• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2006.06a
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• pp.55-60
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• 2006

Draw-bead is applied to control the material flow in a stamping process and improve the product quality by controlling the draw-bead restraining force (DBRF). Actual die design depends mostly on the trial-and-error method without calculating the optimum DBRF. Die design with the predicted value of DBRF can be utilized at the tryout stage effectively reducing the cost of the product development. For the prediction of DBRF, a simulation-based prediction model of the circular draw-bead is developed using the Box-Behnken design with selected shape parameters such as the bead height, the shoulder radius and the sheet thickness. The value of DBRF obtained from each design case by analysis is approximated by a second order regression equation. This equation can be utilized to the calculation of the restraining force and the determination of the draw-bead shape as a prediction model. For the evaluation of the prediction model, the optimum design of DBRF in sheet metal forming is carried out using response surface methodology. The suitable type of the draw-bead is suggested based on the optimum values of DBRF. The prediction model of the circular draw-bead proposes the design method of the draw-bead shape. The present procedure provides a guideline in the tool design stage for sheet metal forming to reduce the cost of the product development.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.918-925
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• 2021

The perovskite solar cell is a next-generation solar cell that replaces the existing silicon solar cell. It is a solar cell device using an organic-inorganic hybrid material having a perovskite structure as a photoactive layer. It has advantages for the process and has shown rapid efficiency improvement over the past decade. In the process of commercialization of such perovskite solar cells, research and development for a large-area coating method should be carried out. As one of the large-area perovskite solar cell large-area coating methods, the slot-die coating method was studied. By using a meniscus to pass over the substrate and coating the solution, the 3D printer was equipped with a meniscus so that it could be coated. Variables that act during coating include bed temperature, coating speed, N₂ blowing interval, N₂ blowing height, N₂ blowing intensity, etc. By controlling these, the perovskite absorption layer was manufactured and the coating conditions for manufacturing large-area devices were optimized.

• Design & Manufacturing
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• v.15 no.4
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• pp.24-31
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• 2021

In this study, an artificial neural network model was constructed to convert CAE analysis data into similar experimental data. In the analysis and experiment, the injection molding data for 50 conditions were acquired through the design of experiment and random selection method. The injection molding conditions and the weight, height, and diameter of the product derived from CAE results were used as the input parameters for learning of the convert model. Also the product qualities of experimental results were used as the output parameters for learning of the convert model. The accuracy of the convert model showed RMSE values of 0.06g, 0.03mm, and 0.03mm in weight, height, and diameter, respectively. As the next step, additional randomly selected conditions were created and CAE analysis was performed. Then, the additional CAE analysis data were converted to similar experimental data through the conversion model. An artificial neural network model was constructed to predict the quality of injection molded product by using converted similar experimental data and injection molding experiment data. The injection molding conditions were used as input parameters for learning of the predicted model and weight, height, and diameter of the product were used as output parameters for learning. As a result of evaluating the performance of the prediction model, the predicted weight, height, and diameter showed RMSE values of 0.11g, 0.03mm, and 0.05mm and in terms of quality criteria of the target product, all of them showed accurate results satisfying the criteria range.

• Transactions of Materials Processing
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• v.24 no.4
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• pp.280-286
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• 2015

Hemming is used to connect two sheet metal components by folding the edge of an outer panel around an inner panel to create a smooth edge. The minimization of hemming defects is critical to the final quality of automobile products because hemming is one of the last operations during fabrication. Designing the hemmed part is not easy and is influenced by the geometry of the bent part. Therefore, the main problem for automotive parts is dimensional accuracy since formed products often deviate geometrically due to large springback. Few numerical approaches using 3-dimensional finite element model have been applied to hemming due to the small element size which is needed to properly capture the bending behavior of the sheet around small die corner and the comparatively big size of automotive opening parts, such as doors, hoods and deck lids. The current study concentrates on the 3-dimensional numerical simulation of hemming for an automotive door. The relationship between the design parameters of the hemming operation and the height difference defect is shown. Quality improvement of the automotive door can be increased through the study of model parameters.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10b
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• pp.47-50
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• 2003

Grain size of the $\alpha$ phase is computed during isothermal forging of the TC6 aerofoil blade, by combining FE with the Yada's model of grain size. The present results illustrate the grain size and distribution of the $\alpha$ phase during isothermal forging of the TC6 aerofoil blade' in detail. The computed results show that height reduction, deformation temperature, hammer velocity and friction have significant effect on distribution of the equivalent strain, and that height reduction, deformation temperature and hammer velocity have more significant effect on grain size of the $\alpha$ phase than friction between billet and die.

• Journal of the Microelectronics and Packaging Society
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• v.23 no.4
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• pp.69-77
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• 2016

We propose nano-scale Cu direct bonding technology using ultra-high density Cu nano-pillar (CNP) with for high stacking yield exascale 2.5D/3D integration. We clarified the joining mechanism of nano-scale Cu direct bonding using CNP. Nano-scale Cu pillar easily bond with Cu electrode by re-crystallization of CNP due to the solid phase diffusion and by morphology change of CNP to minimize interfacial energy at relatively lower temperature and pressure compared to conventional micro-scale Cu direct bonding. We confirmed for the first time that 4.3 million electrodes per die are successfully connected in series with the joining yield of 100%. The joining resistance of CNP bundle with $80{\mu}m$ height is around 30 m for each pair of $10{\mu}m$ dia. electrode. Capacitance value of CNP bundle with $3{\mu}m$ length and $80{\mu}m$ height is around 0.6fF. Eye-diagram pattern shows no degradation even at 10Gbps data rate after the lamination of anisotropic conductive film.

• Journal of Industrial Technology
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• v.19
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• pp.67-74
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• 1999

The mechanical properties including forming limit and deep-drawability of commercially-used sheet metals were experimentally estimated in this study. Uniaxial tensile test to obtain basic mechanical properties was carried out, followed by limiting dome height (LDH) test and forming limit diagram (FLD) test to quantitatively evaluate the sheet-formability. Deep drawing and reverse drawing tests were also performed to find out the critical values of the blank holding force and the gap between the die and the blank holder which enabled the deep drawing and reverse drawing of a successful cop without any wrinkle or fracture. The thickness of the cup wall along the rolling-, transeverse- and $45^{\circ}$-directions was measured and compared with one another. And the punch force-stroke curve and the critical punch force expected from the theory coincided with the experimental result very well for mild steel while not for aluminium alloy.

• Transactions of Materials Processing
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• v.9 no.6
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• pp.670-680
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• 2000

The purpose of this study is to provide the database of forming limit diagram applicable to the warm forming of oil pan. The test materials are SCP1 and SCP3C with the thickness of 1.4mm which is used for the oil pan of automobile. The testing temperature is 5$^{\circ}C$~15$0^{\circ}C$ which is In the range of practical usage. The results are the forming limit diagram limiting dome height and the maximum punch load at each temperature such as 5$^{\circ}C$, $25^{\circ}C$, 6$0^{\circ}C$, 9$0^{\circ}C$, 12$0^{\circ}C$ and 15$0^{\circ}C$. From these results, we can see that the forming limit curves are translated depending upon the temperature and that FLC at low temperature is higher than at high temperature. Both of limiting dome height and maximum punch load also decrease as the temperature increases. Present results can be useful for die trial and forming analysis as a tool of evaluating the forming severity for the sheet metal forming processes at the warm working condition by comparing the practical strains with FLC.

• Design & Manufacturing
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• v.16 no.3
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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.

• The Journal of Korean Academy of Prosthodontics
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• v.44 no.5
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• pp.503-513
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• 2006

Statement of the problem: The cold-cured resins used in fabrication of the provisional crown and fixed partial dentures could cause pulpal damage by heat generated during exothermic polymerization reactions. Purpose: In this in vitro study investigates the how external conditions such as material of the matrix, thickness of the matrix and thickness of dentin affect the temperature of the tooth during polymerization reaction of the cold-cured resins. Material and methods : To measure the temperature of the resin, metal die was maintained to the temperature of $37^{\circ}C$ with water bath to simulate the temperature of thetooth and thermocouple was placed in the center of the metal die. Acrylic pipe was cut in height of 1, 2, 3, 6, 10 mm and placed on the metal die and mixed resin was pored in the acrylic pipe As the resin polymerized temperature was recorded with the thermometer. Temperature of the resin using matrix was recorded by using the individual tray relieved in different thickness 2, 5, 7, 10 mm. The material of the matrix was irreversible hydrocolloid impression material, vinyl polysilloxane impression material and vacuum-formed template Temperature rise of the resin using different thickness of tooth section was record ed by placing tooth section on the metal die and placing resin over the tooth section. Results : Conclusion : 1. Temperature rise increased as the thickness of the resin increased but there was no significant differences over 3 mm thickness of the resin. 2. The lowest temperature rise was showed in irreversible hydrocolloid impression material and vinyl polysilloxane impression material vacuum-formed template as in orders. 3, Temperature rise of the resin decreased regardless of the thickness of the matrix when vinyl polysilloxane impression material was used as the matrix. 4 When irreversible hydrocolloid impression material was used as matrix, the temperature rise of the resin decreased as the thickness of the matrix increased and there was no temperature rise when thickness of the matrix reached 10 mm, 5. The temperature rise of the resin did not decreased when Polypropylene vacuum-formed template was used as the matrix. 6, The temperature of the resin increased as the thickness of the dentin decreased.