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Eingeladener Vortrag
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While additive manufacturing (AM) is blossoming in nearly every industrial field, and the most different process are being used to produce components and materials, little attention is paid on the safety concerns around AM materials and processes.
Leveraging on our leading expertise in non-destructive testing (NDT) and materials characterization, we approach AM at BAM under two important viewpoints: first the on-line monitoring of the process and of the product, second the evolution of the (unstable) microstructure of AM materials under external loads.
These two subjects are the core of the two new-born internal projects ProMoAM and AGIL, respectively.
A detailed view of the goals and the organization of these two projects will be given, together with the expected output, and some preliminary results.
Quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. I will show a few examples of possible use of X-ray tomographic data for quantitative assessment of damage evolution and microstructural properties, as well as for non-destructive testing, with particular focus on additively manufactured materials. I will also show how X-ray refraction computed tomography (CT) and Neutron diffraction can be highly complementary to classic absorption CT, being sensitive to internal interfaces and residual stress analysis, respectively.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a non-destructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. The results of the defect detection using infrared cameras are presented for a custom research PBF-LB/M machine. Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
Das pulverbettbasierte selektive Laserstrahlschmelzen (engl. laser powder bed fusion, L-PBF) ist die am weitesten verbreitete additive Fertigungstechnologie für die Herstellung metallischer Komponenten. Unter der Vielzahl an Einflussfaktoren auf die Qualität und die mechanischen Eigenschaften von L-PBF-Bauteilen hat die Zwischenlagenzeit (engl. inter layer time, ILT) bisher kaum Beachtung in der wissenschaftlichen Literatur gefunden, obwohl sie je nach Bauraumausnutzungsgrad stark variieren kann. In diesem Vortrag werden Ergebnisse einer Studie präsentiert, die den Einfluss der ILT in Kombination mit der Bauteilhöhe und unter Berücksichtigung verschiedener Volumenenergiedichten am Beispiel der austenitischen Stahllegierung AISI 316L untersucht. Die Fertigungsprozesse wurden in-situ mittels Thermographiekamera überwacht. Auf diese Weise konnten intrinsische Vorerwärmungstemperaturen während der Bauteilfertigung lagenweise extrahiert werden. Es wurden signifikante Effekte der ILT und der Bauteilhöhe auf Wärmeakkumulation, Mikrostruktur, Schmelzbadgeometrie und Härte festgestellt. Ferner konnte ein Anstieg von Defektdichten bei einem gegenseitigen Wechselspiel aus Bauteilhöhe und ILT aufgezeigt werden. Die Zwischenlagenzeit wurde somit als kritischer Faktor für die L-PBF-Fertigung von Realbauteilen identifiziert.
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 LPBF process is characterized by a large number of influencing factors which can be hard to quantify. Machine Learning (ML) is a prominent tool to predict the outcome of complex processes on the basis of different sensor data. In this study, a ML model for defect prediction is created using thermographic image features as input data. As a reference, the porosity information calculated from an x-ray Micro Computed Tomography (µCT) scan of the produced specimen is used. Physical knowledge about the keyhole pore formation is incorporated into the model to increase the prediction accuracy. From the prediction result, the quality of the input data is evaluated and future demands on in-situ monitoring of LPBF processes are formulated.
Additive manufacturing of metals gains increasing relevance in the industrial field for part production. However, especially for safety relevant applications, a suitable quality assurance is needed. A time and cost efficient route to achieve this goal is in-situ monitoring of the build process. Here, the BAM project ProMoAM (Process monitoring in additive manufacturing) is briefly introduced and recent advances of BAM in the field of in-situ monitoring of the L-PBF and the LMD process using thermography are presented.
Additive manufacturing is no longer just used for the production of prototypes but already found its way into the industrial production. However, the fabrication of massive metallic parts with high geometrical complexity is still too time-consuming to be economically viable. The combination of the powder bed-based selective laser melting process (SLM), known for its geometrical freedom and accuracy, and the nozzle-based laser metal deposition process (LMD), known for its high build-up rates, has great potential to reduce the process duration. For the industrial application of the SLM-LMD hybrid process chain it is necessary to investigate the interaction of the processes and its effect on the material properties to guarantee part quality and prevent component failure. Therefore, hybrid components are manufactured and examined before and after the heat treatment regarding the microstructure and the hardness in the SLM-LMD transition zone. The experiments are conducted using the nickel-based alloy Inconel 718.
Rapid localized heating and cooling during additive manufacturing using laser deposition method (LMD) lead to loss of dimensional accuracy as well as cracking of built parts. Finite-Element welding simulations allow prediction of geometrical deviations and accumulated residual stresses as well as their optimization before conducting experiments. Due to the great length of stacked welds, calculation times for fully transient thermomechanical simulations are currently long, the calculation stability suffers from the high number of contact bodies in the model and the modelling effort is high, as the geometries need to be sliced and positioned layer-wise.
In this contribution, an integrated modelling approach is demonstrated for a thin-walled LMD component made from 30 layers of 1.4404 (316L) stainless steel: Instead of the layer-by-layer modelling strategy commonly found in the literature, the whole component mesh is kept in one piece and the fully transient, layer-by-layer material deposition is implemented via element sets. In contrast to prior simulations, nonlinear contact between the layers does not have to be considered, significantly decreasing calculation times. The calculated distortions are compared to recently published, in-situ digital image correlation (DIC) measurements as well as numerical simulations conducted with the established layer-wise modelling strategy to judge result quality. Finally, the improvement in calculation time and ease-of-use is compared between both modelling approaches and conclusions regarding future usage for industrial-scale components are drawn.
Additive Manufacturing provides an important enabling technology for the digital transformation of the economy. As an emerging technology it has seen a remarkable development over the last three decades. Nevertheless, it is far from a broad adoption with several barriers to overcome yet. One of the major challenges is the lack of standards. The critical role of standardization for innovation is generally recognized, still the topic too often has been neglected in strategic roadmapping exercises for emerging technologies. Too little is known about the complex dynamics and interrelations of standardization and innovation. The anticipation of standardization needs and the timely and efficient implementation of standards is challenging. This paper aims at contributing to a better understanding of the role that standards play in the multi-dimensional system of innovation. It analyzes the trajectories of innovation in Additive Manufacturing in a systematic and holistic way, focusing on standardization activities with regard to coordination, stakeholders involved, the timing and types of standards developed. Putting standardization in context of the multi-dimensional innovation system of Additive Manufacturing the research shows where standards can support the diffusion of an emerging technology.
State-of-the-art laser powder bed fusion (PBF-LB/M) machines allow pre-heating of the substrate plate to reduce stress and improve part quality. However, two major issues have been shown in the past: First, with increasing build height the apparent pre-heat temperature at the surface can deviate drastically from the nominal pre-heat temperature in the substrate plate. Second, even within a single layer the local surface pre-heat temperature can show large gradients due to thermal bottlenecks in the part geometry underneath the top surface. Both lead to unwanted changes in microstructure or defects in the final parts. In this study, a first attempt is taken to show the feasibility of pre-heating the top surface with the onboard laser beam to overcome the mentioned issues. A single layer of a group of three parts built from IN718 to a height of 33.5 mm is pre-heated in a commercially available PBF-LB/M machine to an average steady state surface temperature of 200 °C using the onboard laser beam. The parts are continuously heated, omitting powder deposition and melting step. Temperatures are measured by thermocouples underneath the surface. The experiments are supported by a thermal finite element (FE) model that predicts the temperature field in the parts. When heating the parts uniformly with the laser beam, differences in surface temperatures as large as 170 K are observed. To overcome this inhomogeneity, the heat flux supplied by the laser beam is modulated. An optimized, spatial heat flow distribution is provided by the thermal FE model and translated into a scan pattern that reproduces the optimized heat distribution on the PBF-LB/M machine by locally modulating hatch distance and scan velocity. This successfully reduces the differences in surface temperature to 20 K. Thermographic imaging shows that a homogeneous surface temperature can be achieved despite the localized heat input by the beam. The potential for industrial application of the optimized laser-heating technique is discussed.
In additive manufacturing the powder bed based processes binder jetting and powder bed fusion are increasingly used also for the production of ceramics. Final part properties depend to a high percentage on the powder bed density. Therefore, the aim is to use the best combination of powder deposition method and powder which leads to a high packing of the particles. The influence of flowability, powder properties and deposition process on the powder bed density is discussed and the different deposition processes including slurry-based ones are reviewed.
It turns out that powder bed density reached by slurry-based layer deposition exceeds conventional powder deposition, however, layer drying and depowdering are extra steps or more time-consuming for the slurry route.
Depending on the material properties needed the most suitable process for the part has to be selected.