• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.5
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• pp.556-561
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• 2007

The rapid thermal response(RTR) molding is a novel process developed to raise the temperature of mold surface rapidly in the injection stage and then cool rapidly to the ejection temperature by air or water. The objectives of this paper are to investigate the effect of mold temperature, pressure and thickness of micro pattern molding and to provide a optimization of RTR injection molding for micro pattern from Moldflow simulation. Optimal minimum temperature and pressure was found without shortcut according to thickness. Filling percentage was influenced by glass transition temperature with the kinds of resin. Optimal temperature is slightly higher than glass transition temperature irrespectively of pressure, thickness, the kinds of resin in the micro pattern molding.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.465-469
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• 2001

In injection molding short shot is one of the frequent and fatal defects. Experts of Injection molding usually adjust process conditions such as injection time, mold temperature, and melt temperature because it is most economic way in time and cost. However, it is difficult task to find appropriate process conditions for troubleshooting of short shot as injection molding process is a highly nonlinear system and process conditions are coupled. In this paper, a modular fuzzy neural network (MFNN) has been applied to injection molding process to shorten troubleshooting time of short shot. Based on melt temperature and fill time, a reasonable initial mo이 temperature is recommenced by the NFNN, and then the mold temperature is inputted to injection molding process. Depending on injection molding result, specifically the insufficient quantity of an injection molded part. and appropriate mold temperature is recommend repeatedly through the NFNN.

• Design & Manufacturing
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• v.2 no.5
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• pp.30-33
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• 2008

Injection Molding is the most effective process for mass production of plastic parts. The injection molding process is composed with several steps such as Filling, Packing, Holding, Cooling, Ejecting. Among them, filling and packing process should be considered carefully to improve accuracy of dimension, surface quality of plastic parts. Usually the quality above-mentioned is managed with weight of part after molding on the field. In this paper, a series of experiment for molding automotive front bumper was conducted with cavitity temperature sensor to optimize switch-over time(V-P switching), hot runner vale gate sequence time during filling and packing step for the purpose of uniform quality, weight at every molding. As a result, it was found that it is effective method to use temperature sensor in injection molding for quality control of plastic molding.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.768-773
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• 2003

Injection molding has been widely used for the mass production of a plastic product. With the development of the relative technique, various injection molding techniques have been developed and we could get more precise plastic product. The temperature of a melting resin is an important factor in the injection molding and this temperature has direct influence on the quality of a plastic product. In the present injection molding machine, the deriation of a temperature controlled by PID control method is within 2$^{\circ}C$ in the injection molding machine but PID control method takes too much time to stabilize after preheating and its overshoot is so big. We applied fuzzy control to alleriate the problem. In this research, we experimented the fuzzy temperature control with the usage of PC based PLC.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.09a
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• pp.9-12
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• 2005

The rapid thermal response (RTR) molding is a novel process developed to raise the temperature of mold surface rapidly to the polymer melt temperature prior to the injection stage and then cool rapidly to the ejection temperature. The resulting filling process is achieved inside a hot mold cavity by prohibiting formation of frozen layer so as to enable thin wall injection molding without filing difficulty. The present work covers flow simulation of thin wall injection molding using the RTR molding process. In order to take into account the effects of thermal boundary conditions of the RTR mold, coupled analysis with transient heat transfer simulation is suggested and compared with conventional isothermal analysis. The proposed coupled simulation approach based on solid elements provides reliable thin wall flow estimation fur both the conventional molding and the RTR molding processes

• Transactions of Materials Processing
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• v.15 no.1 s.82
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• pp.15-20
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• 2006

The rapid thermal response (RTR) molding is a novel process developed to raise the temperature of mold surface rapidly to the polymer melt temperature prior to the injection stage and then cool rapidly to the ejection temperature. The resulting filling process is achieved inside a hot mold cavity by prohibiting formation of frozen layer so as to enable thin wall injection molding without filling difficulty. The present work covers flow simulation of thin wall injection molding using the RTR molding process. In order to take into account the effects of thermal boundary conditions of the RTR mold, coupled analysis with transient heat transfer simulation is suggested and compared with conventional isothermal analysis. The proposed coupled simulation approach based on solid elements provides reliable thin wall flow estimation for both the conventional molding and the RTR molding processes.

• Journal of the Korean Society of Food Science and Nutrition
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• v.30 no.2
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• pp.250-255
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• 2001

Effect of molding temperature on the quality changes of extruded meju was studied. Meju was molded at 8$0^{\circ}C$, 6$0^{\circ}C$ and 4$0^{\circ}C$, and then stored at $25^{\circ}C$ with 50% of relative humidity for 30 days. The texture of the cooked soybean grain showed that the firmness and cohesiveness were increased, and consistency was decreased by decrease of molding temperature. The density of the meju molded at 8$0^{\circ}C$, 6$0^{\circ}C$ and 4$0^{\circ}C$ were 1.072g/mL, 1.079g/mL and 1.203g/mL, respectively. The meju molded at 4$0^{\circ}C$ had significantly higher density than those molded at 8$0^{\circ}C$ or 6$0^{\circ}C$. Also, delay of water evaporation, acidification, and rapid growth of fungal mycellium were observed on the sample with molding temperature at 4$0^{\circ}C$ during fermentation. Activity of amylase and protease, contents of total reducing sugar and amino nitrogen of 4$0^{\circ}C$-molded meju were represented lower level than those of 6$0^{\circ}C$ or 8$0^{\circ}C$-molded sample. Therefore, it was considered that the molding temperature was an important factor for meju fermentation and molding temperature of 6$0^{\circ}C$ or over would be acceptable.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.105-112
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• 2017

In this study, plastics were deformed after molding due to the characteristics of the material. The Taguchi experimental design method was utilized to find the molding conditions that minimized deformation of the plastic bezel to be assembled in an automotive steering wheel. The injection molding conditions applied to the experimental design method are the melt temperature, cavity plate coolant temperature, core plate coolant temperature, and cooling time. Each condition was divided into five levels, and a total of 25 experiments were planned. However, instead of performing 25 actual molding experiments, the injection molding analysis was performed using the Moldflow program, and the deformation values for each molding analysis were obtained. The optimal molding conditions were obtained from these deformation values. The actual injection molding experiment using optimal molding conditions was compared with the deformation amount of the current molded product. The deformation was measured using a precise 3D scanner. The deformation amount of the molded product under optimal molding conditions was 16.1% lower than the deformation amount of the current molded product.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1609-1612
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• 2005

The effects of injection molding conditions on the uniformity and brightness of light guide plate(LGP) with micro-patterns were investigated in the present study. An injection molding system for stampers with mirco-pattern was designed and manufactured to perform experiment. Variations of injection molding speed, mold and melt temperature for LGP were considered in this work. Also, injection molding characteristics of LGP were investigated by numerical analysis using plastic injection molding commercial code. It was shown that injection molding conditions such as injection speed, melt temperature and mold temperature can have an effect on the uniformity and brightness of light guide plate.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.83-86
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• 2001

In injection molding, short shot is one of the frequent and fatal defects. Experts of injection molding usually adjust process conditions such as injection time, mold temperature, and melt temperature because it is the most economic way in time and cost. However it is a difficult task to find appropriate process conditions for troubleshooting of short shot as injection molding process is a highly nonlinear system and process conditions are coupled. In this paper, a fuzzy neural network(FNN) has been applied to injection molding process to shorten troubleshooting time of short shot. Based on melt temperature and fill time, a reasonable initial mold temperature is recommended by the FNN, and then the mold temperature is inputted to injection molding process. Depending on injection molding result, specifically the insufficient quantity of an injection molded part, an appropriate mold temperature is recommend repeatedly through the FNN.