• 한국주조공학회지
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• 제33권2호
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• pp.55-62
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• 2013

Effect of Fe and Mn contents on the castability of Al-4wt%Mg-0.9wt%Si system alloy has been studied. According to the analysis of cooling curve for Al-4wt%Mg-0.9wt%Si-0.3wt%Fe-0.3/0.5wt%Mn alloy, ${\alpha}-Al_{15}(Fe,Mn)_3Si_2$ and ${\beta}-Al_5FeSi$ phases crystallized above eutectic temperature of $Mg_2Si$. Therefore, these phases affected both the fluidity and shrinkage behaviors of the alloy during solidification. As Fe and Mn contents of Al-4wt%Mg-0.9wt%Si system alloy increased from 0.1 wt% to 0.4 wt% and from 0.3 wt% to 0.5 wt% respectively, the fluidity of the alloy decreased by 26% and 33%. When Fe content of the alloy increased from 0.1 wt% to 0.4 wt%, 23% decrease of macro shrinkage and 19% increase of micro shrinkage appeared. Similarly, Mn content of the alloy increased from 0.3 wt% to 0.5 wt%, 11% decrease of macro shrinkage and 14% increase of micro shrinkage appeared. Judging from the castability of the alloy, Al-4wt%Mg-0.9wt%Si alloy with low content of Fe and Mn, 0.1 wt% Fe and 0.3 wt% Mn, is recommendable.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.297-301
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• 2002

High-speed machining generates concenter thermal/frictional damage at the cutting ed rapidly decreases the tool life. This paper I at determining the effect of cutter orienter the cutting environment on tool life, tool mechanism when down milling. In this paper, experiments were carried out in various tool and cutting environments, such as dry, wet compressed chilled air, tool life were measu evaluate machinability in high-speed milli difficult-to-cut material and die steel, Tool measured in horizontal upwards, horiz downwards, vertical upwards and vert downwards. In addition, tool life was measur dry, wet and compressed chilled air. For this a compressed chi1led-air system was manufact The results show that a horizontal cutter ori provided a longer tool life than a vertical orientation. With respect to the cutting envi compressed chilled air increased tool life. H the wet condition decreased tool life due thermal shock caused by excessive cooling high-speed mill ins and the compressed chilled had little effect.

• 한국추진공학회지
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• 제4권1호
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• pp.1-12
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• 2000

유도탄의 성능 향상을 위해 추진기관의 경량화가 요구되고 있으며 연소관 모타 마개의 경우, Ti 합금 (Ti-6Al-4V)이 사용되고 있다. 제작 과정 중에 열간 형단조 공정이 이용되나 이 과정에서 Ti alloy의 좁은 성형 온도 구간 관계로 단조시 국부적 소성 변형 집중에 의한 결함이 단조품의 다수 생성되며, 심한 경우 전단 파단까지 이르고 있다. 성형 과정에서 금형과의 접촉에 의한 Ti 합금 온도 하강이 전단 파단 발생과 밀접한 관계를 갖고 있으며 따라서 각 단조 조건에 따른 Ti 합금의 내부 및 표면에 대한 변형 및 온도의 분포가 관찰되었다. 아울러 전단 밴드 형성에 대한 별도의 분석도 포함되었다.

• Design & Manufacturing
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• 제15권3호
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• pp.7-12
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• 2021

Plastic injection molds used for rapid heating and cooling must minimize surface damage due to friction and maintain excellent thermal and low electrical conductivity. Accordingly, various surface treatments are being applied. The properties of Al₂O₃ coating and DLC coating were compared to find the optimal surface treatment method. Al₂O₃ coating was deposited by thermal spray method. DLC films were deposited by sputtering process in room temperature and high temperature PECVD (Plasma enhanced chemical vapor deposition) process in 723 K temperature. For the evaluation of physical properties, the electrical and thermal conductivity including surface hardness, adhesion and wear resistance were analyzed. The electrical resistance of the all coated samples was showed insulation properties of 24 MΩ/sq or more. Especially, the friction coefficient of high temp. DLC coating was the lowest at 0.134.

• Design & Manufacturing
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• 제16권3호
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• Design & Manufacturing
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• 제17권1호
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• pp.1-5
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• 2023

In multi-material injection molding, since two or more materials with different process conditions are used, it is essential to maximize process efficiency by operating the cooling or heating system to a minimum. In this study, Liquid silicone rubber (LSR) that can be cured at a low temperature suitable for the multi-material injection molding was selected and the cure behavior according to the process conditions was analyzed through differential scanning calorimetry (DSC). Dynamic measurement results of DSC with different heating rate were obtained, and through this, the total heat of reaction when the LSR was completely cured was calculated. Isothermal measurement results of DSC were derived for 60 minutes at each temperature from 80 ℃ to 110 ℃ at 10 ℃ intervals, and the final degree of cure at each temperature was calculated based on the total heat of reaction identified from the Dynamic DSC measurement results. As the result, it was found that when the temperature is lowered, the curing start time and the time required for the curing reaction increase, but at a temperature of 90 ℃ or higher, LSR can secure a degree of cure of 80% or more. However, at 80 ℃., it was found that not only had a relatively low degree of curing of about 60%, but also significantly increased the curing start time. In addition, in the case of 110 ℃, the parameters were derived from experimental result using the Kamal kinetic model.

• Design & Manufacturing
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• 제17권2호
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• pp.62-69
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• 2023

In this study, we conducted a study on the optimization of injection molding conditions to minimize deformation of plastic product. The charging management system housing of the vehicle was selected as the research subject. Melting temperature, cooling temperature, packing time, and packing pressure were selected as the main factors expected to affect the deformation of molded products. Each main factor was divided into 5 levels. Optimization of injection molding conditions to minimize deformation was performed using the Taguchi Method. We performed an analysis of variance (ANOVA) to identify significant factors affecting the deformation of plastic product. In order to select injection molding conditions that minimize deformation of plastic products, injection molding analysis was additionally performed for insignificant factors. We then compared the deformation of the molded part before and after optimization. As a result of comparing the injection analysis results of the basic conditions and the injection analysis results of the optimal conditions, it was confirmed that the amount of deformation after optimization was improved by about 10.9%.

• Design & Manufacturing
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• 제18권2호
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• pp.64-73
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• 2024

The purpose of this paper is to introduce a fusion method that combines the design of experiments (DOE) and machine learning to optimize the bias of plastic products. The study focuses on the plastic motor housing used in automobiles, which is manufactured through plastic injection molding. Achieving optimal molding for the motor housing involves the optimization of various molding conditions, including injection pressure, injection time, holding pressure, mold temperature, and cooling time. Failure to optimize these conditions can lead to increased product deformation. To minimize the deformation of the motor housing, the widely used Taguchi method, which is one of the design of experiment techniques, was employed to identify the injection molding conditions that affect deformation. Machine learning was then applied to various models based on the identified molding conditions. Among the models, the Random Forest model emerged as the most effective in predicting deformation amounts. The validity of the Random Forest model was also confirmed through verification. The verification results demonstrated the excellent prediction accuracy of the trained Random Forest model. By utilizing the validated model, molding conditions that minimize deformation were determined. Implementation of these optimal molding conditions led to a reduction of approximately 5.3% in deformation compared to the conditions before optimization. It is noteworthy that all injection molding outcomes presented in this paper were obtained through robust injection molding simulations, ensuring both research objectivity and speed.

• 한국식품저장유통학회지
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• 제31권4호
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• pp.518-526
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• 2024

This study analyzed the quality of texturized vegetable protein (TVP) made from defatted soy flour combined with flour or starch from rice sources. The base raw material formulation consisted of 50% soybean protein, 30% gluten, and 20% rice flour and rice starch. A cooling die-equipped extruder was used with a barrel temperature of 190℃ and screw rotation speed of 250 rpm. The hardness and cutting strength of the extruded TVP were found to be higher for white rice than for glutinous rice and higher for flour than for starch. Gumminess and chewiness were similar across rice types, but higher for flour than for starch. White rice TVP had a lower water absorption capacity than glutinous rice TVP. Turbidity was lowest for white rice flour and highest for corn starch. Using rice flour instead of starch in TVP production can simplify processing and contribute to promoting the consumption of rice.

• 방사성폐기물학회지
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• 제7권4호
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• pp.213-218
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• 2009

전해제련 공정은 악티늄족 원소를 동시에 회수하는 공정으로써, Pyroprocessing의 핵확산 저항성을 보장하는 중요한 공정이다. 공학규모의 전해제련 장치를 설계하기 위한 기본 도구를 개발하기 위해서 실험실 규모의 장치에 대한 열전달 해석을 수행하였다. 열전달 해석을 수치 해석적으로 계산하기 위해 ANSYS CXF 상용 코드를 사용하였다. 열전달 해석 결과, 가열부의 길이가 수직으로 용융염의 높이보다 약3배 이상이 되었을 때, 용융염의 온도를 일정하게 유지할 수 있었으며, 냉각부의 길이는 그 영향이 미비하였다. 전해조 덮개 아래의 아르곤 가스의 온도는 냉각 판의 개수에 따라 감소하였으며, 5개 이상 설치 할 경우 $250^{\circ}C$ 이하로 유지할 수 있음을 보였다. 이러한 계산 결과는 실제 실험 장치에서 측정된 장치 내부 온도 분포와 경향성이 일치하는 것을 볼 수 있었다. 본 연구에서 해석 된 전해제련 장치의 열 분포 특성은 공학규모 장치의 설계를 위해 중요한 자료로 사용 될 수 있을 것이다.