TY - CONF A1 - Mishurova, Tatiana T1 - 3D imaging and residual stress analysis of AM materials at BAM N2 - The overview of the activity of group 8.5 Micro-NDT (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). T2 - Seminar at Chalmers University and Centre for Additive Manufacture (CAM2) CY - Gothenburg, Sweden DA - 19.05.2022 KW - Additive manufacturing KW - Laser powder bed fusion KW - Residual stress KW - Computed tomography KW - Synchrotron X-ray diffraction KW - X-ray refraction PY - 2022 AN - OPUS4-55019 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Roveda, Ilaria T1 - Investigation of residual stresses and microstructure effects on the fatigue behaviour of a L-PBF AlSi10Mg alloy N2 - Laser Powder Bed Fusion (L-PBF) allow the fabrication of lightweight near net shape AlSi10Mg components attractive to the aerospace, automotive, biomedical and military industries. During the build-up process, high cooling rates occur. Thus, L-PBF AlSi10Mg alloys exhibit a Si-nanostructure in the as-built condition, which leads to superior mechanical properties compared to conventional cast materials. At the same time, such high thermal gradients generally involve a deleterious residual stress (RS) state that needs to be assessed during the design process, before placing a component in service. To this purpose post-process heat treatments are commonly performed to relieve detrimental RS. In this contribution two low-temperature stress-relief heat treatments (SRHT) are studied and compared with the as-built state: a SRHT at 265°C for 1 hour and a SRHT at 300°C for 2 hours. At these temperatures microstructural changes occur. In the as-built state, Si atoms are supersaturated in the α-aluminium matrix, which is enveloped by a eutectic Si-network. At 265°C the Si precipitation from the matrix to the pre-existing network is triggered. Thereafter, above 295°C the fragmentation and spheroidization of the Si branches takes place, presumably by Al–Si interdiffusion. After 2 hours the original eutectic network is completely replaced by uniformly distributed blocky particles. The effect of the heat and the microstructure modification on the RS state and the fatigue properties is investigated. Energy dispersive x-ray and neutron diffraction are combined to investigate the near-surface and bulk RS state of a L-PBF AlSi10Mg material. Differences in the endurance limit are evaluated experimentally by high cycle fatigue (HCF) tests and cyclic R-curve determination. T2 - 43rd Materials Mechanics Seminar CY - Sani, Chalkidiki, Greece DA - 05.06.2022 KW - AlSi10Mg KW - Fatigue KW - Neutron diffraction KW - X-ray diffraction PY - 2022 AN - OPUS4-55090 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mishurova, Tatiana T1 - 3D Imaging and residual stress analysis of additively manufactured materials N2 - The focus of the presentation focus will be on 3D imaging by means of X-ray Computed Tomography (XCT) at the lab and at synchrotron, and the non-destructive residual stress (RS) characterization by diffraction of additively manufactured (AM) materials in BAM (Berlin, Germany). The manufacturing defects and high RS are inherent of AM techniques and affect structural integrity of the components. Using XCT the defects size and shape distribution as well as geometrical deviations can be characterized, allowing the further optimization of the manufacturing process. Diffraction-based RS analysis methods using neutron and synchrotron X-rays at large scale facilities offer the possibility to non-destructively spatially resolve both surface and bulk RS in complex components and track their changes following applied thermal or mechanical loads. T2 - The International Symposium on Nondestructive Characterization of Materials 2023 CY - Zurich, Switzerland DA - 15.08.2023 KW - Additive manufacturing KW - Residual stress KW - X-ray computed tomography PY - 2023 AN - OPUS4-58113 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mishurova, Tatiana T1 - Failure Mechanisms Investigation by Means of in-situ Synchrotron Computed Tomography in Aluminum MMC-based Alloy Tailored for Additive Manufacturing N2 - Synchrotron X-ray computed tomography (SXCT) at BAMline has been paired with in-situ tensile loading to monitor damage evolution in LPBF Metal Matrix Composite (MMC) 7017 Aluminium alloy + 3 wt% Zr + 0.5 wt% TiC. The processing of the material leads formation to different categories of Zr-rich inclusions, precipitates and defects. In-situ SXCT test disclosed the critical role of the pre-cracks in the reinforcement phases in the failure mechanisms of LPBF MMC. The damage was initiated from lack-of-fusion defects and cracks propagated through coalescence with other defects. T2 - HZB Uer Meeting 2023 CY - Berlin, Germany DA - 22.06.23 KW - Additive manufacturing KW - BAMline KW - Synchrotron X-ray computed tomography KW - in-situ PY - 2023 AN - OPUS4-57801 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Khrapov, D. A1 - Kozadayeva, M. A1 - Koptyug, A. A1 - Mishurova, Tatiana A1 - Meinel, Dietmar A1 - Surmenev, R. A1 - Surmeneva, M. T1 - Geometrical features and mechanical properties of the sheet-based gyroid scaffolds with functionally graded porosity manufactured by electron beam melting N2 - Functionally graded porous scaffolds (FGPS) constructed with pores of different size arranged as spatially continuous structure based on sheet-based gyroid with three different scaling factors of 0.05, 0.1 and 0.2 were produced by electron beam powder bed fusion. The pore dimensions of the obtained scaffolds satisfy the values required for optimal bone tissue ingrowth. Agglomerates of residual powder were found inside all structures, which required post-manufacturing treatment. Using X-ray Computed Tomography powder agglomerations were visualized and average wall thickness, wall-to-wall distances, micro- and macro-porosities were evaluated. The initial cleaning by powder recovery system (PRS) was insufficient for complete powder removal. Additional treatment by dry ultrasonic vibration (USV) was applied and was found successful for gyroids with the scaling factors of 0.05 and 0.1. Mechanical properties of the samples, including quasi-elastic gradients and first maximum compressive strengths of the structures before and after USV were evaluated to prove that additional treatment does not produce structural damage. The estimated quasi-elastic gradients for gyroids with different scaling factors lie in a range between 2.5 and 2.9 GPa, while the first maximum compressive strength vary from 52.5 for to 59.8 MPa, compressive offset stress vary from 46.2 for to 53.2 MPa. KW - Additive manufacturing KW - Electron beam KW - Powder bed fusion KW - Triply periodic minimal surfaces KW - Functionally graded porous scaffolds KW - X-ray computed tomography PY - 2023 DO - https://doi.org/10.1016/j.mtcomm.2023.106410 SN - 2352-4928 VL - 35 SP - 1 EP - 9 PB - Elsevier Ltd. AN - OPUS4-57682 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Obaton, A.-F. A1 - Fain, J. A1 - Meinel, Dietmar A1 - Tsamos, Athanasios A1 - Léonard, F. A1 - Lécuelle, B. A1 - Djemaï, M. T1 - In Vivo Bone Progression in and around Lattice Implants Additively Manufactured with a New Titanium Alloy N2 - The osseointegration in/around additively manufactured (AM) lattice structures of a new titanium alloy, Ti–19Nb–14Zr, was evaluated. Different lattices with increasingly high sidewalls gradually closing them were manufactured and implanted in sheep. After removal, the bone–interface implant (BII) and bone–implant contact (BIC) were studied from 3D X-ray computed tomography images. Measured BII of less than 10 µm and BIC of 95% are evidence of excellent osseointegration. Since AMnaturally leads to a high-roughness surface finish, the wettability of the implant is increased. The new alloy possesses an increased affinity to the bone. The lattice provides crevices in which the biological tissue can jump in and cling. The combination of these factors is pushing ossification beyond its natural limits. Therefore, the quality and speed of the ossification and osseointegration in/around these Ti–19Nb–14Zr laterally closed lattice implants open the possibility of bone spline key of prostheses. This enables the stabilization of the implant into the bone while keeping the possibility of punctual hooks allowing the implant to be removed more easily if required. Thus, this new titanium alloy and such laterally closed lattice structures are appropriate candidates to be implemented in a new generation of implants. KW - Osseointegration KW - X-ray computed tomography KW - Additive manufacturing KW - Machine learning segmentation PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-577066 DO - https://doi.org/10.3390/app13127282 VL - 13 IS - 12 SP - 1 EP - 18 PB - MDPI CY - Basel, Switzerland AN - OPUS4-57706 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mishurova, Tatiana T1 - Applications of x-ray computed tomography in material science N2 - The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field material characterization by X-ray imaging is presented. The principle of X-ray Computed Tomography (XCT) is explained. The multiple examples of application of quantitative analysis by XCT are reported, such as additive manufacturing, Li-ion battery, concrete research. T2 - Lecture for PhD students at Politecnico di Torino CY - Turin, Italy DA - 14.03.2024 KW - X-ray computed tomography KW - Additive manufacturing PY - 2024 AN - OPUS4-59689 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mishurova, Tatiana T1 - In-situ hot isostatic pressing combined with x-ray imaging and diffraction of laser powder bed fusion ti-6al-4v N2 - Hot Isostatic Pressing (HIP) is often introduced to tackle the porosity issue in additively manufactured (AM) materials. For instance, HIP post-processing is recommended to improve fatigue resistance of Laser powder bed fusion (PBF-LB) manufactured parts [1, 2]. Even though HIP cannot completely remove porosity, it significantly decreases the defect population and its average size below the critical threshold value leading to early crack initiation. In the present study, in-situ investigation of HIP procedure of PBF-LB Ti-6Al-4V parts was carried out to gain further insights into the densification mechanism occurring during HIP. The in-situ observations at high pressure and high temperature are uniquely possible at the PSICHE beamline of the Soleil synchrotron (France), thanks to the Ultrafast Tomography on a Paris-Edinburgh Cell (UToPEC) and the combination of the fast phase-contrast tomography and energy-dispersive diffraction [3, 4]. A detailed methodology was developed to ensure that the correct pressure and temperature were maintained during the experiments. The results allowed an estimation of the global dentification rate during HIP of PBF-LB Ti-Al-4V material, as well as a detailed quantitative characterization of the influence of pore size and shape on the densification process, thereby understanding the effectiveness of HIP process on different pore categories. After 20 mins, 75% of porosity can be considered as closed or has size below the resolution of the XCT reconstruction. We also observed that the smallest defects showed higher densification rate, while the defect shape did not have significant effect on such rate. The current development of in-situ HIP experiment allows experimental quantification and validation of the simulation work. Ultimately it paves the road to tailoring the HIP procedure for different materials depending on the porosity and microstructure. T2 - AAMS 2023 CY - Madrid, Spain DA - 26.09.23 KW - Additive manufacturing KW - HIP KW - X-ray computed tomography PY - 2023 AN - OPUS4-58482 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mishurova, Tatiana T1 - 3D imaging and residual stress analysis for AM Materials N2 - The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). T2 - Seminar at Integrated Additive Manufacturing center, Politecnico Torino CY - Turin, Italy DA - 14.02.2023 KW - Additive manufacturing KW - Laser powder bed fusion KW - Residual stress KW - Computed tomography KW - Synchrotron X-ray diffraction PY - 2023 AN - OPUS4-57047 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Evans, Alexander T1 - Introduction to AGIL N2 - An introduction to the Themenfeld Material project AGIL will be presented. The concept of the project, the work package structure and the material used within the project will be presented. T2 - 2nd Workshop on In situ Monitoring and Microstructure Development in Additive Manufacturing CY - Online meeting DA - 19.04.2021 KW - AGIL KW - Ageing KW - Additive manufacturing KW - Laser powder bed fusion PY - 2021 AN - OPUS4-54107 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - D'Accardi, E. A1 - Krankenhagen, Rainer A1 - Ulbricht, Alexander A1 - Pelkner, Matthias A1 - Pohl, Rainer A1 - Palumbo, D. A1 - Galietti, U. T1 - Capability to detect and localize typical defects of laser powder bed fusion (L‑PBF) process: an experimental investigation with different non‑destructive techniques N2 - Additive manufacturing (AM) technologies, generally called 3D printing, are widely used because their use provides a high added value in manufacturing complex-shaped components and objects. Defects may occur within the components at different time of manufacturing, and in this regard, non-destructive techniques (NDT) represent a key tool for the quality control of AM components in many industrial fields, such as aerospace, oil and gas, and power industries. In this work, the capability of active thermography and eddy current techniques to detect real imposed defects that are representative of the laser powder bed fusion process has been investigated. A 3D complex shape of defects was revealed by a μCT investigation used as reference results for the other NDT methods. The study was focused on two different types of defects: porosities generated in keyhole mode as well as in lack of fusion mode. Different thermographic and eddy current measurements were carried out on AM samples, providing the capability to detect volumetric irregularly shaped defects using non-destructive methods. KW - Additive Manufacturing KW - Defect detection KW - Thermography KW - Eddy-current testing KW - Micro-computed tomography PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546680 DO - https://doi.org/10.1007/s40964-022-00297-4 SN - 2363-9512 VL - 7 IS - 6 SP - 1239 EP - 1256 PB - Springer AN - OPUS4-54668 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Evans, Alexander A1 - Przyklenk, A. T1 - European Metrology Network for Advanced Manufacturing N2 - The progress of Advanced Manufacturing, which has been identified by the European Commission as a Key Enabling Technology (KET) for future economic and societal progress is strongly reliant on the development of metrology capabilities. EURAMET, the association of metrology institutes in Europe, has established metrology research programs to address the metrology requirements across a spectrum of different thematic areas. In order to leverage the benefits of these developments on the wider industrial landscape, a high-level coordination of the metrology community supporting the Advanced Manufacturing landscape is required. This coordination is aimed to be achieved by the establishment of European Metrology Networks (EMNs), which are intended by EURAMET to provide a sustainable structure for stakeholder engagement and support. The joint networking project 19NET01 AdvManuNet funded by EMPIR for 4 years, started in June 2020 and aims to accelerate the process of establishing an EMN to strengthen Europe’s position in Advanced Manufacturing. The AdvManuNet project aims to support the establishment of an EMN on Advanced Manufacturing via the following specific aims: 1. Creation of a single hub for stakeholder engagement across the landscape of various industrial sectors including relevant societies and standardization bodies. 2. Development of a Strategic Research Agenda (SRA) and roadmaps for Advanced Manufacturing metrology based on the stakeholder engagement activities, considering current gaps in metrological capabilities existing networks and roadmaps. 3. Establish a knowledge-sharing program for Advanced Manufacturing stakeholders, promoting the dissemination and exploitation of the results of the project, including those from previous EU funded research projects. 4. Development of a sustainable web-based platform and service desk for Advanced Manufacturing stakeholders to allow for easy access to European metrology capabilities and support the wider advanced manufacturing community with metrology-based requirements. 5. Develop a plan for a coordinated and sustainable European metrology infrastructure for Advanced Manufacturing via a European Metrology Network. The project concept followed by the scope and definition of Advanced Manufacturing will be described. The analysis of the current capability of metrology for Advanced Manufacturing and the preliminary concepts for the strategic research agenda will be presented with a focus on dimensional metrology. T2 - CIM 2021 CY - Online meeting DA - 07.09.2021 KW - Advanced manufacturing KW - Metrology KW - European Metrology Networks (EMNs) KW - Strategic Research Agenda (SRA) KW - Stakeholder PY - 2021 AN - OPUS4-54101 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ulbricht, Alexander T1 - Do Microbes like Additively Manufactured Aluminium? First Details of a Corrosion Test using Sulphate-Reducing Bacteria N2 - Additively manufactured metals become relevant for industrial application. Although many studies on wet corrosion of these metals have been conducted, to the authors knowledge no study seems to contain microbiological corrosion (MIC). In the presented study an experiment was conducted on PBF-LB/AlSi10Mg to test this material's susceptibility for MIC. The tested specimen were analysed using Computed Tomography before and after the MIC experiment to enable a detailed characterisation the damage on the specimens' global and local level. A global reduction of material was observed. In addition, localised damage along process inherent features of the materials microstructure was observed. T2 - Beiratssitzung TF Umwelt CY - Berlin, Germany DA - 17.03.2025 KW - Computed Tomography KW - Additive Manufacturing KW - Biocorrosion KW - Sulphate-reducing Bacteria KW - Microbially influenced corrosion PY - 2025 AN - OPUS4-62772 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - O'Connor, Daniel T1 - European Metrology Network (EMN) for Advanced Manufacturing Development of the Strategic Research Agenda (SRA) N2 - The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community. The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing. This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing. T2 - Euspen, 23rd International Conference & Exhibitio CY - Copenhagen, Danmark DA - 13.06.2023 KW - European Metrology Network (EMN) KW - Advanced Manufacturing KW - Metrology KW - Strategic Research Agenda (SRA) PY - 2023 AN - OPUS4-59176 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon T1 - Local porosity prediction in metal powder bed fusion using in-situ thermography: A comparative study of machine learning techniques N2 - The formation of flaws such as internal porosity in parts produced by Metal-based Powder Bed Fusion with Laser Beam (PBF-LB/M) significantly hinders its broader industrial application, as porosity can potentially lead to part failure. Addressing this issue, this study explores the efficacy of in-situ thermography, particularly short-wave infrared thermography, for detecting and predicting porosity during manufacturing. This technique is capable of monitoring the part’s thermal history which is closely connected to the flaw formation process. Recent advancements in Machine Learning (ML) have been increasingly leveraged for porosity prediction in PBF-LB/M. However, previous research primarily focused on global rather than localized porosity prediction which simplified the complex prediction task. Thereby, the opportunity to correlate the predicted flaw position with expected part strain to judge the severity of the flaw for part performance is neglected. This study aims to bridge this gap by studying the potential of SWIR thermography for predicting local porosity levels using regression models. The models are trained on data from two identical HAYNES®282® specimens. We compare the effectiveness of feature-based and raw data-based models in predicting different porosity types and examine the importance of input data in porosity prediction. We show that models trained on SWIR thermogram data can identify systematic trends in local flaw formation. This is demonstrated for forced flaw formation using process parameter shifts and, moreover, for randomly formed flaws in the specimen bulk. Furthermore, we identify features of high importance for the prediction of lack-of-fusion and keyhole porosity from SWIR monitoring data. KW - PBF-LB/M KW - In situ monitoring KW - Thermography KW - Additive Manufacturing KW - Process monitoring KW - Porosity prediction KW - Machine Learning KW - Feature extraction PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-621798 DO - https://doi.org/10.1016/j.addma.2024.104502 SN - 2214-7810 VL - 95 SP - 1 EP - 17 PB - Elsevier B.V. AN - OPUS4-62179 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon T1 - From Thermographic In-situ Monitoring to Porosity Detection – A Deep Learning Framework for Quality Control in Laser Powder Bed Fusion N2 - In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk. T2 - Sensor and Measurement Science International CY - Nurnberg, Germany DA - 08.05.2023 KW - Laser powder bed fusion KW - In-situ monitoring KW - Thermography KW - Machine Learning KW - Porosity PY - 2023 AN - OPUS4-57614 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Roveda, Ilaria A1 - Serrano-Munoz, Itziar A1 - Kromm, Arne A1 - Madia, Mauro T1 - Investigation of residual stresses and microstructure effects on the fatigue behaviour of a L-PBF AlSi10Mg alloy N2 - Al-Si alloys produced by Laser Powder Bed Fusion (L-PBF) techniques allow the fabrication of lightweight free-shape components that find space in aerospace, automotive, biomedical and military applications. Due to the high cooling rates occurring during the building process, L-PBF AlSi10Mg alloys exhibit an ultra-fine microstructure that leads to superior mechanical properties in the as-built condition compared to conventional cast Al-Si materials. Nevertheless, L-PBF processing induces high thermal gradients, leading to deleterious residual stress levels that must be considered to avoid part distortion and unpredicted failures. In order to relax detrimental residual stress and to increase the ductility, post-processing stress relief treatments are generally performed. In as-built condition the hypoeutectic AlSi10Mg microstructure consist of fine α-Al cells containing uniformly dispersed silicon nanoparticles, which are, in addition, surrounded by a eutectic Si network. Above 260°C the silicon interconnectivity starts to breakdown into spheroidized particles and to coarsen. At the same time, the heating residual stresses are relieved. The objective of the contribution is to investigate, under different heat treatment conditions, the evolution of microstructure and residual stresses in view of optimizing the fatigue performance of the alloy. To this purpose various heat treatments in a range of temperatures between 265°C and 300°C for a duration between 15 minutes and 2 hours are performed. The microstructure modifications are analysed using a scanning electron microscope and the residual stress state is measured by laboratory X-ray diffraction. T2 - FATIGUE DESIGN 2021 CY - Online meeting DA - 17.11.2021 KW - AlSi10Mg alloy KW - Additive manufacturing KW - L-PBF KW - Residual stress KW - Heat treatment PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-544942 DO - https://doi.org/10.1016/j.prostr.2022.03.057 SN - 2452-3216 VL - 38 SP - 564 EP - 571 PB - Elsevier B.V. AN - OPUS4-54494 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Roveda, Ilaria A1 - Serrano-Munoz, Itziar A1 - Haubrich, J. A1 - Requena, G. A1 - Madia, Mauro T1 - Influence of post-process heat treatments on the fatigue crack propagation behaviour of a PBF-LB/M AlSi10Mg alloy N2 - The microstructure has a great influence on short fatigue crack growth in metallic materials. Laser-based Powder Bed Fusion AlSi10Mg alloys exhibit in the as-built condition a fine fibrous Si structure and a supersaturated solid solution of Si in the α-Al matrix, which is significantly modified by heat treatments starting already at temperatures under 260 °C. This study focuses on the influence of post-process heat treatments on the microstructural evolution and the resulting fatigue crack growth resistance. As compared to the as-built condition, two heat treatments at 265 °C/1 h and at 300 °C/2 h are found to be beneficial to the fatigue crack growth resistance of the investigated material. KW - Additive manufacturing KW - Fatigue crack growth KW - Cyclic R-curve KW - Heat treatment PY - 2023 DO - https://doi.org/10.1016/j.ijfatigue.2023.107808 SN - 0142-1123 VL - 175 SP - 1 EP - 12 PB - Elsevier Ltd. AN - OPUS4-57822 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mishurova, Tatiana A1 - Serrano-Munoz, Itziar T1 - Multiscale residual stress analysis and synchrotron X-ray refraction of additively manufactured parts N2 - The overview of the activity of group 8.5 Micro-NDT (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The challenges in the residual stress analysis of AM components are discussed on the basis on the show studies performed in BAM. Also, the synchrotron X-ray refraction technique, available in BAM, is presented, showing example of in-situ heating test of Al10SiMg AM material. T2 - Seminar at Grenoble INP, Science et Ingénierie des Matériaux et Procédés (SIMaP) CY - Grenoble, France DA - 01.07.2022 KW - Additive manufacturing KW - Residual stress KW - X-ray refraction KW - Computed tomography PY - 2022 AN - OPUS4-55232 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Serrano-Munoz, Itziar T1 - Influence of microstructure and residual stress state on the fatigue behaviour of a PBF-LB/M AlSi10Mg alloy N2 - The high cooling rates (~106 K/s) occurring during Laser Powder Bed Fusion (PBF-LB/M) of AlSi10Mg induce to the formation of a fine nanometric silicon network in the as-built condition. Such unprecedented microstructure enhances the mechanical strength when compared to equivalent as-cast materials. Nevertheless, PBF-LB/M also leads to high magnitude residual stress (RS) due to the extreme localized temperature gradients. The presence of RS can be detrimental to the fatigue life of engineering components, and great efforts are focused on understanding their generation and evolution after post-process heat treatments. Typically, T6 heat treatments are used to mitigate RS and improve mechanical performances by Mg2Si precipitation during ageing at 160-180°C. Nevertheless, the solutionizing at 500-540°C vanishes the fine silicon network, leading to the formation of micrometric (average of ~2-5 µm) polygonal Si particles, similar to those observed in T6 heat-treated Al-Si cast materials. Therefore, the aim of this work is to evaluate the ability of two so-called low temperature heat treatments (i.e., at 265°C and 300°C) to mitigate RS while retaining the fine as-built microstructure inherent to PBF-LB/M AlSi10Mg. The fatigue behavior of the as-built material is subsequently compared to the two low temperature conditions. T2 - LightMat 2023 CY - Trondheim, Norway DA - 21.06.2023 KW - AlSi10Mg KW - Fatigue crack propagation KW - Residual stress KW - Post processing heat treatment PY - 2023 AN - OPUS4-57807 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Roveda, Ilaria T1 - Effect of heat treatment on the microstructure, residual stress state and fatigue properties of PBF-LB/M AlSi10Mg N2 - Al-Si alloys produced by Laser Powder Bed Fusion (PBF-LB/M) techniques allow the fabrication of lightweight free-shape components. Due to the extremely heterogeneous cooling and heating, PBF-LB/M induces high magnitude residual stress (RS) and a fine Si microstructure. As the RS can be deleterious to the fatigue resistance of engineering components, great efforts are focused on understanding their evolution before and after post-process heat treatments (HT). T2 - Alloys for Additive Manufacturing Symposium 2022 (AAMS22) CY - Munich, Germany DA - 12.09.2022 KW - Neutron diffraction KW - X-ray diffraction KW - Crack propagation PY - 2022 AN - OPUS4-55871 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Serrano-Munoz, Itziar T1 - 3D imaging and residual stress analysis for AM Materials N2 - Metal Additive Manufacturing (AM) technologies such as Laser Powder Bed Fusion (LPBF) are characterized by layer wise construction, which enable advancements of component design, leading to potential efficiency and performance improvements. However, the rapid cooling rates associated with the process consequently leads to the generation of high magnitude residual stresses (RS). Therefore, a deep understanding of the formation of RS, the influence of process parameters on their magnitude and the impact on mechanical performance is crucial for widespread application. The experimental characterization of these RS is essential for safety related engineering application and supporting the development of reliable numerical models. Diffraction-based methods for RS analysis using high energy synchrotron X-rays and neutrons enable non-destructive spatially resolved characterization of both surface and bulk residual stresses in complex components. This presentation will provide an overview of recent research conducted by the BAM at large scale facilities for the characterization of residual stresses in LPBF metallic alloys. Special focus will be given to the challenges posed by textured LPBF materials for the reliable choice of the diffraction elastic constants (DECs), which is crucial to the accurate calculation of the level of RS. T2 - Seminar at LTDS, Ecole Centrale de Lyon CY - Lyon, France DA - 15.06.2023 KW - Residual stress KW - Additive manufacturing KW - Diffraction methods PY - 2023 AN - OPUS4-57808 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Madia, Mauro T1 - Prediction of the fatigue limit of additively manufactured metallic materials N2 - Structural alloys are largely employed in key industrial sectors and their demand is predicted to rise rapidly for the next decades. Most of these materials require a large amount of energy for extraction and manufacturing, which causes the emission of greenhouse gases and other pollutants. Therefore, strategies for improving the sustainability of structural metallic alloys are urgently needed. Additive Manufacturing (AM), in particular Laser Powder Bed Fusion (PBF-LB/M), aims to be a sustainable manufacturing process, as it allows the build-up of complex geometry in near net-shape from 3D models, while minimizing material waste and the energy required for the process and post-process treatments. Nevertheless, the application of additively manufactured parts in structural safety-relevant applications is still hindered by the poor fatigue performance. The cause of this has been mainly attributed to the presence of manufacturing defects and surface roughness. Therefore, a huge effort has been made to optimize the process parameters and to introduce post-process treatments to minimize the defect content. However, material flaws cannot be fully eliminated, but these can be considered in a damage tolerance framework for the prediction of the fatigue performance of additively manufactured metallic materials, which is essential for part design and qualification. This work aims at presenting different modelling strategies for the prediction of the fatigue limit of AM metals. Simple empirical models and more complex models based on fatigue short crack propagation are proposed. The investigated material is an AlSi10Mg alloy fabricated by PBF-LB/M and subjected to two different low-temperature heat-treatments (265°C for 1 h and 300°C for 2h). The results show that the models can provide good approximation of the fatigue limits and help in the interpretation of the scatter of fatigue data. T2 - ASTM International Conference on Advanced Manufacturing CY - Washington DC, USA DA - 30.10.2023 KW - Additive Manufacturing KW - AlSi10Mg KW - Fatigue KW - Residual stress KW - Microstructure PY - 2023 AN - OPUS4-58866 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Roveda, Ilaria T1 - Investigation of residual stresses and microstructure effects on the fatigue behaviour of a L-PBF AlSi10Mg alloy N2 - Al-Si alloys produced by Laser Powder Bed Fusion (L-PBF) techniques allow the fabrication of lightweight free-shape components. Due to the high cooling rates occurring during the building process, L-PBF AlSi10Mg alloys exhibit an ultra-fine microstructure that leads to superior mechanical properties in the as-built condition compared to conventional cast Al-Si materials. Nevertheless, L-PBF processing induces high thermal gradients, leading to deleterious residual stress. In order to relax detrimental residual stress and to increase the ductility, post-processing stress relief treatments are performed. The objective of the contribution is to investigate, under different heat treatment condition, the evolution of microstructure and residual stresses in view of optimizing the fatigue performance of the alloy. To this purpose various heat treatments in a range of temperatures between 265°C and 300°C for a duration between 15 minutes and 2 hours are performed. T2 - Fatigue Design 2021 CY - Senlis, France DA - 17.11.2021 KW - AlSi10Mg KW - Additive manufacturing KW - L-PBF KW - Residual stress KW - Heat treatment PY - 2021 AN - OPUS4-53794 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Santi, Alberto A1 - Schröder, Jakob A1 - Serrano-Munoz, Itziar A1 - Bayat, Mohamad A1 - Hattel, Jesper Henri T1 - Exploring the Flash Heating method in additive manufacturing for residual stress prediction: A comparative study with diffraction results from X-ray and neutron techniques N2 - Residual stress (RS) control is crucial for ensuring the performance and reliability of components produced through laser-based powder bed fusion (PBF-LB) additive manufacturing (AM). This study evaluates the Flash Heating (FH) method as an efficient approach for RS prediction, comparing its outcomes with multiple experimental techniques, including X-ray diffraction, neutron diffraction, and layer removal methods. These experimental assessments are conducted in different regions of the component, both before and after detachment from the baseplate. The study validates the FH method and analyzes key numerical parameters, such as meta-layer height, contact time, and time-stepping strategies. Results indicate that FH effectively predicts bulk RS distributions but shows discrepancies in surface stress estimations, likely due to unaccounted factors like surface roughness. Additionally, implementing experimentally derived material properties from as-built AM samples significantly enhances model accuracy compared to conventional material datasets. These findings underscore the potential of FH for efficient RS prediction in PBF-LB while identifying areas for further improvement. Refinements should focus on incorporating anisotropic, temperature-dependent material behavior derived from as-built AM samples and surface roughness effects. This work advances the understanding of key factors necessary for accurate and computationally efficient RS prediction, supporting the optimization of AM processes. KW - Finete element method KW - Inconel 718 KW - Metal additive manufacturing KW - Residual stress KW - Thermomechanics PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-639533 DO - https://doi.org/10.1080/01495739.2025.2541862 SN - 0149-5739 SP - 1 EP - 24 PB - Taylor & Francis AN - OPUS4-63953 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Madia, Mauro T1 - Damage Tolerant Approach in Additively Manufactured Metallic Materials N2 - Damage tolerance counts as one of the most widespread approach to fatigue assessment and surely as one of the most promising in understanding the process-structure-property-performance relationships in additively manufactured metallic materials. Manufacturing defects, surface roughness, microstructural features, short and long crack fatigue propagation, residual stresses and applied loads can be taken into consideration in a fracture mechanics-based fatigue assessment. Many aspects are crucial to the reliable component life prediction. Among those a prominent role is played by an accurate measurement and modelling of the short crack fatigue behavior, and reliable statistical characterization of defects and residual stresses. This work aims at addressing the issues related to both experimental testing, fatigue and fatigue crack propagation, and fracture mechanics-based modelling of fatigue lives. Examples will be provided on an additively manufactured AISI 316 L. T2 - TMS2021 VIRTUAL CY - Online meeting DA - 15.03.2021 KW - AISI 316L KW - Additive Manufacturing KW - Damage Tolerance KW - Microstructure KW - Defects KW - Residual Stress PY - 2021 AN - OPUS4-52293 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Przyklenk, A. A1 - Balsamo, A. A1 - O'Connor, D. A1 - Evans, Alexander A1 - Yandayan, T. A1 - Akgöz, S. A1 - Flys, O. A1 - Zeleny, V. A1 - Czułek, D. A1 - Meli, F. A1 - Ragusa, C. A1 - Bosse, H. T1 - New European Metrology Network for advanced manufacturing N2 - Advanced manufacturing has been identified as one of the key enabling technologies with applications in multiple industries. The growing importance of advanced manufacturing is reflected by an increased number of publications on this topic in recent years. Advanced manufacturing requires new and enhanced metrology methods to assure the quality of manufacturing processes and the resulting products. However, a high-level coordination of the metrology community is currently absent in this field and consequently this limits the impact of metrology developments on advanced manufacturing. In this article we introduce the new European Metrology Network (EMN) for Advanced Manufacturing within EURAMET, the European Association of National Metrology Institutes (NMIs). The EMN is intended to be operated sustainably by NMIs and Designated Institutes in close cooperation with Stakeholders interested in advanced manufacturing. The objectives of the EMN are to set up a permanent stakeholder dialogue, to develop a Strategic Research Agenda for the metrology input required for advanced manufacturing technologies, to create and maintain a knowledge sharing programme and to implement a web-based service desk for stakeholders. The EMN development is supported by a Joint Network Project within the European Metrology Programme for Innovation and Research. KW - Stakeholder KW - Advanced manufacturing KW - Metrology KW - European Metrology Networks (EMNs) KW - Strategic Research Agenda (SRA), PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-530618 DO - https://doi.org/10.1088/1361-6501/ac0d25 VL - 32 IS - 11 SP - 111001 PB - IOP Publishing AN - OPUS4-53061 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - D'Accardi, E. T1 - Capability of active thermography to detect and localize pores in Metal Additive Manufacturing materials N2 - A powerful tool to understand, demonstrate and explain the limits of the pulsed technique in terms of detectability and localizability of AM keyhole pores has been assessed by comparing the active thermographic approach (both experimental and FEM simulations) to Computed Tomography results; ✓ µCT results demonstrate that the intended defect geometry is not achieved; indeed a network of voids (microdefects consisting of small sharp-edged hollows with a complicated, almost fractal, inner surface) was found; ✓ both Exp-PT and FEM results explains clearly why no indication of defect related to the thermal contrasts could be found during the investigation of an uncoated surface. However, the application of further data evaluations focusing on the thermal behavior and emissivity evaluation (PPT post data processing) enable the detection of some defects; ✓ coating facilitates a closer inspection of inner defects, but inhomogeneities of the coating could impair the spatial resolution and lead to the emergence of hotspots (the FEM simulation reached its limit with this extreme geometry where a 25 µm thin disc is considered at a 1 cm thick specimen in millisecond time resolution); ✓ both Exp-PT and FEM results allow the conclusion that very short pulses of 200 ms or shorter should be sufficient to detect these defects below, but near the surface; besides a short duration of the thermal phenomenon it should be emphasized, about 0.04 s (high frame rate camera); T2 - Convegno AIAS 2020 CY - Online meeting DA - 02.09.2020 KW - Additive Manufacturing KW - Laser powderbed fusion KW - Pores KW - Thermography PY - 2020 AN - OPUS4-51922 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Tang, Lei A1 - Magdysyuk, Oxana V. A1 - Jiang, Fuqing A1 - Wang, Yiqiang A1 - Evans, Alexander A1 - Kabra, Saurabh A1 - Cai, Biao T1 - Mechanical performance and deformation mechanisms at cryogenic temperatures of 316L stainless steel processed by laser powder bed fusion: In situ neutron diffraction N2 - Manufacturing austenitic stainless steels (ASSs) using additive manufacturing is of great interest for cryogenic applications. Here, the mechanical and microstructural responses of a 316L ASS built by laser powder bed fusion were revealed by performing in situ neutron diffraction tensile tests at the low-temperature range (from 373 to 10 K). The stacking fault energy almost linearly decreased from 29.2 ± 3.1 mJm⁻² at 373 K to 7.5 ± 1.7 mJm⁻² at 10 K, with a slope of 0.06 mJm⁻²K⁻¹, leading to the transition of the dominant deformation mechanism from strain-induced twinning to martensite formation. As a result, excellent combinations of strength and ductility were achieved at the low-temperature range. KW - Condensed Matter Physics KW - General Materials Science KW - Mechanics of Materials KW - Metals and Alloys KW - Mechanical Engineering PY - 2022 DO - https://doi.org/10.1016/j.scriptamat.2022.114806 SN - 1359-6462 VL - 218 SP - 1 EP - 7 PB - Elsevier BV CY - Amsterdam AN - OPUS4-59317 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Favres, Georges T1 - European Metrology Network (EMN) for Advanced Manufacturing N2 - The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). By fully utilizing these KETs, advanced and sustainable economies will be created. It is considered that Metrology is a key enabler for the advancement of these KETs. EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network for Advanced Manufacturing. The EMN is made up of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The EMN aims to provide a high-level coordination of European metrology activities for the Advanced Materials and Advanced Manufacturing community. The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing and Advanced Materials (Large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider metrology community (including TCs) to provide input for the preparation of a Strategic Research Agenda (SRA) for Metrology for Advanced Manufacturing. This presentation will describe the progress in the development of the SRA by the EMN for Advanced Manufacturing. The metrology challenges identified across the various key industrial sectors, which utilise Advanced Materials and Advanced Manufacturing will be presented. The EMN for Advanced Manufacturing is supported by the project JNP 19NET01 AdvManuNet. T2 - 21st International Metrology Congress, CIM 2023 CY - Lyon (Chassieu), France DA - 07.03.2023 KW - Advanced Materials KW - EMN KW - European Metrology Network for Advanced Manufacturing, Strategic Research Agenda KW - SRA PY - 2023 AN - OPUS4-59208 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - O'Connor, Daniel A1 - Evans, Alexander A1 - Balsamo, Alessandro A1 - Favres, Georges A1 - Przyklenk, Anita A1 - Bosse, Harald A1 - Phillips, Dishi T1 - European Metrology Network (EMN) for Advanced Manufacturing ─ Development of the Strategic Research Agenda (SRA) N2 - The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community. The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing. This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing T2 - Euspen, 23rd International Conference & Exhibitio CY - Copenhagen, Danmark DA - 12.06.2023 KW - European Metrology Network (EMN) KW - Advanced Manufacturing KW - Metrology KW - Strategic Research Agenda (SRA) PY - 2023 SP - 363 EP - 364 AN - OPUS4-59196 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon A1 - Gerlach, G. T1 - Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in laser powder bed fusion N2 - Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled. Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring. Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R² score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³. It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally. T2 - XXXVII. Messtechnisches Symposium 2023 CY - Freiburg, Germany DA - 27.09.2023 KW - Porosity prediction KW - Defect detection KW - Laser powder bed fusion (PBF-LB/M, L-PBF) KW - Selective laser melting KW - Thermography KW - Machine learning PY - 2023 DO - https://doi.org/10.1515/teme-2023-0062 SN - 0171-8096 SN - 2196-7113 VL - 90 SP - 85 EP - 96 PB - De Gruyter CY - Berlin AN - OPUS4-58366 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon T1 - Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in PBF-LB/M N2 - Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled. Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring. Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R2 score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³. It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally. T2 - XXXVII. Messtechnisches Symposium 2023 CY - Freiburg im Breisgau, Germany DA - 27.09.2023 KW - Porosity prediction KW - Defect detection KW - Laser Powder Bed Fusion (PBF-LB/M, L-PBF) KW - Selective Laser Melting KW - Thermography KW - Machine Learning PY - 2023 AN - OPUS4-59192 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 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 - 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 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 - TY - CONF A1 - Oster, Simon A1 - Maierhofer, Christiane A1 - Mohr, Gunther A1 - Hilgenberg, Kai A1 - Ulbricht, Alexander A1 - Altenburg, Simon T1 - Investigation of the thermal history of L-PBF metal parts by feature extraction from in-situ SWIR thermography N2 - Laser powder bed fusion is used to create near net shape metal parts with a high degree of freedom in geometry design. When it comes to the production of safety critical components, a strict quality assurance is mandatory. An alternative to cost-intensive non-destructive testing of the produced parts is the utilization of in-situ process monitoring techniques. The formation of defects is linked to deviations of the local thermal history of the part from standard conditions. Therefore, one of the most promising monitoring techniques in additive manufacturing is thermography. In this study, features extracted from thermographic data are utilized to investigate the thermal history of cylindrical metal parts. The influence of process parameters, part geometry and scan strategy on the local heat distribution and on the resulting part porosity are presented. The suitability of the extracted features for in-situ process monitoring is discussed. T2 - Thermosense: Thermal Infrared Applications XLIII CY - Online meeting DA - 12.04.2021 KW - SWIR camera KW - Additive manufacturing (AM) KW - Selective laser melting (SLM) KW - Laser beam melting (LBM) KW - In-situ monitoring KW - Infrared thermography PY - 2021 SN - 978-1-5106-4324-6 DO - https://doi.org/10.1117/12.2587913 VL - 11743 SP - 1 EP - 11 PB - SPIE - The international society for optics and photonics AN - OPUS4-52535 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Portella, Pedro Dolabella A1 - Ulbricht, Alexander A1 - Evans, Alexander A1 - Altenburg, Simon A1 - Ehlers, Henrik A1 - Hilgenberg, Kai A1 - Mohr, Gunther T1 - Monitoring additive manufacturing processes by using NDT methods N2 - In this presentation we discuss the online monitoring of metallic AM parts produced by the Laser Powder Bed Fusion (LPBF) process by using optical, thermographic and electromagnetic methods. In a first approach we present the detection of defects generated during the process and discuss how to improve these methods for the optimization of design and production of metallic AM parts. T2 - ABENDI - Workshop CY - Online meeting DA - 19.11.2020 KW - Additive Fertigung PY - 2020 AN - OPUS4-52042 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon T1 - Defect prediction on the Base of Thermographic features in Laser Powder Bed Fusion Utilizing Machine Learning Algorithms N2 - Avoiding the formation of defects such as keyhole pores is a major challenge for the production of metal parts by Laser Powder Bed Fusion (LPBF). The use of in-situ monitoring by thermographic cameras is a promising approach to detect defects, however the data is hard to analyze by conventional algorithms. Therefore, we investigate the use of Machine Learning (ML) in this study, as it is a suitable tool to model complex processes with many influencing factors. A ML model for defect prediction is created based on features extracted from process thermograms. The porosity information calculated from an x-ray Micro Computed Tomography (µCT) scan is used as reference. Physical characteristics of the keyhole pore formation are incorporated into the model to increase the prediction accuracy. Based on the prediction result, the quality of the input data is inferred and future demands on in-situ monitoring of LPBF processes are derived. T2 - Additive Manufacturing Benchmarks 2022 CY - Bethesda, MA, USA DA - 14.08.2022 KW - Laser Powder Bed Fusion KW - Thermography KW - In-situ Monitoring KW - Machine Learning KW - Defect prediction PY - 2022 AN - OPUS4-55591 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon T1 - Investigation of the thermal history of L-PBF metal parts by feature extraction from in-situ SWIR thermography N2 - Laser powder bed fusion is used to create near net shape metal parts with a high degree of freedom in geometry design. When it comes to the production of safety critical components, a strict quality assurance is mandatory. An alternative to cost-intensive non-destructive testing of the produced parts is the utilization of in-situ process monitoring techniques. The formation of defects is linked to deviations of the local thermal history of the part from standard conditions. Therefore, one of the most promising monitoring techniques in additive manufacturing is thermography. In this study, features extracted from thermographic data are utilized to investigate the thermal history of cylindrical metal parts. The influence of process parameters, part geometry and scan strategy on the local heat distribution and on the resulting part porosity are presented. The suitability of the extracted features for in-situ process monitoring is discussed. T2 - Thermosense: Thermal Infrared Applications XLIII CY - Online meeting DA - 12.04.2021 KW - SWIR camera KW - Additive manufacturing (AM) KW - Selective laser melting (SLM) KW - Laser beam melting (LBM) KW - In-situ monitoring KW - Infrared thermography PY - 2021 UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11743/117430C/Investigation-of-the-thermal-history-of-L-PBF-metal-parts/10.1117/12.2587913.short?SSO=1&tab=ArticleLink AN - OPUS4-52540 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Oster, Simon T1 - Defect prediction in laser powder bed fusion based on thermographic features utilizing convolutional neural networks N2 - The appearance of irregularities such as keyhole porosity is a major challenge for the production of metal parts by laser powder bed fusion (PBF-LB/M). The utilization of thermographic in-situ monitoring is a promising approach to extract the thermal history which is closely related to the formation of irregularities. In this study, we investigate the utilization of convolutional neural networks to predict keyhole porosity based on thermographic features. Here, the porosity information calculated from an x-ray micro computed tomography scan is used as reference. Feature engineering is performed to enable the model to learn the complex physical characteristics of the porosity formation. The model is examined with regard to the choice of hyperparameters, the significance of thermal features and characteristics of the data acquisition. Based on the results, future demands on irregularity prediction in PBF-LB/M are derived. T2 - GIMC SIMAI YOUNG 2022 CY - Pavia, Italy DA - 29.09.2022 KW - Laser Powder Bed Fusion KW - Thermography KW - In-situ Monitoring KW - Convolutional Neural Networks PY - 2022 AN - OPUS4-56331 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Evans, Alexander T1 - The European Metrology Network (EMN) for Advanced Manufacturing N2 - Advanced Manufacturing and Advanced Materials have been identified by the European Commission as one of six Key Enabling Technologies (KETs), the full exploitation of which will create advanced and sustainable economies. Metrology is a key enabler for progress of these KETs. EURAMET, which is the association of metrology institutes in Europe, has addressed the vital importance of Metrology for these KETs through the support for the creation of a European Metrology Network for Advanced Manufacturing. The EMN for Advanced Manufacturing (AdvanceManu) was approved in June 2021 and held the formal kick-of meeting in October 2022. The EMN comprises both National Metrology Institutes (NMIs) from across Europe and other designated Institutes (Dis). The EMN is organized in three sections; Advanced Materials, Smart Manufacturing Systems and Manufactured components and products. The aim of the EMN is to engage with stakeholders in the field of Advanced Manufacturing and Advanced Materials (Large & SMEs, industry organisations, existing networks and academia) with the aim to prepare a Strategic Research Agenda (SRA) for Metrology for Advanced Manufacturing. In the shorter term, an orientation paper is aimed to be produce to in the context of the European Partnership for Metrology. In addition to the SRA, the EMN will establish knowledge and technology transfer and promotion plan. This includes leveraging the existing research results from the completed and running EMPIR JRP projects funded through EURAMET. This presentation will outline the EMN for Advanced Manufacturing, describing the structures and goals, the route to the production of the SRA and the progress made to date identifying the key metrology challenges across the related Key Industrial Sectors (KICs). In particular, the presentation aims to inform the community on how to be involved in the shaping of the strategic research agenda for the future of Metrology for Advanced Manufacturing and Advanced Materials. T2 - 3D Metrology Conference (3DMC) CY - Online meeting DA - 08.11.2021 KW - Advanced manufacturing KW - Metrology KW - European Metrology Network (EMN) KW - Strategic Research Agenda (SRA) KW - JNP PY - 2021 AN - OPUS4-54099 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Przyklenk, A. T1 - Progress of the European Metrology Network for Advanced Manufacturing N2 - The European Metrology Network (EMN) for Advanced Manufacturing has been established in June 2021. Currently nine EMNs focussing on different important topics of strategic importance for Europe exist and form an integral part of EURAMET, the European Association of National Metrology Institutes (NMI). EMNs are tasked to ▪ develop a high-level coordination of the metrology community in Europe in a close dialogue with the respective stakeholders (SH) ▪ develop a strategic research agenda (SRA) within their thematic areas ▪ provide contributions to the European Partnership on Metrology research programme Based on the analysis of existing metrology infrastructures and capabilities of NMIs, the metrology research needs for advanced manufacturing are identified in close cooperation with academic, governmental and industrial stakeholders. Here, we report on the progress of the EMN for Advanced Manufacturing. T2 - Euspen 22nd International Conference & Exhibition (Euspen 2022) CY - Genf, Switzerland DA - 30.05.2022 KW - JNP AdvManuNet KW - Metrology KW - Advanced manufacturing KW - European Metrology Network KW - EMN PY - 2022 AN - OPUS4-55805 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Waske, Anja T1 - A unique Authenticator for additively manufactured parts N2 - Components produced using additive manufacturing can be marked for unique identification and secure authentication [1,2]. Serial numbers and machine-readable codes can be used to identify the component, and link digital product-related data (i.e., a digital product passport) to the actual components. The most prevailing solution consists of local process manipulation, such as printing a quick response (QR) code [3] or a set of blind holes on the surface of the internal cavity of hollow components. However, local manipulation of components may alter the properties, and external tagging features can be altered or even removed by post-processing treatments. This work therefore aims to provide a new methodology for identification, authentication, and traceability of additively manufactured (AM) components using microstructural features that are unique to each part. X-ray computed tomography (XCT) was employed to image the microstructural features of AlSi10Mg parts. Based on size and geometry, the most prominent features were selected to create a unique digital authenticator. We implemented a framework in Python using open-access modules that can successfully create a digital object authenticator using the segmented microstructure information from XCT. The authenticator is stored as a QR code, along with the 3D information of the selected features. T2 - DGM Additive Berlin 2024 CY - Berlin, Germany DA - 12.06.2024 KW - Additive Fertigung KW - Authentifizierung KW - Mikrostruktur PY - 2024 AN - OPUS4-60957 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meinel, Dietmar T1 - Classic Materials Testing in the Light of CT N2 - Currently, mandatory requirements and recommendations for the detection of irregularities in laser beam welded joints are based on classic micrographs as set out in the standard ISO 13919-1:2019. Compared to classic micrographs, computed tomography enables a non-destructive, three-dimensional and material-independent mode of operation, which delivers much more profound results. Even in building material testing, methods with limited informative value can be checked and supplemented by CT examinations. T2 - 13th International Conference on Industrial Computed Tomography (iCT2024) CY - Wels, Austria DA - 06.02.2024 KW - Computed Tomography KW - Additive Manufacturing KW - Machine-Learning Segmentation KW - Air Void System PY - 2024 AN - OPUS4-59568 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Gupta, Kanhaiya A1 - Poka, Konstantin A1 - Ulbricht, Alexander A1 - Waske, Anja T1 - Identification and authentication of additively manufactured components using their microstructural fingerprint N2 - In the field of additive manufacturing, the ability to uniquely identify and authenticate parts is crucial for certification, logistics, and anti-counterfeiting efforts. This study introduces a novel methodology that leverages the intrinsic microstructural features of additively manufactured components for their identification, authentication, and traceability. Unlike traditional tagging methods, such as embedding QR codes on the surface or within the volume of parts, this approach requires no alteration to the printing process, as it utilizes naturally occurring microstructural characteristics. The proposed workflow involves the analysis of 3D micro-computed tomography data to identify specific voids that meet predefined identification criteria. This method is demonstrated on a batch of 24 parts manufactured with identical process parameters, proving capable of achieving unambiguous identification and authentication. By establishing a tamper-proof link between the physical part and its digital counterpart, this methodology effectively bridges the physical and digital realms. This not only enhances the traceability of additively manufactured parts but also provides a robust tool for integrating digital materials, parts databases, and product passports with their physical counterparts. KW - Authentication KW - Additive manufacturing KW - X-ray Computed Tomography KW - Digital fingerprint KW - Unique identification PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-630356 DO - https://doi.org/10.1016/j.matdes.2025.113986 SN - 1873-4197 VL - 254 SP - 1 EP - 12 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-63035 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ulbricht, Alexander T1 - Tales from Within: Residual Stress and Void Formation in LPBF 316L N2 - An unusual microstructure, inherent residual stresses and void formation are the three key aspects to control when assessing metallic parts made by LPBF. This talk explains an experiment to unravel the interlinked influence of the two mechanisms for the formation of residual stresses in LPBF: the temperature gradient mechanism and constricted solidification shrinkage. The impact of each mechanism on the shape and magnitudes of the residual stress distribution is described. Combined results from neutron diffraction, X-ray diffraction, computed tomography and in-situ thermography are presented. Also, influence of scan strategies as well as surface roughness of subjacent layers on void formation is shown. Results from computed tomography and in-situ thermography of a specimen dedicated to study the interaction of the melt pool with layers of powder underneath the currently illuminated surface are presented. T2 - 2nd Workshop on In-situ Monitoring and Microstructure Development in Additive Manufacturing CY - Online meeting DA - 19.04.2021 KW - Neutron diffraction KW - Laser powder bed fusion KW - In-situ thermography KW - Computed tomography KW - X-ray diffraction KW - Residual stress KW - Pore formation KW - AISI 316L PY - 2021 AN - OPUS4-52819 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Serrano-Munoz, Itziar A1 - Agudo Jácome, Leonardo A1 - Thompsom, Sean A1 - Schneider, Judy T1 - On the transferability of post-processing heat treatments designed for PBF-LB IN718 alloys to directed energy deposition specimens N2 - Many processes are being developed for metal additive manufacturing (AM) which vary by their heat source and feedstock. The use of directed energy deposition (DED) is growing due to its ability to build larger structures outside of a contained powder bed chamber. However, the only standard exclusively for post-build heat treatment of AM IN718 is ASTM standard F3055-14a, developed for powder bed fusion (PBF). This study evaluates the applicability of this current heat treatment standard to AM IN718 specimens produced using two methods of DED: laser-blown powder (LP)-DED and arc-wire (AW)-DED. Electron microscopy and X-ray diffraction techniques were used to characterize the specimens in the as-built condition and after the full heat treatment (FHT) specified in F3055. No evidence of remaining Laves phase was observed in the two DED specimens after the FHT. Yield strengths for the DED specimens were 1049 MPa for FHT AW-DED and 1096 MPa for LP-DED, higher than the minimum stated for PBF-LB IN718 of 920 MPa. The size, morphology, inter-spacing, and diffraction patterns of the γ´ and γ´´ strengthening precipitates are found to be similar for both DED processes. Differences were observed in the microstructure evolution where the F3055 heat treatments resulted in partial recrystallization of the grain structure, with a higher content of annealing twins observed in the AW-DED. These microstructural differences correlate with differences in the resulting elongation to failure. Thus, it is proposed that variations in heat treatments are needed for optimizing IN718 produced by different AM processes. KW - Additive manufacturing variants KW - Directed energy deposition (DED) KW - Post-process heat treatments KW - SEM-EBSD and TEM microscopy KW - XRD phase analysis PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-628165 DO - https://doi.org/10.1007/s00170-025-15386-1 SN - 1433-3015 VL - 137 IS - 7-8 SP - 3949 EP - 3965 PB - Springer Science and Business Media LLC AN - OPUS4-62816 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altenburg, Simon T1 - Machine Learning and Thermography as Tools for Local Porosity Prediction in AM of Metals N2 - Quality assurance of metal additive manufacturing (PBF-LB/M) is still a challenge. Offering deep process insights, thermography is a well-suited monitoring technique. Here, we show how machine learning based on thermographic data enables a local part porosity prediction. T2 - Laser Applications Conference (LAC) CY - Prague, Czech Republic DA - 19.10.2025 KW - PBF-LB/M KW - In situ monitoring KW - Thermography KW - Additive Manufacturing KW - Process monitoring KW - Porosity prediction KW - Machine Learning KW - Feature extraction PY - 2025 AN - OPUS4-64669 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wang, Y. A1 - Ulbricht, Alexander A1 - Schmidt, F. A1 - Müller, Bernd R. A1 - Kupsch, Andreas A1 - Schwitalla, A.D. T1 - Micro-CT analysis and mechanical properties of low dimensional CFR-PEEK specimens additively manufactured by material extrusion N2 - Material extrusion of thermoplastic polymers enables the realization of complex specific designs with high performance composites. The present study aims at evaluating the mechanical properties of carbon fiberreinforced semi-crystalline thermoplastic polymer polyether ether ketone (CFR-PEEK) manufactured by material extrusion and correlating them with results obtained by micro-CT. Samples in the shape of small bars were provided by Kumovis (Munich, Germany). The determination of surface roughness and density was followed by three-point bending tests. To reveal the pore distribution as well as the fusion quality of CFR PEEK when applied with external forces, micro-CT scans were performed with an X-ray microscope before and after the mechanical test to localize the sites where the fracture is generated. The density of CFR-PEEK bars indicated that they had superior mechanical properties compared with our previous study on unfilled 3D printed PEEK (bending modulus: (5.4 ± 0.5) GPa vs. (1.05 ± 0.05) GPa to (1.48 ± 0.10) GPa; bending strength: (167 ± 11) MPa vs. (51 ± 15) to (193 ± 7) MPa). Micro-CT analyses revealed the local 3D-distribution of voids. Voids of 30 μm diameter are nearly spherical and make up the main part of the total porosity. The larger the voids, the more they deviate from a spherical shape. Significant lack-of-fusion voids are located between the deposited filaments. By growing and merging, they act as seeds for the forming fracture line in the region of the flexural specimens where the maximum local tensile stresses occurred under bending load. Our work provides a detailed analysis of printed PEEK with fiber additive and relates this with mechanical properties. KW - CFR-PEEK KW - Material extrusion (MEX) KW - FFF KW - Surface topography KW - Bending property KW - Micro-CT PY - 2023 DO - https://doi.org/10.1016/j.jmbbm.2023.106085 SN - 1751-6161 VL - 146 SP - 1 EP - 9 PB - Elsevier Ltd. AN - OPUS4-58112 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Poka, Konstantin A1 - Ali, Sozol A1 - Ulbricht, Alexander A1 - Schröder, Jakob A1 - Khambayat, Jiganesh A1 - Scholz, Maik A1 - Saeed, Waleed A1 - Merz, Benjamin A1 - Epperlein, Martin A1 - Hilgenberg, Kai T1 - Reduction of extraneous variance in powder bed fusion with laser beam of metals by means of advanced digital preprocessing N2 - Data-driven quality assurance and reproducibility are critical for advancing the industrial maturity of Powder Bed Fusion with Laser Beam of Metals (PBF-LB/M). This study addresses the extraneous variance in scan vectors that arises even for identical cross sections of nominally identical components but located at different positions on the build platform. This inherent variance, common across most PBF-LB/M machines, is caused by scan vector computation relative to the machine coordinate origin and subsequent projection of the resulting pattern onto individual component cross sections. In this work, scan vectors are computed still following conventional slicing, but relative to the workpiece origin of each component, using an EOS M 300-4. This digital preprocessing approach homogenizes fabrication conditions, ensuring that anomalies, such as scan vector overlaps, occur consistently across identical components. The impact during fabrication is assessed through powder bed imaging, melt pool monitoring, and operational data from the multilaser PBF-LB/M machine. Components are manufactured from AlSi10Mg for each scan vector computation origin and subsequently qualified using x-ray computed tomography, optical coordinate measurement, and optical surface measurement. A comprehensive evaluation is conducted, comparing the results in terms of component density, geometric accuracy, and surface roughness to those obtained using conventional preprocessing. Based on these findings, practical recommendations are provided, focusing on achieved quality criteria to identify potential drawbacks, while also considering the life cycle analysis of fabrication. Finally, the study emphasizes the significance of consistent scan vector provisioning for identical components placed at different build platform positions, assuming no roll or pitch during nesting. T2 - ICALEO CY - Orlando, FL, USA DA - 13.10.2025 KW - Quality assurance KW - Data management KW - 3D printing KW - Laser fabrication KW - Life cycle analysis PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-642104 DO - https://doi.org/10.2351/7.0001890 SN - 1042-346X VL - 37 IS - 4 SP - 1 EP - 14 PB - American Institute of Physics Publishing CY - New York AN - OPUS4-64210 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -