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Hybrid additive manufacturing is becoming increasingly important in the field of additive manufacturing. Hybrid approaches combine at least two different manufacturing processes. The focus of this work is the build-up of geometries onto conventionally manufactured parts using Powder Bed Fusion with Laser Beam of Metals (PBF-LB/M). The hybrid build-up requires a precise position detection system inside the PBF-LB/M machines to determine the exact position of the existing component. For this purpose, high-resolution camera systems can be utilized. However, the use of a camera system is associated with several challenges. The captured images are subject to various distortions of the optical path. Due to these distortions, it is not possible to use the images for measurements and, therefore, it is not possible to calculate the positions of objects. In this study a homography matrix is calculated to correct keystone distortion in the images. Different calibration patterns have been tested for the calculation of the homography matrix. The influence of the number of calibration points on the precision of position detection of objects is determined. Furthermore, the influence of an additional camera calibration by using ChArUco boards is evaluated. The result is a camera calibration workflow with associated calibration pattern for a precise position detection of parts inside PBF-LB/M machines allowing a hybrid build-up with minimum physical offset between base component and build-up.
Laser Powder Bed Fusion (PBF-LB/M) is a layer wise metal additive manufacturing (AM) technology, which enables significant advancements of component design, leading to potential efficiency and performance improvements. However, the thermal cycles inherent to the process comprising large localized thermal gradients and repeated melting and solidification cycles leads to the generation of high magnitude residual stresses. These residual stresses can be detrimental both during manufacturing of components and in subsequent application. Therefore, a deep understanding of the influence of process parameters on the residual stresses are crucial for efficient manufacturing and safe application. The experimental characterization of these residual stresses is therefore crucial and can provide a reliable baseline for simulations of both the process and applications.
Diffraction-based methods for residual stress analysis using penetrating neutrons and high energy X-rays enable non-destructive spatially resolved characterization of both surface and bulk residual stresses. However, the unique microstructural features inherent to the process can challenge some of our assumptions when using these methods. These challenges include the determination of a stress-free reference, the use of correct elastic constants (both SCEC and DEC) and the influence of surface roughness, texture, and porosity on residual stresses.
This presentation will detail recent insights and recommendations for the characterization of residual stresses in a range of PBF-LB/M metallic alloys (Fe, Ni, Al and Ti)
The determination of residual stress in additively manufactured materials is a challenge, even after decades from the establishment of the basics of residual stress analysis. This is due to the peculiar microstructure of such materials. In fact, researchers have discovered that conventional methods for the determination of RS in materials do not properly work for AM materials. In this tutorial, the basics of RS analysis will be explained, together with the basics of AM manufacturing techniques. The microstructure of the peculiar materials (AM) dealt with here will be elucidated. Successively, the necessary modifications to the conventional approaches to RS analysis will be explained and case studies will be displayed, for the attendant to touch with hands the peculiarities of the approaches. Finally, a few experimental and theoretical tips will be given on dos and don’ts for a correct determination of RS in AM materials.
The thermal history during additive manufacturing of complex components differs significantly from the thermal history of geometrically primitive test specimens. This can result in differences in properties that can lead to different material behavior. In this talk, the concept of representative test specimens is introduced, which enables the transfer of thermal histories from complex geometries to simple geometries, which can lead to better comparability of material properties.
Laser Powder Bed Fusion (PBF-LB/M) of AISI 316L stainless steel has gained popularity due to its exceptional capacity to produce complex geometries and hierarchical microstructures, which can increase the yield strength while maintaining good ductility. Nevertheless, owing to high thermal gradients encountered during the process, the as printed 316L stainless steel often exhibit microstructural heterogeneities and residual stresses, which can limit its performance in demanding environments. Hence, employing heat treatments which balance the reduction of residual stresses while retaining improved static strength may be beneficial in various scenarios and applications. This study investigates the impact of post-processing heat treatments on the microstructure of 316L stainless steel manufactured via PBF-LB/M, along with its correlation with micro-hardness properties. To this end, 6 different heat treatments, i.e., 450 °C for 4h, 700 °C for 1h, 700 °C for 3h, 800 °C for 1h, 800 °C for 3h, and 900 °C for 1h, were applied to different specimens and Vickers hardness measurements (HV1) were performed in all states. At 800 °C, although the cellular structure appears to be retained, there is an observable increase in cellular size. However, while treatments exceeding 900 °C indicate no significant grain growth compared to other conditions, the cellular structure is entirely dissolved, which leads to a reduced Vickers hardness. The effect of the heat treatments on other microstructural features such as grain size and morphology, melt pool boundaries (MPB), crystallographic texture, chemical segregation, dispersoids and phase stability are also discussed in the present work
This study provides insights into the properties of 316L stainless steel produced by additive manufacturing using fused filament fabrication (FFF). One key finding is particularly noteworthy: in significant contrast to cold-rolled 316L, FFF316L develops a pronounced martensite phase after fabrication. The comprehensive comparative analysis shows that FFF316L not only retains the ferrite volume content, but that this is also significantly influenced by the build-up direction. Despite the sintering process, which typically involves densification of the material, a pore volume fraction of 8.45 % remains, which influences the mechanical properties. Although FFF316L has lower elastic
modulus and tensile strength values compared to cold-rolled 316L, its ductility is still competitive. The study further reveals that deformation-induced martensite forms at the intersections of the deformation twins and ferrite islands form at the grain boundaries during the compression and sintering phases. These findings highlight the challenges associated with FFF316L in specific application fields and signal the need to continue to carefully evaluate and improve the development of manufacturing technologies.
Die thermische Historie beim additiven Aufbau von komplexen Realkomponenten und geometrisch primitiven Prüfkörpern unterscheidet sich signifikant. Daraus können Eigenschaftsunterschiede resultieren, die zu unterschiedlichem Materialverhalten führen können. In diesem Vortrag wird das Konzept repräsentativer Probekörper eingeführt, das eine Übertragung thermischer Historien von komplexen Geometrien auf einfache Geometrien ermöglicht und hierdurch zu einer besseren Vergleichbarkeit der Werkstoffeigenschaften führen soll.
Development of representative test specimens by thermal history transfer in laser powder bed fusion
(2024)
The use of components manufactured by laser powder bed fusion (PBF LB/M) and subjected to fatigue loading is still hampered by the uncertainty about the homogeneity of the process results. Numerous influencing factors including the component’s geometry contribute to the risk of process instability and resulting inhomogeneity of properties. This drastically limits the comparability of different built parts and requires expensive full component testing. The thermal history as the spatiotemporal temperature distribution has been identified as a major cause for flaw formation. Therefore, it can be hypothesized that a similar thermal history between components and test specimens enhances their comparability. Following this assumption, a strategy is developed to transfer the intrinsic preheating temperature as a measure of comparability of thermal histories from a region of interest of a complex component to a simple test specimen. This transfer concept has been successfully proved by the use of FEM-based macroscale thermal simulations, validated by calibrated infrared thermography. An adoption of the specimen manufacturing process by the adjustment of the inter layer times was established to manufacture specimens which are representatives of a specific region of a large-scale component in terms of the thermal history similarity criterion. The concept is schematically illustrated in Figure 1 and was demonstrated using a pressure vessel geometry from the chemical industry.
Thermal transient problems, essential for modeling applications like welding and additive metal manufacturing, are characterized by a dynamic evolution of temperature. Accurately simulating these phenomena is often computationally expensive, thus limiting their applications, for example for model parameter estimation or online process control. Model order reduction, a solution to preserve the accuracy while reducing the computation time, is explored. This article addresses challenges in developing reduced order models using the proper generalized decomposition (PGD) for transient thermal problems with a specific treatment of the moving heat source within the reduced model. Factors affecting accuracy, convergence, and computational cost, such as discretization methods (finite element and finite difference), a dimensionless formulation, the size of the heat source, and the inclusion of material parameters as additional PGD variables are examined across progressively complex examples. The results demonstrate the influence of these factors on the PGD model’s performance and emphasize the importance of their consideration when implementing such models. For thermal example, it is demonstrated that a PGD model with a finite difference discretization in time, a dimensionless representation, a mapping for a moving heat source, and a spatial domain non-separation yields the best approximation to the full order model.
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.