• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1997년도 추계학술대회논문집
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• pp.176-181
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• 1997

During a compression molding of continuous fiber reinforced composites, the separation of matrix and fiber is caused by the flow of the molding process. As the characteristics of the products are greatly dependent on the separation, it is very important to clarify the separation in relation to molding condition, degree of needle punching number on the degree of nonhomogeneity are studied.

• 소성∙가공
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• 제31권1호
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• pp.29-38
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• 2022

Recently, the composite material market is gradually growing. Various composite forming processes have been developed in order to reduce the production cost of the composite material. Unlike the conventional forming process, the microwave composite forming process has the advantage of reducing the processing time because the composite material is heated directly or indirectly at the same time. Due to this advantage, in this study, a double cantilever beam test was conducted with specimens manufactured by the microwave composite forming process. The purpose of this study was to compare mode-I energy release rate for specimens manufactured by prepreg compression forming and microwave composite forming processes. First, a microwave oven was proposed to conduct the microwave composite forming process. Double cantilever beam specimens were manufactured. After that, the double cantilever beam test was conducted to obtain the mode-I energy release rate. Mode-I energy release rates of specimens manufactured by the microwave composite forming and prepreg compression forming processes were then compared. As a result, mode-I energy release rates of specimens fabricated by the microwave composite forming process were similar to those fabricated with the prepreg compression forming process with a relatively reduced process time.

• 한국정밀공학회지
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• 제13권2호
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• pp.37-47
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• 1996

This paper presents an automatic tele-inspection scheme for the remotely manufacturing process. The remote-manufacturing process is continuously monitored and a crucial process is captured by CCD Camera. The captured image is compressed by neural network and JPEG, and it is sent directly to the assembly plant for incoming inspection. Massive image data require broadband channel to transmit them to remote distance, but sender is able to transmit them to receiver in use common channel by compressing massive image data in the high ratio. After the receiver reconstructs the compressed image to be transmitted, the reconstructed image is also directly used for automatic inspection of the process. The Experimental results show that the proposed inspection mechanism could be effectively implemented for real applications.

• 소성∙가공
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• 제19권5호
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• pp.305-310
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• 2010

Recently industry of motor vehicle is making a gradual progress of automotive electric components. According to this step, wire harness equipped at motor vehicle is also increased. The most important component at the wire harness is electric connector. At the manufacturing process of electric connector, exactly at the crimping process, design variables, such as clamping-height, clamping-width and clamping die shape are critical parameters to assure satisfactory harness shape in clamping process of electric connector. In this study we have performed FEM simulation for clamping process and clarified the effect of design variables on compression rate of wire.

• International Journal of Precision Engineering and Manufacturing
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• 제8권1호
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• pp.66-72
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• 2007

A computer code was developed to simulate the filling stage of an injection/compression molding process using a finite element method. The constitutive equation was the compressible Leonov model and the PVT relationship was assumed to follow the Tait equation. The flow-induced birefringence was related to the calculated flow stresses through the linear stress-optical law. Simulations of a disk under different processing conditions, including variations of the compression stroke and compression speed, were performed to determine their effects on the flow-induced birefringence. Simulated pressure traces were also compared to those obtained in conventional injection molding and with experimental data from the literature.

• 소성∙가공
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• 제3권2호
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• pp.215-228
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• 1994

The purpose of this paper is to pursue a general method to determine both the flow stress of a material and the friction factor by ring compression test. The materials are assumed to obey the expanded n-power hardening rule including the strain-rate effect. Ring compression is simulated by the rigid-plastic finite element method to obtain the database used in determining the flow stress and friction factor. The Simulation is conducted for various strain hardening exponent, strain-rate sensitivity, friction factor, and compressing speed, as variables. It is assumed that the friction factor is constant during the compression process. To evaluate the compatibility of the database, experiments are carried out at room and evaluated temperature using specimens of aluminum 6061-T6 under dry and grease lubrication condition. It is shown that the proposed test method is useful and easy to use in determining the flow stress and the friction factor.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 추계학술대회논문집
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• pp.65-69
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• 2004

A computer code was developed to simulate the filling stage of the injection/compression molding process by a finite element method. The constitutive equation used here was the compressible Leonov model. The PVT relationship was assumed to follow the Tait equation. The flow-induced birefringence was related to the calculated flow stresses through the linear stress-optical law. Simulations of a disk part under different processing conditions including the variation of compression stroke and compression speed were carried out to understand their effects on flow-induced birefringence. The simulated results were also compared with those by conventional injection molding and with experimental data from literature.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2022년도 추계학술대회
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• pp.112-115
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• 2022

The process of deep learning usually needs to deal with massive data which has greatly limited the development of deep learning technologies today. Convolutional Neural Network (CNN) structure is often used to solve image classification problems. However, a large number of images may be required in order to train an image in CNN, which is a heavy burden for existing computer systems to handle. If the image data can be compressed under the premise that the computer hardware system remains unchanged, it is possible to train more datasets in deep learning. However, image compression usually adopts the form of lossy compression, which will lose part of the image information. If the lost information is key information, it may affect learning performance. In this paper, we will analyze the effect of image compression on deep learning performance on CNN-based cat and dog classification. Through the experiment results, we conclude that the compression of images does not have a significant impact on the accuracy of deep learning.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.1245-1246
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• 2011

• 대한기계학회논문집A
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• 제21권1호
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• pp.154-163
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• 1997

Thermally-induced deformation in SMC(Sheet Molding Compound) products is analyzed using three dimensional finite element method. Planar fiber orientation, which causes the anisotropic material properties, is calculated through the flow analysis during the compression stage of the mold. Also curing process is analyzed to predict temperature profile which has significant effects on warpage of SMC products. Through the developed procedure, effects of various process conditions such as charge location, mold temperature, fiber contents, and fiber orientations on deformation of final products are studied. and processing strategies are proposed to reduce the warpage and the shrinkage.