thermal conditions prevalent during the production of simply shaped test coupons. This may lead to unexpected and unpredicted local inhomogeneities of the microstructure and defect distribution in the final part and it is a root cause of reservations against the use of additive manufacturing for the production of safety relevant parts. In this study, the influence of changing thermal conditions on the resulting melt pool depth of 316L stainless steel specimens is demonstrated. A variation of thermo-graphically measured intrinsic preheating temperatures was triggered by an alteration of inter layer times and a variation of cross section areas of specimens for three distinct sets of process parameters. Correlations between the preheating temperature, the melt pool depth, and occurring defects were analyzed. The limited expressiveness of the results of small density cubes is revealed throughout the systematic investigation. Finally, a clear recommendation to consider thermal conditions in future process parameter optimizations is given. T2 - Icaleo 2023 CY - Chicago, IL, USA DA - 16.10.2023 KW - Additive manufacturing KW - Heat accumulation KW - Thermal history KW - In situ monitoring KW - Representative specimens KW - Thermography PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586558 DO - https://doi.org/10.2351/7.0001080 SN - 1042-346X VL - 35 IS - 4 SP - 1 EP - 10 AN - OPUS4-58655 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Sprengel, Maximilian A1 - Mohr, Gunther A1 - Altenburg, Simon A1 - Evans, Alexander A1 - Serrano Munoz, Itziar A1 - Kromm, Arne A1 - Pirling, T. A1 - Bruno, Giovanni A1 - Kannengießer, Thomas T1 - Triaxial Residual Stress in Laser Powder Bed Fused 316L: Effects of Interlayer Time and Scanning Velocity JF - Advanced Engineering Materials N2 - The triaxial distribution of the residual stress in laser powder bed fused austenitic steel 316L was determined by X-ray and neutron diffraction. The residual stress analysis results were linked to the thermal history of the specimens, which were manufactured with varying inter-layer-times and scanning velocities. A clear link between the in-process temperature of the specimens and the residual stress was found, based on in-situ monitoring data. KW - Stainless Steel KW - AGIL KW - Residual Stress KW - X-ray and Neutron Diffraction KW - Additive Manufacturing PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-542620 DO - https://doi.org/10.1002/adem.202101330 SP - 1 EP - 13 PB - Wiley-VCH GmbH AN - OPUS4-54262 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -