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 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 - CONF A1 - Merz, Benjamin A1 - Poka, Konstantin A1 - Mohr, Gunther A1 - Hilgenberg, Kai A1 - Polte, Julian T1 - Advanced camera calibration for lens distortion correction in hybrid manufacturing processes: An exemplary application in laser powder bed fusion (PBF-LB/M) N2 - Hybrid additive manufacturing is becoming increasingly important in the field of additive manufacturing. Hybrid approaches combine at least two different manufacturing processes. The focus of this work is the build-up of geometries onto conventionally manufactured parts using Powder Bed Fusion with Laser Beam of Metals (PBF-LB/M). The hybrid build-up requires a precise position detection system inside the PBF-LB/M machines to determine the exact position of the existing component. For this purpose, high-resolution camera systems can be utilized. However, the use of a camera system is associated with several challenges. The captured images are subject to various distortions of the optical path. Due to these distortions, it is not possible to use the images for measurements and, therefore, it is not possible to calculate the positions of objects. In this study a homography matrix is calculated to correct keystone distortion in the images. Different calibration patterns have been tested for the calculation of the homography matrix. The influence of the number of calibration points on the precision of position detection of objects is determined. Furthermore, the influence of an additional camera calibration by using ChArUco boards is evaluated. The result is a camera calibration workflow with associated calibration pattern for a precise position detection of parts inside PBF-LB/M machines allowing a hybrid build-up with minimum physical offset between base component and build-up. T2 - euspen’s 24th International Conference & Exhibition CY - Dublin, Ireland DA - 10.06.2024 KW - Additive manufacturing KW - Hybrid build-up KW - Position detection KW - Camera calibration PY - 2024 SP - 1 EP - 4 AN - OPUS4-60599 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Rehmer, Birgit A1 - Bayram, Faruk A1 - Ávila Calderón, Luis A1 - Mohr, Gunther A1 - Skrotzki, Birgit T1 - BAM reference data: Temperature-dependent Young's and shear modulus data for additively and conventionally manufactured variants of austenitic stainless steel AISI 316L N2 - The elastic properties (Young's modulus, shear modulus) of austenitic stainless steel AISI 316L were investigated between room temperature and 900 °C in an additively manufactured variant (laser powder bed fusion, PBF‑LB/M) and from a conventional process route (hot rolled sheet). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty. The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data. KW - Elastic modulus KW - Young's modulus KW - Shear modulus KW - Additive manufacturing KW - AISI 316L PY - 2023 DO - https://doi.org/10.5281/zenodo.7813835 PB - Zenodo CY - Geneva AN - OPUS4-57288 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Rehmer, Birgit A1 - Bayram, Faruk A1 - Ávila Calderón, Luis A1 - Mohr, Gunther A1 - Skrotzki, Birgit T1 - BAM reference data: Temperature-dependent Young's and shear modulus data for additively and conventionally manufactured variants of Ni-based alloy Inconel IN718 N2 - The elastic properties (Young's modulus, shear modulus) of Ni-based alloy Inconel IN718 were investigated between room temperature and 800 °C in an additively manufactured variant (laser powder bed fusion, PBF‑LB/M) and from a conventional process route (hot rolled bar). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty. The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data. KW - Elastic modulus KW - Young's modulus KW - Shear modulus KW - Additive manufacturing KW - IN718 PY - 2023 DO - https://doi.org/10.5281/zenodo.7813824 PB - Zenodo CY - Geneva AN - OPUS4-57287 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Rehmer, Birgit A1 - Bayram, Faruk A1 - Ávila Calderón, Luis A1 - Mohr, Gunther A1 - Skrotzki, Birgit T1 - BAM reference data: Temperature-dependent Young's and shear modulus data for additively and conventionally manufactured variants of Ti-6Al-4V N2 - The elastic properties (Young's modulus, shear modulus) of titanium alloy Ti-6Al-4V were investigated between room temperature and 400 °C in an additively manufactured variant (laser-based directed energy deposition with powder as feedstock, DED-LB/M) and from a conventional process route (hot rolled bar). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, microstructure, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty. The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data. KW - Elastic modulus KW - Young's modulus KW - Shear modulus KW - Additive manufacturing KW - Ti-6Al-4V PY - 2023 DO - https://doi.org/10.5281/zenodo.7813732 PB - Zenodo CY - Geneva AN - OPUS4-57286 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 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 - CONF A1 - Mohr, Gunther T1 - Comparability issues of test specimens in laser powder bed fusion - how to consider differences in thermal history of complex components and primitive test specimens 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. However, the thermal history during additive manufacturing of complex components can differ significantly from the thermal history of geometrically primitive test specimens. This can result in divergent microstructures and resulting mechanical properties. It drastically limits the comparability of different built parts and requires expensive full component testing. Moreover, the thermal history as the spatiotemporal temperature distribution has been identified as a major cause for flaw formation. Therefore, it can be hypothesized that a similar thermal history between components and test specimens enhances their comparability. In this talk, the concept of representative test specimens is introduced, which enables the transfer of thermal histories from complex geometries to simple geometries, which can lead to better comparability of material properties. T2 - 4th Asia-Pacific International Conference on Additive Manufacturing (APICAM) CY - Melbourne, Australia DA - 30.06.2025 KW - Additive Manufacturing PY - 2025 AN - OPUS4-64527 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Scheuschner, Nils A1 - Oster, Simon A1 - Mohr, Gunther A1 - Hilgenberg, Kai T1 - Comparison of NIR and SWIR thermography for defect detection in Laser Powder Bed Fusion N2 - Since laser powder bed fusion (PBF-LB/M) is prone to the formation of defects during the building process, a fundamental requirement for widespread application is to find ways to assure safety and reliability of the additively manufactured parts. A possible solution for this problem lies in the usage of in-situ thermographic monitoring for defect detection. In this contribution we investigate possibilities and limitations of the VIS/NIR wavelength range for defect detection. A VIS/NIR camera can be based on conventional silicon-based sensors which typically have much higher spatial and temporal resolution in the same price range but are more limited in the detectable temperature range than infrared sensors designed for longer wavelengths. To investigate the influence, we compared the thermographic signatures during the creation of artificially provoked defects by local parameter variations in test specimens made of a nickel alloy (UNS N07208) for two different wavelength ranges (~980 nm and ~1600 nm). KW - Laser powder bed fusion KW - PBF-LB/M KW - Thermography KW - Additive manufacturing KW - NDT PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-610380 DO - https://doi.org/10.1016/j.procir.2024.08.122 VL - 124 SP - 301 EP - 304 PB - Elsevier B.V. AN - OPUS4-61038 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Merz, Benjamin A1 - Knobloch, Tim A1 - Mohr, Gunther A1 - Hilgenberg, Kai T1 - Concepts for bridging voids in metal additive manufacturing for repair of gas turbine blades using laser powder bed fusion N2 - One of the main advantages of additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) is the possibility to manufacture complex near-net-shape components. Therefore, the PBF-LB/M process is becoming increasingly important for the manufacturing and repair of gas turbine blades. Despite the great freedom in design, there are also limitations to the process. Manufacturing overhangs or bridging voids are some of the main challenges. In the conventional PBF-LB/M process, overhangs with angles up to 45° can be manufactured. However, gas turbine blades feature voids for cooling, which have to be bridged when using PBF-LB/M. In this work, different concepts for bridging voids are developed for future application in gas turbine blade repair. For this purpose, a test geometry is derived from the tip area of a gas turbine blade as a reference. By changing the initial geometry of the reference body, different designs for bridging voids are developed based on the PBF-LB/M requirements. Subsequently, these distinct designs are manufactured by PBF-LB/M. The different approaches are compared with respect to their volume increase. In addition, the specimens are visually inspected for warpage, shrinkage and imperfections by overheating. Out of the seven concepts developed, three concepts can be recommended for gas turbine blade repair based on low volume increase, distortion and shrinkage. T2 - Metal Additive Manufacturing Conference - MAMC 2022 CY - Graz, Austria DA - 26.09.2022 KW - Repair of gas turbine blades KW - Laser Powder Bed Fusion (PBF-LB/M) KW - Selective Laser Melting (SLM) KW - Design for Additive Manufacturing (DfAM) KW - Bridging voids KW - Supportless PY - 2022 SP - 19 EP - 28 PB - TU Graz CY - Graz AN - OPUS4-55868 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ávila Calderón, Luis A1 - Rehmer, Birgit A1 - Schriever, Sina A1 - Ulbricht, Alexander A1 - Agudo Jácome, Leonardo A1 - Sommer, Konstantin A1 - Mohr, Gunther A1 - Skrotzki, Birgit A1 - Evans, Alexander T1 - Creep and creep damage behavior of stainless steel 316L manufactured by laser powder bed fusion N2 - This study presents a thorough characterization of the creep properties of austenitic stainless steel 316L produced by laser powder bed fusion (LPBF 316L) contributing to the sparse available data to date. Experimental results (mechanical tests, microscopy, X-ray computed tomography) concerning the creep deformation and damage mechanisms are presented and discussed. The tested LPBF material exhibits a low defect population, which allows for the isolation and improved understanding of the effect of other typical aspects of an LPBF microstructure on the creep behavior. As a benchmark to assess the material properties of the LPBF 316L, a conventionally manufactured variant of 316L was also tested. To characterize the creep properties, hot tensile tests and constant force creep tests at 600 °C and 650 °C are performed. The creep stress exponents of the LPBF material are smaller than that of the conventional variant. The primary and secondary creep stages and the times to rupture of the LPBF material are shorter than the hot rolled 316L. Overall the creep damage is more extensive in the LPBF material. The creep damage of the LPBF material is overall mainly intergranular. It is presumably caused and accelerated by both the appearance of precipitates at the grain boundaries and the unfavorable orientation of the grain boundaries. Neither the melt pool boundaries nor entrapped gas pores show a significant influence on the creep damage mechanism. KW - 316L KW - Laser Powder Bed Fusion (LPBF) KW - Creep behavior KW - Additive Manufacturing KW - AGIL PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-539373 DO - https://doi.org/10.1016/j.msea.2021.142223 SN - 0921-5093 VL - 830 SP - 142223 PB - Elsevier B.V. AN - OPUS4-53937 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -