• Journal of Welding and Joining
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• v.32 no.4
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• pp.10-14
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• 2014

Laser aided Direct Metal Tooling(DMT) process is a kind of Additive Manufacturing processes (or 3D-Printing processes), which is developed for using various commercial steel powders such as P20, P21, SUS420, H13, D2 and other non-ferrous metal powders, aluminum alloys, titanium alloys, copper alloys and so on. The DMT process is a versatile process which can be applied to various fields like the mold industry, the medical industry, and the defense industry. Among of them, the application of DMT process to the mold industry is one of the most attractive and practical applications since the conformal cooling channel core of injection molds can be fabricated at the slightly expensive cost by using the hybrid fabrication method of DMT technology compared to the part fabricated with the machining technology. The main objectives of this study are to provide various characteristics of the parts made by DMT process compared to the same parts machined from bulk materials and prove the performance of the injection mold equipped with the conformal cooling channel core which is fabricated by the hybrid method of DMT process.

• Journal of Drive and Control
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• v.16 no.3
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• pp.51-58
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• 2019

The objective of this study was to investigate a simulation technology for the AM field based on ANSYS Inc.. The introduction of metal 3D printing AM process, and the examining of the present status of AM process simulation software, and the AM process simulation processor were done in the previous study (part 1). This present study (part 2) examined the use of the AM process simulation processor, presented in Part 1, through direct execution of Topology Optimization, Ansys Workbench, Additive Print and Additive Science. Topology Optimization can optimize additive geometry to reduce mass while maintaining strength for AM products. This can reduce the amount of material required for additive and significantly reduce additive build time. Ansys Workbench and Additive Print simulate the build process in the AM process and optimize various process variables (printing parameters and supporter composition), which will enable the AM to predict the problems that may occur during the build process, and can also be used to predict and correct deformations in geometry. Additive Science can simulate the material to find the material characteristic before the AM process simulation or build-up. This can be done by combining specimen preparation, measurement, and simulation for material measurements to find the exact material characteristics. This study will enable the understanding of the general process of AM simulation more easily. Furthermore, it will be of great help to a reader who wants to experience and appreciate AM simulation for the first time.

• Journal of Powder Materials
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• v.29 no.5
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• pp.363-369
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• 2022

AlSi10Mg alloys are being actively studied through additive manufacturing for application in the automobile and aerospace industries because of their excellent mechanical properties. To obtain a consistently high quality product through additive manufacturing, studying the flowability and spreadability of the metal powder is necessary. AlSi10Mg powder easily forms an oxide film on the powder surface and has hydrophilic properties, making it vulnerable to moisture. Therefore, in this study, AlSi10Mg powder was hydrophobically modified through silane surface treatment to improve the flowability and spreadability by reducing the effects of moisture. The improved flowability according to the number of silane surface treatments was confirmed using a Carney flowmeter. In addition, to confirm the effects of improved spreadability, the powder prior to surface treatment and that subjected to surface treatment four times were measured and compared using s self-designed recoating tester. The results of this study confirmed the improved flowability and spreadability based on the modified metal powder from hydrophilic to hydrophobic for obtaining a high-quality additive manufacturing product.

• Journal of Powder Materials
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• v.30 no.3
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• pp.223-232
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• 2023

Metal additive manufacturing (AM) has transformed conventional manufacturing processes by offering unprecedented opportunities for design innovation, reduced lead times, and cost-effective production. Aluminum alloy, a material used in metal 3D printing, is a representative lightweight structural material known for its high specific strength and corrosion resistance. Consequently, there is an increasing demand for 3D printed aluminum alloy components across industries, including aerospace, transportation, and consumer goods. To meet this demand, research on alloys and process conditions that satisfy the specific requirement of each industry is necessary. However, 3D printing processes exhibit different behaviors of alloy elements owing to rapid thermal dynamics, making it challenging to predict the microstructure and properties. In this study, we gathered published data on the relationship between alloy composition, processing conditions, and properties. Furthermore, we conducted a sensitivity analysis on the effects of the process variables on the density and hardness of aluminum alloys used in additive manufacturing.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.7-15
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• 2020

Recently, the fourth industrial revolution has been presented as a new paradigm and additive manufacturing (AM) has become one of the most important topics. For this reason, process monitoring for each cross-sectional layer of additive metal manufacturing is important. Particularly, deep learning can train a machine to analyze, optimize, and repair defects. In this paper, image classification is proposed by learning images of defects in the metal cross sections using the convolution neural network (CNN) image labeling algorithm. Defects were classified into three categories: crack, porosity, and hole. To overcome a lack-of-data problem, the amount of learning data was augmented using a data augmentation algorithm. This augmentation algorithm can transform an image to 180 images, increasing the learning accuracy. The number of training and validation images was 25,920 (80 %) and 6,480 (20 %), respectively. An optimized case with a combination of fully connected layers, an optimizer, and a loss function, showed that the model accuracy was 99.7 % and had a success rate of 97.8 % for 180 test images. In conclusion, image labeling was successfully performed and it is expected to be applied to automated AM process inspection and repair systems in the future.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.104-107
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• 2002

Direct Metal Manufacturing (DMM) is a new additive process that aims to take die making and metalworking in an entirely new direction. It is the blending of five common technologies : lasers, computer-aided design (CAD), computer-aided manufacturing (CAM), sensors and powder metallurgy. The resulting process creates parts by focusing an industrial laser beam onto a tool-steel work piece or platform to create a molten pool of metal. A small stream of powdered tool-steel metal is then injected into the melt pool to increase the size of the molten pool. By moving the laser beam back and forth, under CNC control, and tracing out a pattern determined by a computerized CAD design, the solid metal part is built line-by-line, one layer at a time. DMM produces improved material properties in less time and at a lower cast than is possible with traditional fabrication.

• Transactions of Materials Processing
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• v.31 no.5
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• pp.309-328
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• 2022

• The Journal of Advanced Prosthodontics
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• v.7 no.4
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• pp.294-302
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• 2015

PURPOSE. The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). MATERIALS AND METHODS. Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (${\alpha}=.05$). RESULTS. The mean marginal gaps and internal gaps showed significant differences according to tooth type (P<.001 and P<.001, respectively) and manufacturing method (P<.037 and P<.001, respectively). Micro-SLA did not show any significant difference from CLWT regarding mean marginal gap compared to the WBM and MJM methods. CONCLUSION. The mean values of gaps resulting from the four different manufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing.

• Journal of Powder Materials
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• v.27 no.2
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• pp.164-173
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• 2020

Metal matrix composites (MMCs), which are a combination of two or more constituents with different physical or chemical properties, are today receiving great attention in various areas, as they have high specific strength, corrosion resistance, fatigue strength, and good tribological properties. This paper presents a research review on the combination of matrix and reinforced materials, fabrication processes, and application status of metal matrix composites. In this paper, we aim to discuss and review the importance of metal composite materials as advanced materials that can be used in various applications such as transportation, defense, sports, and extreme environments. In addition, the applicability and technology development trends in new process technology fields such as additive manufacturing of metal composites will be described.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.9-14
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• 2015

The Direct Metal Tooling (DMT) process is a kind of additive manufacturing processes, which is developed using various commercial steel powders, such as P20, P21, SUS420, and other non-ferrous metal powders. The DMT process is a versatile process that can be applied to various fields, such as the molding industry, the medical industry, and the defense industry. Among them, the application of the DMT process to the molding industry is one of its most attractive and practical applications, since the conformal cooling channel cores of injection molds can be fabricated at a slightly expensive cost by using the hybrid fabrication method of DMT technology compared with parts fabricated with machining technology. The main objectives of this study are to provide various characteristics of the parts made using the DMT process compared with the same parts machined from bulk materials and evaluate the performance of the injection mold equipped with a conformal cooling channel core fabricated using the hybrid method of the DMT process.