• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2005년도 금형가공,미세가공,플라스틱가공 공동 심포지엄
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• pp.126-131
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• 2005

In the present study, warpage characteristics of mobile phone cover through injection molding process were investigated by using design of experiments. Warpage in plastic injection molding process has a significant effect on quality of product. Effects of injection time, packing pressure, packing time, mold temperature ana melt temperature on warpage of mobile phone cover were considered by CAE analysis and experiment with Taguchi method. The degree of warpage for the injection molded product was measured by using three dimensional CMM. It was shown that temperature parameter has more significant effect on the warpage of mobile phone cover than pressure parameter.

• Current Applied Physics
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• 제18권11호
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• pp.1451-1457
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• 2018

Injection compression molding (ICM) is an advantageous processing method for producing thin and large polymeric parts in a robust manner. In the current study, we employed the ICM process for an energy-related application, i.e., thin and large polymeric battery case. A mold for manufacturing the battery case was fabricated using injection molding. The filling behavior of molten polymer in the mold cavity was investigated experimentally. To provide an in-depth understanding of the ICM process, ICM and normal injection molding processes were compared numerically. It was found that the ICM had a relatively low filling pressure, which resulted in reduced shrinkage and warpage of the final products. Effect of the parting line gap on the ICM characteristics, such as filling pressure, clamping force, filling time, volumetric shrinkage, and warpage, was analyzed via numerical simulation. The smaller gap in the ICM parting line led to the better dimensional stability in the finished product. The ICM sample using a 0.1 mm gap showed a 76% reduction in the dimensional deflection compared with the normal injection molded part.

• 한국정밀공학회지
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• 제13권9호
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• pp.130-137
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• 1996

In the present paper the effect of various process conditions on the final weight of injection molded rectangular plates has been investigated in detail. The main parameters involved in the simulations were melt temperature, mold temperature, injection speed and packing pressure. The dimensions of the plate used were 100mm long, 2mm of width and polystyrene was used as a molding material. The shear viscosity of the polymeric material was treated as a function of shear rate, temperature and pressure through the whole processes including packing and cooling stages. By increasing a packing pressure the final weight of sample increased linearly. Furthermore, as the melt temperature, the mold temperature and the injection speed increased, the final weight of the injection molded plate decreased within the molding window.

• 대한기계학회논문집
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• 제15권6호
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• pp.1933-1947
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• 1991

본 연구에서는 특징형상기반 CAD 시스템의 기계가공을 고려한 기하학적 모델 링 기능과 부형상의 합성과 해석을 위한 사출성형에 관한 광범위한 지식을 연계, 종합 한 형태의 지식형 CAD 시스템을 제안하였다.

• 한국자동차공학회논문집
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• 제20권1호
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• pp.124-130
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• 2012

An injection mold cooling circuit for an automotive front bumper was optimally designed in order to simultaneously minimize the average of the standard deviations of the temperature and the difference in mean temperatures of the upper and lower molds for uniform cooling. The temperature distribution for a specified design was evaluated by Moldflow Insight 2010, a commercial injection molding analysis tool. For efficient design, PIAnO (Process Integration, Automation and Optimization), a commercial PIDO tool, was used to integrate and automate injection molding analysis procedure. The weighted-sum method was used to handle the multi-objective optimization problem and PQRSM, a function-based sequential approximate optimizer equipped in PIAnO, to handle numerically noisy responses with respect to the variation of design variables. The optimal average of the standard deviations and difference in mean temperatures were found to be reduced by 9.2% and 56.52%, respectively, compared to the initial ones.

• Korea-Australia Rheology Journal
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• 제21권1호
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• pp.17-25
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• 2009

We studied the flow characteristics of the polymer melt in the injection molding process with ultrasonic vibration by using the numerical analysis. To minimize the error between the experimental data and numerical result, we presented a methodology using the design of experiments and the response surface method for reverse engineering. This methodology can be applied to various fields to obtain a valid and accurate numerical analysis. Ultrasonic vibration is generally applied between an extruder and the entrance of a mold for improvement the flow rate in injection molding. In comparison with the general ultrasonic process, the mode shape of the mold must be also considered when the ultrasonic vibration is applied on the mold. The mode shape is defined as the periodic and spatial deformation of the structure owing to the effect of the vibration, and it varies greatly according to vibration conditions such as the forcing frequency. Therefore, we considered new index and found the forcing frequency for obtaining the highest flow rate within the range from 20 to 60 kHz on the basis of the index. Ultimately, we presented the methodology for not only obtaining a valid and accurate numerical analysis, but also for finding the forcing frequency to obtain the highest flow rate in injection molding using ultrasonic vibration.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.97-100
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• 1997

In order to predict the moldability of a injection molded part, a simulation of filling is needed. Especially when short shot is predicted by CAE simulation in the filling stage, there are mainly three ways to solve the problem. Modification of gate and runner, replacement of plastic resin, and adjustment of process conditions are the main ways. Among them, adjustment of process conditions is the most economic way in the cost and time since the mold doesn\\`t need t be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, a fuzzy neural network(FNN) based upon injection molding process is proposed to evaluate moldability in filling stage and also to solve the problem in case of short shot. An adequate mold temperature is generated through the fuzzy neural network where fill time and melt temperature are taken into considerations because process conditions affect each other.

• 소성∙가공
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• 제16권8호
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• pp.596-602
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• 2007

LGP (Light Guiding Plate) of LCD-BLU (Liquid Crystal Display - Back Light Unit) is one of the major components that affect the product quality of LCD. The optical patterns of LGP(2.2") molds are fabricated by three different methods, namely, (1) laser ablation, (2) chemical etching and (3) LiGA-reflow, respectively. The characteristics of surface patterns and roughnesses of molds and injection molded parts were compared to evaluate the optical characteristics. The optical patterns of injection molded LGP with mold fabricated by LiGA - reflow method showed the best geometric structure. The surface roughness (Ra) of LGP#s with molds fabricated by (1) laser ablation: $Ra={\sim}31nm$, (2) chemical etching: $Ra={\sim}22nm$, and (3) LiGA-reflow: $Ra={\sim}4nm$.

• Design & Manufacturing
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• 제2권4호
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• pp.37-43
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• 2008

Supplementary features in injection molded products, which are boss, rib and snap fit, are mainly located in the products. These features might make molding flow improper in injection processing and consequently give rise to some of molding troubles such as short shot and hesitation. The sink mark on boss parts is generated by the volumetric shrinkage that is caused by both the molding thickness and the closed boss height. The volumetric shrinkage is affected by packing pressure and its amount tends to decrease by increasing the packing pressure. The packing pressure can therefore increase flow rate to a boss part and causes the sink mark depth to increase. As the molding thickness and the closed boss height in the boss part can increase the part volume, these may yield bad solidifying and also extend the molding cycle. In this paper, both the injection molding test and the flow analysis were carried out to investigate the effect of sink marks generated in the boss part of injection molded products.

• Design & Manufacturing
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• 제14권3호
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• pp.1-7
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• 2020

This paper predicts the mass and the length of injection-molded products through the Artificial Neural Network (ANN) method. The ANN was implemented with 5 input parameters and 2 output parameters(mass, length). The input parameters, such as injection time, melt temperature, mold temperature, packing pressure and packing time were selected. 44 experiments that are based on the mixed sampling method were performed to generate training data for the ANN model. The generated training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. A random search method was used to find the optimized hyper-parameter of the ANN model. After the ANN completed the training, the ANN model predicted the mass and the length of the injection-molded product. According to the result, average error of the ANN for mass was 0.3 %. In the case of length, the average deviation of ANN was 0.043 mm.