• Journal of Powder Materials
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• v.28 no.2
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• pp.120-126
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• 2021

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 ㎛. 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.10-20
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• 2022

Recently, metal additive manufacturing (AM) is being investigated as a new manufacturing technology. In metal AM, powder bed fusion (PBF) is a promising technology that can be used to manufacture small and complex metallic components by selectively fusing each powder layer using an energy source such as laser or an electron beam. PBF includes selective laser melting (SLM) and electron beam melting (EBM). SLM uses high power-density laser to melt and fuse metal powders. EBM is similar to SLM but melts metals using an electron beam. When these processes are applied, the mechanical properties and microstructures change due to the many parameters involved. Therefore, this study is conducted to investigate the effects of the parameters on the mechanical properties and microstructures such that the processes can be performed more economically and efficiently.

• Journal of Powder Materials
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• v.27 no.1
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• pp.44-51
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• 2020

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 ㎛ 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.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.9
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• pp.773-779
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• 2015

The laser Powder Bed Fusion (PBF) system is currently recognized as a leading process. Due to the various materials employed such as thermoplastic, metal and ceramic composite powder, the application's use extends to machinery, automobiles, and medical devices. The PBF system's surface quality of prototypes and processing time are significantly affected by several parameters such as laser power, laser beam size, heat temperature and laminate thickness. In order to develop a more elaborate and rapid system, this study developed a new PBF system and sintering process. It contains a 3-axis dynamic focusing scanner system that maintains a uniform laser beam size throughout the system unlike the $f{\theta}$ lens. In this study, experiments were performed to evaluate the effects of various laser scanning parameters and fabricating parameters on the fusion process, in addition to fabricating various 3D objects using a PA-12 starting material.

• Journal of Powder Materials
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• v.29 no.2
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• pp.99-109
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• 2022

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.

• Journal of Powder Materials
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• v.29 no.1
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• pp.14-21
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• 2022

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 ℃ on the microstructure and hardness has been investigated.

• Journal of Powder Materials
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• v.27 no.6
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• pp.509-519
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• 2020

A well-established characterization method is required in powder bed fusion (PBF) metal additive manufacturing, where metal powder is used. The characterization methods from the traditional powder metallurgy process are still being used. However, it is necessary to develop advanced methods of property evaluation with the advances in additive manufacturing technology. In this article, the characterization methods of powders for metal PBF are reviewed, and the recent research trends are introduced. Standardization status and specifications for metal powder for the PBF process which published by the ISO, ASTM, and MPIF are also covered. The establishment of powder characterization methods are expected to contribute to the metal powder industry and the advancement of additive manufacturing technology through the creation of related databases.

• Journal of Powder Materials
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• v.30 no.2
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• pp.140-145
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• 2023

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 high-tech 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.

• Journal of Powder Materials
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• v.30 no.2
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• pp.146-155
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• 2023

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.

• Journal of Powder Materials
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• v.30 no.3
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• pp.210-216
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• 2023

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.