• 대한기계학회논문집A
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• 제26권12호
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• pp.2550-2555
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• 2002

Hybrid composites usually are defined as composites having different types of reinforcements such as fibers and particles. The major advantage of hybrid composites is able to control the material properties such as optical, electrical, and mechanical properties. For this reason, hybrid composites are widely used in automotive, marine, household, and electrical industries. The objective of this work was to investigate processing characteristics in the compression molding of hybrid thermoplastic composites. The mechanical properties of composites manufactured in various forming conditions were monitored. The composites contained randomly oriented long carbon fiber and carbon black in polypropylene(PP) matrix were used. The carbon fiber contents of composites were 5%, 10%, 15%, and 20%, and carbon black contents were 5%, 10%, 15%, 20%, and 25% by weight. Compression molding was conducted at various mold temperatures. Crstallinity was also measured by using X-RD. The tensile modulus of the composites increased with increasing the mold temperature. However, the impact strength of the composites decreased as the mold temperature increased.

• 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.

• Design & Manufacturing
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• 제14권1호
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• pp.15-21
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• 2020

Smart systems in different application areas such as automotive, medical and consumer electronics require a novel manufacturing method of electronic, optical and mechanical functions into products. Traditional methods including mechanical assembly, bonding of plastic and electronic circuit cause the problems in large size of products and complicated manufacturing processes. In this study, thermoforming and film insert molding were applied to fabricate a dome shaped plastic part embedded with electronic circuits. The deformation of patterns printed on PET film was predicted by thermoforming simulation using T-SIM, and the results were compared with those by experiment. In order to decrease spring-back after thermoforming, the Taguchi method of design of experiment was used. Through ANOVA analysis, it was found that mold temperature was the most dominant parameter for spring-back. By using flow analysis, gate design was performed to decrease injection pressure. During film insert molding, the wash-out of ink printed on film occurred for Polycarbonate. When the resin was changed to PMMA, the wash-out disappeared due to low melt temperature.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2000년도 추계학술대회 논문집
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• pp.171-177
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• 2000

It is essential to understand the creep behavior, which shows how long the characteristics of material maintains because press joined molding GMT-Sheet for recycle is usually used in the severe environment. In this study, we predict joining strength of GMT-Sheet for recycle, when lap length was changed. and we will investigate how compression ratio have an effect on creep behavior in press joined molding. The result of experiment of forming condition concerned with joining problem of GMT-Sheet is as followings joining efficiency. of GMT-Sheet, increases as lap joint length I, increases. Increase of compression ratio causes decrease o f joining efficiency after of GMT-Sheet joining. As the result of creep test, GMT-Sheet is easily damaged in high temperature range, because it is sensitive to the temperature

• 한국분말재료학회지
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• 제21권6호
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• pp.407-414
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• 2014

The powder injection molding process having advantages in manufacturing three-dimensional precision parts essentially requires a debinding process before sintering to remove the binders used for preparing feedstock. In this study, powder injection molding of translucent alumina was performed, and carbon dioxide ($CO_2$) is used as a supercritical fluid that makes it possible to remove a large amount of binder, which is paraffin wax. The relationship between the optical property of translucent alumina and the debinding condition (temperature and pressure) of supercritical $CO_2$ was investigated. As temperature and pressure increased, extraction rate of the binder showed rising tendency and average grain size after sintering process was relatively fine. On the other hand, optical transmittance was reduced. As a result, the debinding condition at $50^{\circ}C$ and 20 MPa that represents the lowest extraction rate, $8.19{\times}10^{-3}m^2/sec$, corresponds to the largest grain size of $14.7{\mu}m$ and the highest optical transmittance of 45.2%.

• Design & Manufacturing
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• 제13권3호
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• pp.53-58
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• 2019

This paper presents Artificial Neural Network(ANN) method to predict maximum injection pressure of injection molding machine and weights of injection molding products. 5 hidden layers with 10 neurons is used in the ANN. The ANN was conducted with 5 Input parameters and 2 response data. The input parameters, i.e., melt temperature, mold temperature, fill time, packing pressure, and packing time were selected. The combination of the orthogonal array L27 data set and 23 randomly generated data set were applied in order to train and test for ANN. According to the experimental result, error of the ANN for weights was $0.49{\pm}0.23%$. In case of maximum injection pressure, error of the ANN was $1.40{\pm}1.19%$. This value showed that ANN can be successfully predict the injection pressure and the weights of injection molding products.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2005년도 추계학술대회 논문집
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• pp.83-86
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• 2005

In this study, SAM (self-assembled monolayer) was applied as an anti-adhesion layer in the nano molding process, to reduce the surface energy between the nano-stamper and the moldeded polymeric nano patterns. Before depositing SAM on the stamper, the nickel stamper was pretreated to remove oxide on the nickel stamper surface. Then, using the solution deposition method, alkanethiol SAM as an anti-adhesion layer was deposited on nickel surface. To examine the effectiveness of the SAM deposition on the metallic nano stamper, the contact angle and the lateral friction force were measured at the actual processing temperature and pressure for the case of nano compression molding and at the actual UV dose for the case of nano UV molding. The surface energy due to SAM deposition on the nickel nano stamper markedly decreased and the high hydrophobic quality of SAM on the nickel stamper maintained under the actual molding environments.

• 한국정밀공학회지
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• 제18권12호
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• pp.60-65
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• 2001

To simulate the real molding conditions, the effects of phase change and compressibility of the resin were considered in the present investigation. A modified Cross model with either an Arrhenius-type or WLF-type functional form was used for modeling viscosity of the resin. A double-domain Tait equation of state was employed to describe the compressibility of the resin during molding. The energy balance equation including latent-heat dissipation fur semi-crystalline materials was solved in order to predict the solidified layer and temperature profile. Injection molding experiments were carried out using polypropylene(PP) in the present study. Based on the comparison between experiments and simulations, it was found out the predicted pressure distributions and melt front propagations were accurate. Thus it was concluded that the program developed in this study was proved to be useful in simulations of injection molding process.

• Elastomers and Composites
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• 제56권3호
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• pp.164-171
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• 2021

Due to the problem of environmental pollution by plastics, it is necessary to decrease their consumption. In the case of PET bottles, it is essential to reduce the thickness of the bottle for the reduction of plastic used. For manufacturing PET bottles with reduced thickness, it is a prerequisite to design a preform with reduced thickness and study its molding capability. In this study, the injection molding capability was investigated after reducing the body thickness of the preform to 15% and 20%, respectively, for the two preform models currently in use. Injection molding analysis was performed on the existing models and on the models for reduced weight, under the molding conditions of the existing models. Using the computed results, temperature distribution, pressure distribution, deformation and clamping force were compared. Based on the analysis, the injection conditions of the preform model with less thickness were discussed.

• 한국염색가공학회지
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• 제28권4호
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• pp.239-245
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• 2016

In this study, carbon/phenol composites were prepared from carbon fiber preform and phenol resin by RTM(resin transfer molding) process. And changes in the properties of the composite according to the pre-treatment of phenol resin was mainly studied. RTM process conditions were deduced from viscosity and thermal analysis of phenol resin which were rheometer and thermogravimetric analyzer(TGA). RTM process was performed under various injection and molding temperature. Characterization of the prepared C/P composites were evaluated by various analysis. Morphology of composites was analyzed by Micro-CT(MCT), Mechanical properties of composites were measured through the flexural properties. As results, volatile impurities of phenol resin were effectively removed at resin pre-treatment temperature of $100^{\circ}C$ and composite was sufficiently cured at molding temperature of $180^{\circ}C$.