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- Additive manufacturing (20) (entfernen)
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Directed energy deposition (DED) has been in industrial use as a coating process for many years. Modern applications include the repair of existing components and additive manufacturing. The main advantages of DED are high deposition rates and low energy input. However, the process is influenced by a variety of parameters affecting the component quality. Artificial neural networks (ANNs) offer the possibility of mapping complex processes such as DED. They can serve as a tool for predicting optimal process parameters and quality characteristics. Previous research only refers to weld beads: a transferability to additively manufactured three-dimensional components has not been investigated. In the context of this work, an ANN is generated based on 86 weld beads. Quality categories (poor, medium, and good) are chosen as target variables to combine several quality features. The applicability of this categorization compared to conventional characteristics is discussed in detail. The ANN predicts the quality category of weld beads with an average accuracy of 81.5%. Two randomly generated parameter sets predicted as “good” by the network are then used to build tracks, coatings,walls, and cubes. It is shown that ANN trained with weld beads are suitable for complex parameter predictions in a limited way.
With additive manufacturing in the powder bed, the component size is limited by the installation space. Joint welding of additively manufactured parts offers a possibility to remove this size limitation. However, due to the specific stress and microstructure state in the additively built material, it is unclear to what extent existing evaluation rules of joint welding are also suitable for welds on additive components. This is investigated using laser beam welding of additively manufactured pipe joints. The welds are evaluated by means of visual inspection, metallographic examinations as well as computed tomography. The types of defects found are comparable to conventional components. This is an indicator that existing evaluation regulations also map the possible defects occurring for weld seams on additive components.
Maintenance, repair and overhaul of components are of increasing interest for parts of high complexity and expensive manufacturing costs. In this paper a production process for laser metal deposition is presented, and used to repair a gas turbine burner of Inconel 718. Different parameters for defined track geometries were determined to attain a near net shape deposition with consistent build-up rate for changing wall thicknesses over the manufacturing process. Spot diameter, powder feed rate, welding velocity and laser power were changed as main parameters for a different track size. An optimal overlap rate for a constant layer height was used to calculate the best track size for a fitting layer width similar to the part dimension. Deviations in width and height over the whole build-up process were detected and customized build-up strategies for the 3D sequences were designed. The results show the possibility of a near net shape repair by using different track geometries with laser metal deposition.
Laser beam processes are increasingly used in the field of additive manufacturing.
Prominent methods are either powderbed-based like Laser Metal Fusion (LMF), or utilizing a powder nozzle like Laser Metal Deposition (LMD). While LMF allows the manufacturing of complex structures, build rate, part volumes and material flexibility are limited. In contrast, LMD is able to operate with high deposition rates on existing parts, and materials can be changed easily during the process. However LMD shape complexity is limited. Utilizing their respective strengths, a combination of these two additive technologies has the potential to produce complex parts with high deposition rates and increased material flexibility. In this paper, combined manufacturing with additive technologies LMF and LMD is described. Its benefit for industry with emphasis on turbomachinery is shown. As reality test for the innovation, an industrial turbine blade is manufactured.
The process of laser metal deposition can be applied in many ways. Mostly, it is relevant to coating, for repair welding and for additive manufacturing. To increase the effectiveness and the productiveness, a good process understanding is necessary. Statistical test planning is effectual and often used for this purpose. For financial and temporal reasons, a restriction of the test space is reasonable. In this case, it is recommended to use a D-optimal experimental design which is practically applied to extend existing test plans or if process Limits are known. This paper investigates the applicability of a D-optimum experimental design for the laser metal deposition. The results are compared to the current results of a full factorial test plan.
Known restrictions are used for the limitation of the test space. Ti6Al4 is utilized as Substrate material and powder. Comparable results of the D-optimal experimental design and of the full factorial test plan can be demonstrated. However, 80 % of time can be saved by the experimental procedure. For this reason, the application of D-optimal experimental design for laser metal deposition is recommend.
Laser metal deposition (LMD) has been applied as a coating technology for many years. Today, the technologies capacity to produce 3D depositions leads to a new field of application as additive manufacturing method. In this paper, 3D laser metal deposition of titanium alloy Ti-6Al-4V is studied with special regard to the demands of additive manufacturing. Therefore, only the coaxial LMD powder nozzle is used to create the shielding gas atmosphere, which ensures high geometric flexibility. Furthermore, specimen with high aspect ratio and hundreds of layers are manufactured, which represent typical features in additive manufacturing. The presented study contains the following steps: First, cylindrical specimens are manufactured with a standard shell-core build-up strategy and mechanical properties as well as fracture mechanisms are determined. Based on the results, experiments are conducted to improve the build-up strategy and new tensile test specimens are built with the improved strategy. The improved strategy incorporates variable track overlap ratios to achieve a constant growth in the shell and core area. As blanks, lean cylinders comprising more than 240 layers and a height of more than 120mm are manufactured. The specimens are analyzed by X-ray inspection for material defects. Fractured surfaces are observed via scanning electron microscopy and the composition of the surfaces is determined using energy dispersive X-ray spectroscopy. The tensile test results prove mechanical properties close to ASTM F1108 specification for wrought material.
Laser metal deposition (LMD) is an established technology for two-dimensional surface coatings. It offers high deposition rates, high material flexibility, and the possibility to deposit material on existing components. Due to these features, LMD has been increasingly applied for additive manufacturing of 3D structures in recent years. Compared to previous coating applications, additive manufacturing of 3D structures leads to new challenges regarding LMD process knowledge. In this paper, the process steps for LMD as additive manufacturing technology are described. The experiments are conducted using titanium alloy Ti-6Al-4Vand Inconel 718. Only the LMD nozzle is used to create a shielding gas atmosphere. This ensures the high geometric flexibility needed for additive manufacturing, although issues with the restricted size and quality of the shielding gas atmosphere arise. In the first step, the influence of process parameters on the geometric dimensions of single weld beads is analyzed based on design of experiments. In the second step, a 3D build-up strategy for cylindrical specimen with high dimensional accuracy is described. Process parameters, travel paths, and cooling periods between layers are adjusted. Tensile tests show that mechanical properties in the as-deposited condition are close to wrought material. As practical example, the fir-tree root profile of a turbine blade is manufactured. The feasibility of LMD as additive technology is evaluated based on this component.
Directed energy deposition is a metal additive manufacturing process that builds parts by joining material in a layer-by-layer fashion on a substrate. Those parts are exposed to rapid thermo-cycles which cause steep stress gradients and the layer-upon-layer manufacturing fosters an anisotropic microstructure, therefore stress relief heat treatment is necessary. The numerical simulation can be used to find suitable parameters for the heat treatment and to reduce the necessary efforts to perform an effective stress relieving. Suitable validation Experiments are necessary to verify the results of the numerical simulation.
In this paper, a 3D coupled thermo-mechanical model is used to simulate the heat treatment of an additive manufactured component to investigate the application of a C-ring geometry for the distortion-based validation of the numerical simulation.
Therefore, the C-ring samples were 3D scanned using a structured light 3D scanner to quantify the distortion after each process step.
In additive manufacturing (AM) directed energy deposition (DED), parts are built by welding layers of powder or wire feedstock onto a substrate with applications for steel powders in the fields of forging tools, spare parts, and structural components for various industries. For large and bulky parts, the choice of toolpaths influences the build rate, the mechanical performance, and the distortions in a highly geometry-dependent manner. With weld-path lengths in the range of hundreds of meters, a reliable, automated tool-path generation is essential for the usability of DED processes. This contribution presents automated tool-path generation approaches and discusses the results for arbitrary geometries. Socalled “zig-zag” and “contour-parallel” processing strategies are investigated and the tool-paths are automatically formatted into machine-readable g-code for experimental validation to build sample geometries. The results are discussed in regard to volume-fill, microstructure, and porosity in dependence of the path planning according to photographs and metallographic cross-sections.
Components distort during directed energy deposition (DED) additive manufacturing (AM) due to the repeated localised heating. Changing the geometry in such a way that distortion causes it to assume the desired shape – a technique called distortion-compensation – is a promising method to reach geometrically accurate parts. Transient numerical simulation can be used to generate the compensated geometries and severely reduce the amount of necessary experimental trials. This publication demonstrates the simulation-based generation of a distortioncompensated DED build for an industrial-scale component. A transient thermo-mechanical approach is extended for large parts and the accuracy is demonstrated against 3d-scans. The calculated distortions are inverted to derive the compensated geometry and the distortions after a single compensation iteration are reduced by over 65%.