• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.347-352
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• 2019

This study focused on improving the cast quality of small-sized induction motor rotors during the die casting process. A new rotor core cast model was proposed based on previous research results and parametric studies. Numerical analyses using 3-dimensional half models were performed to evaluate the filling patterns of aluminum molten metals into a mold and on-site experiment performed to verify the newly proposed cast model. The following were obtained from numerical filling analyses and experimental results. First, molten metals started to fill the lower end ring, then moved on to fill the core slot and upper end ring and finally stopped to fill at the rotor core slot. Second, significant circulation of molten metals was not observed on the lower end ring, resulting in fewer defects at the section of the lower end ring from the experimental results. Third, the new shape of a rotor core cast was effective in producing rotors with sound cast quality, and reducing the end ring cast defect area by approximately 70 %.

• Journal of Korea Foundry Society
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• v.42 no.6
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• pp.369-376
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• 2022

The die-casting process is an important process for various industries, but there are limitations in the profitability and productivity of related companies due to the high defect rate. In order to overcome this, this study has developed die-casting fault detection modules based on industrial AI technologies. The developed module is constructed from three-stage models depending on the characteristics of the dataset. The first-stage model conducts fault detection based on supervised learning from the dataset without labels. The second-stage model realizes one-class classification based on semi-supervised learning, where the dataset only has production success labels. The third-stage model corresponds to fault detection based on supervised learning, where the dataset includes a small amount of production failure cases. The developed fault detection module exhibited outstanding performance with roughly 96% accuracy for actual process data.

• Journal of Korea Foundry Society
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• v.42 no.1
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• pp.3-11
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• 2022

In this study, the parameters on the shrinkage defect of HR3C alloy was secured through computer simulation research, and the ingot mold with greater than 85% of sound area was designed and manufactured. Moreover, the optimized coagulation was proposed at design stage through computer simulation and test was performed upon ingot manufactured. After the test, the defect pattern was analyzed through cutting and non-destructive inspection to verify the parameter and ingot mold design. Based on the verification results, shrinkage defect parameters such as Niyama, Feed Efficiency, and Hot Tear Intensity of HR3C Alloys were obtained. In addition, through the secured parameters, a plan for designing ingot mold with a Non-defect area of 85% or more was secured.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.312-320
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• 2023

Recently, there has been an increasing attempt to replace defect detection inspections in the manufacturing industry using deep learning techniques. However, obtaining substantial high-quality labeled data to enhance the performance of deep learning models entails economic and temporal constraints. As a solution for this problem, semi-supervised learning, using a limited amount of labeled data, has been gaining traction. This study assesses the effectiveness of semi-supervised learning in the defect detection process of manufacturing using the MixMatch algorithm. The MixMatch algorithm incorporates three dominant paradigms in the semi-supervised field: Consistency regularization, Entropy minimization, and Generic regularization. The performance of semi-supervised learning based on the MixMatch algorithm was compared with that of supervised learning using defect image data from the metal casting process. For the experiments, the ratio of labeled data was adjusted to 5%, 10%, 25%, and 50% of the total data. At a labeled data ratio of 5%, semi-supervised learning achieved a classification accuracy of 90.19%, outperforming supervised learning by approximately 22%p. At a 10% ratio, it surpassed supervised learning by around 8%p, achieving a 92.89% accuracy. These results demonstrate that semi-supervised learning can achieve significant outcomes even with a very limited amount of labeled data, suggesting its invaluable application in real-world research and industrial settings where labeled data is limited.

• Journal of Korean Neurosurgical Society
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• v.52 no.6
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• pp.541-546
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• 2012

Objective : The prefabrication of customized cranioplastic implants has been introduced to overcome the difficulties of intra-operative implant molding. The authors present a new technique, which consists of the prefabrication of implant molds using three-dimensional (3D) printers and polymethyl-methacrylate (PMMA) casting. Methods : A total of 16 patients with large skull defects (>100 $cm^2$) underwent cranioplasty between November 2009 and April 2011. For unilateral cranial defects, 3D images of the skull were obtained from preoperative axial 1-mm spiral computed tomography (CT) scans. The image of the implant was generated by a digital subtraction mirror-imaging process using the normal side of the cranium as a model. For bilateral cranial defects, precraniectomy routine spiral CT scan data were merged with postcraniectomy 3D CT images following a smoothing process. Prefabrication of the mold was performed by the 3D printer. Intraoperatively, the PMMA implant was created with the prefabricated mold, and fit into the cranial defect. Results : The median operation time was $184.36{\pm}26.07$ minutes. Postoperative CT scans showed excellent restoration of the symmetrical contours and curvature of the cranium in all cases. The median follow-up period was 23 months (range, 14-28 months). Postoperative infection was developed in one case (6.2%) who had an open wound defect previously. Conclusion : Customized cranioplasty PMMA implants using 3D printer may be a useful technique for the reconstruction of various cranial defects.

• Journal of the Korean Ceramic Society
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• v.36 no.1
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• pp.61-68
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• 1999

To analyze several defects and residual stress in sintering of layer structure materials, multiayer materials with TZP/SUS and ZT/SUS, and bilayer materials with porcelain/alumina and porcelain/Y-TZP were fabricated by sintering method. Multilayer materials prepared by pressureless sintering show the sintering defect such as warping, splitting, cracking originated from the difference of sintering shrinkage between each layer, which could be controlled by the adjustment of number and thickness in interlayer. In tape casting, a certain pressure given during sintering relaxed the sintering defects, specially warping. The residual stress in bilayer was examined with Vickers indentation method. A small tensile stress in porcelain/alumina and a large compressive stress in porcelain/Y-TZP were generated on the porcelain interface due to the thermal expansion mismatch, which affected the strength of bilayer materials. As a consequence, the sintering defects of multilayer materials and the residual stresses of bilayer materials were dominantly influenced on material design and starting material constants.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.305-308
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• 2001

Powder injection molding (PIM) uses the shaping advantage of injection molding but is applicable to metals and ceramics. This process combines a small quantity of polymer with an inorganic powder to form a feedstock that can be molded. After shaping, the polymeric binder is extracted and the powder is sintered often to near-theoretical densities. Accordingly, PIM delivers structural materials in a shaping technology previously restricted to polymers. The process overcomes the shape limitations of traditional powder compaction, the costs of machining, the productivity limits of isostatic pressing and slip casting, and the defect and tolerance limitations of casting. The 17-4 PH stainless steel powders with average diameter of $10{\mu}m$ were injection-molded into flat tensile specimens. Sintering of the compacts was carried out at the various temperatures ranging from 900 to $1350^{\circ}C$. Sintering behavior of the compacts and tensile properties of sintered specimens were investigated.

• Journal of Korea Foundry Society
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• v.24 no.2
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• pp.94-100
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• 2004

Gas porosity which is a common defect in aluminum alloy casting, is also thought to be severer in aluminum alloy castings produced by lost foam process due to the pyrolysis of the polystyrene foam pattern during pouring. Fundamental experiments were carried out to evaluate the effect of process variables such as the melt treatment, the cooling rate and pouring temperature on the density and mechanical properties in A356.2 castings with simple bar shape. The density of grain refined specimen was slightly lower than that of degassed one, but was higher than that of no treated one and that of shot ball packed specimen was higher than the other specimens. The tensile strength and elongation were in the ranges of $200{\sim}230MPa$ and $0.5{\sim}1.5%$ respectively. The density and hardness of lost foam cast specimens decreased with increase in pouring temperature.

• Journal of Korea Foundry Society
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• v.22 no.1
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• pp.17-25
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• 2002

Recently, many studies have been carried out to process on the purpose of lightness in a transport parts because of the saving energy, the environmental problem. The cast-forging process can be expected to lower costs without decreasing the mechanical properties. So, the finest microstructure is needed to get for applying the cast-forging process with Al-Si alloy because the microstructure affects to the cast-forging process. For refinement treatment of eutectic Si and Al solid-solution phase, Sr and TiB were added in Al-Si alloys. The finest microstructure could be observed when 0.075 wt.%Sr and 0.1 wt.%TiB were added respectively. In this case, tensile strength and elongation much more increased than as casting. After high temperature deformation simulation test with grain refinement specimens was carried out, about 70N per unit $area(mm^2)$ of specimen was confirmed. After hot forging, tensile strength and elongation were increased. It was considered because casting defect was removed by compressive working.

• Journal of Korea Foundry Society
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• v.19 no.1
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• pp.47-53
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• 1999

Squeeze casting process has been used in the field of a commercial manufacturing method, in which metal is enforcedly solidified under pressure enough to prevent the cast defects such as either gas porosity or shrinkage defect. In this paper, to clarify the relationship between applied pressures and macro ${\cdot}$ microstructural behaviors in gravity and direct squeeze casts, specimens were cast by various squeezing pressures during solidification of 7000 series Al wrought alloy in the metal die designed specially. The applied pressures used in this study were 0, 25, 50, and 75 MPa. The microstructural morphologies of squeeze cast were more fine and dense with increasing the applied pressures, because of the greater solidification rate of billet resulting from the applied pressure. A normal segregation phenomenon of an increasing in amount of eutectics towards the center of the billet was observed for squeeze casts, whereas gravity cast showed an inverse segregation phenomenon of an increasing in amount of eutectics towards the edge in the billet. This change in segregation pattern which is normal or inverse is due to a higher radial temperature gradient and reduced time in the semi solid state for squeeze casting.