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In this study, machine learning models are proposed to predict the Vickers hardness of AlSi10Mg alloys fabricated by laser powder bed fusion (LPBF). A total of 113 utilizable datasets were collected from the literature. The hyperparameters of the machine-learning models were adjusted to select an accurate predictive model. The random forest regression (RFR) model showed the best performance compared to support vector regression, artificial neural networks, and k-nearest neighbors. The variable importance and prediction mechanisms of the RFR were discussed by Shapley additive explanation (SHAP). Aging time had the greatest influence on the Vickers hardness, followed by solution time, solution temperature, layer thickness, scan speed, power, aging temperature, average particle size, and hatching distance. Detailed prediction mechanisms for RFR are analyzed using SHAP dependence plots.
The Ti-6Al-4V lattice structure is widely used in the aerospace industry owing to its high specific strength, specific stiffness, and energy absorption. The quality, performance, and surface roughness of the additively manufactured parts are significantly dependent on various process parameters. Therefore, it is important to study process parameter optimization for relative density and surface roughness control. Here, the part density and surface roughness are examined according to the hatching space, laser power, and scan rotation during laser-powder bed fusion (LPBF), and the optimal process parameters for LPBF are investigated. It has high density and low surface roughness in the specific process parameter ranges of hatching space (0.06–0.12 mm), laser power (225–325 W), and scan rotation (15°). In addition, to investigate the compressive behavior of the lattice structure, a finite element analysis is performed based on the homogenization method. Finite element analysis using the homogenization method indicates that the number of elements decreases from 437,710 to 27 and the analysis time decreases from 3,360 to 9 s. In addition, to verify the reliability of this method, stress–strain data from the compression test and analysis are compared.
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Although the Ti–6Al–4V alloy has been used in the aircraft industry owing to its excellent mechanical properties and low density, the low formability of the alloy hinders broadening its applications. Recently, laser-powder bed fusion (L-PBF) has become a novel process for overcoming the limitations of the alloy (i.e., low formability), owing to the high degree of design freedom for the geometry of products having outstanding performance used in hightech applications. In this study, to investigate the effect of bulk shape on the microstructure and mechanical properties of L-PBFed Ti-6Al-4V alloys, two types of samples are fabricated using L-PBF: thick and thin samples. The thick sample exhibits lower strength and higher ductility than the thin sample owing to the larger grain size and lower residual dislocation density of the thick sample because of the heat input during the L-PBF process.
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Recently, considerable attention has been given to nickel-based superalloys used in additive manufacturing. However, additive manufacturing is limited by a slow build rate in obtaining optimal densities. In this study, optimal volumetric energy density (VED) was calculated using optimal process parameters of IN718 provided by additive manufacturing of laser powder-bed fusion. The laser power and scan speed were controlled using the same ratio to maintain the optimal VED and achieve a fast build rate. Cube samples were manufactured using seven process parameters, including an optimal process parameter. Analysis was conducted based on changes in density and melt-pool morphology. At a low laser power and scan speed, the energy applied to the powder bed was proportional to
Powder flowability is critical in additive manufacturing processes, especially for laser powder bed fusion. Many powder features, such as powder size distribution, particle shape, surface roughness, and chemical composition, simultaneously affect the flow properties of a powder; however, the individual effect of each factor on powder flowability has not been comprehensively evaluated. In this study, the impact of particle shape (sphericity) on the rheological properties of Ti-6Al-4V powder is quantified using an FT4 powder rheometer. Dynamic image analysis is conducted on plasma-atomized (PA) and gas-atomized (GA) powders to evaluate their particle sphericity. PA and GA powders exhibit negligible differences in compressibility and permeability tests, but GA powder shows more cohesive behavior, especially in a dynamic state, because lower particle sphericity facilitates interaction between particles during the powder flow. These results provide guidelines for the manufacturing of advanced metal powders with excellent powder flowability for laser powder bed fusion.
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In the powder bed fusion (PBF) process, a 3D shape is formed by the continuous stacking of very fine powder layers using computer-aided design (CAD) modeling data, following which laser irradiation can be used to fuse the layers forming the desired product. In this method, the main process parameters for manufacturing the desired 3D products are laser power, laser speed, powder form, powder size, laminated thickness, and laser diameter. Stainless steel (STS) 316L exhibits excellent strength at high temperatures, and is also corrosion resistant. Due to this, it is widely used in various additive manufacturing processes, and in the production of corrosion-resistant components with complicated shapes. In this study, rectangular specimens have been manufactured using STS 316L powder via the PBF process. Further, the effect of heat treatment at 800 °C on the microstructure and hardness has been investigated.
Ti-6Al-4V alloy has a wide range of applications, ranging from turbine blades that require smooth surfaces for aerodynamic purposes to biomedical implants, where a certain surface roughness promotes biomedical compatibility. Therefore, it would be advantageous if the high volumetric density is maintained while controlling the surface roughness during the LPBF of Ti-6Al-4V. In this study, the volumetric energy density is varied by independently changing the laser power and scan speed to document the changes in the relative sample density and surface roughness. The results where the energy density is similar but the process parameters are different are compared. For comparable energy density but higher laser power and scan speed, the relative density remained similar at approximately 99%. However, the surface roughness varies, and the maximum increase rate is approximately 172%. To investigate the cause of the increased surface roughness, a nonlinear finite element heat transfer analysis is performed to compare the maximum temperature, cooling rate, and lifetime of the melt pool with different process parameters.
In this study, AlSi10Mg alloy powders are synthesized using gas atomization and sieving processes for powder bed fusion (PBF) additive manufacturing. The effect of nozzle diameter (ø = 4.0, 4.5, 5.0 and 8.0 mm) on the gas atomization and sieving size on the properties of the prepared powder are investigated. As the nozzle diameter decreases, the size of the manufactured powder decreases, and the uniformity of the particle size distribution improves. Therefore, the ø 4.0 mm nozzle diameter yields powder with superior properties. Spherically shaped powders can be prepared at a scale suitable for the PBF process with a particle size distribution of 10–45 μm. The Hausner ratio value of the powder is measured to be 1.24. In addition, the yield fraction of the powder prepared in this study is 26.6%, which is higher than the previously reported value of 10–15%. These results indicate that the nozzle diameter and the post-sieve process simultaneously influence the shape of the prepared powder as well as the satellite powder on its surface.
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Powder characteristics, such as density, size, shape, thermal properties, and surface area, are of significant importance in the powder bed fusion (PBF) process. The powder required is exclusive for an efficient PBF process. In this study, the particle size distribution suitable for the powder bed fusion process was derived by modeling the PBF product using simulation software (GeoDict). The modeling was carried out by layering sintered powder with a large particle size distribution, with 50 μm being the largest particle size. The results of the simulation showed that the porosity decreased when the mean particle size of the powder was reduced or the standard deviation increased. The particle size distribution of prepared titanium powder by the atomization process was also studied. This study is expected to offer direction for studies related to powder production for additive manufacturing.
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In this study, H13 tool steel sculptures are built by a metal 3D printing process at various laser scan speeds. The properties of commercial H13 tool steel powders are confirmed for the metal 3D printing process used: powder bed fusion (PBF), which is a selective laser melting (SLM) process. Commercial H13 powder has an excellent flowability of 16.68 s/50 g with a Hausner ratio of 1.25 and a density of 7.68 g/cm3. The sculptures are built with dimensions of 10 × 10 × 10 mm3 in size using commercial H13 tool steel powder. The density measured by the Archimedes method is 7.64 g/cm3, similar to the powder density of 7.68 g/cm3. The hardness is measured by Rockwell hardness equipment 5 times to obtain a mean value of 54.28 HRC. The optimum process conditions in order to build the sculptures are a laser power of 90 W, a layer thickness of 25 μm, an overlap of 30%, and a laser scan speed of 200 mm/s.
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