• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.1-7
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• 2006

Injection molding is a very important industrial process for the manufacturing of plastics objects. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of weld-line in injection-molded products is assessed. And the effects of fiber content and injection mold-gate conditions on the fiber orientation are also discussed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.4
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• pp.50-55
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• 2014

Currently, flat cover glasses are widely applied to mobile devices. However, for a good design and for convenience of use, curved cover glasses are in demand. Thus, many companies are attempting to produce curved cover glasses using a shaving technique, but the production efficiency is very low. Therefore, a molding technique has been adopted to increase the efficiency of curved glass production systems. For a glass molding system, a uniform temperature distribution of the mold is crucial to produce high-quality curved cover glasses. Before setting the heating conditions of the molding system for a uniform temperature distribution by a thermal analysis, verification is required. Therefore, in this study, temperature measurements were conducted for a prototype molding system and the experimental results were compared with simulation computations. The temperatures of the heating block surface were in good agreement with the computational results for transient and steady conditions.

• Elastomers and Composites
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• v.55 no.2
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• pp.120-127
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• 2020

In this study, molding shrinkage of PPS resin was investigated. Two types of PPS resins with differing glass fiber and calcium carbonate content were used for this purpose. To observe mold shrinkage, molding conditions based on injection temperature, injection speed, and the position of the cushion were selected. Circular and rectangular specimens were used for the study model. Injection molding simulation was performed to predict the filling pattern and mold shrinkage, and the simulation results were compared with the experimental conclusions. It was observed that the mold shrinkage showed the highest shrinkage (distributed from 0.05% to 0.32%) dependence on the injection temperature, and the lowest shrinkage (distributed from 0.05% to 0.31%) dependence on the injection speed. The role of the position of the cushion in mold shrinkage was difficult to observe. The results of the simulation mostly agreed with the experimental results; however, for some molding conditions, the mold shrinkage in the simulation was overestimated as compared to that in the experiment.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.469-470
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• 2006

The purpose of this research was to investigate and to find out the optimal annealing condition to mold an aspheric glass to be used for mobile phone module having 2 megapixel and $2.5{\times}$ zoom. Taking annealing rate and re-press temperature after molding as molding variables under the identical molding temperature and pressure, a glass lens was molded. And, Form Accuracy, Lens Thickness, Refractive Index, and Modulation Transfer Function(MTF) were measured in order to observe characteristics of molded lens, and then optimal annealing conditions were determined based on the resulting data. Properties of lens molded under the optimal conditions revealed Form Accuracy[PV] $0.2047\;{\mu}m$ in aspheric surface, and $0.2229\;{\mu}m$ in plane, and MTF value was 30.3 % under 80 lp/mm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.946-949
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• 2005

It is very a time-consuming and error-prone process to obtain the optimal injection condition, which can produce good injection molding products in some operational variation of facilities, from a seed injection condition. This study proposes a new approach to search the optimal injection molding condition using a neural network and a genetic algorithm. To estimate the defect type of unknown injection conditions, this study forces the neural network into learning iteratively from the injection molding conditions collected. Major two parameters of the injection molding condition - injection pressure and velocity are encoded in a binary value to apply to the genetic algorithm. The optimal injection condition is obtained through the selection, cross-over, and mutation process of the genetic algorithm. Finally, this study compares the optimal injection condition searched using the proposed approach. with the other ones obtained by heuristic algorithms and design of experiment technique. The comparison result shows the usability of the approach proposed.

• Elastomers and Composites
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• v.56 no.3
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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.

• Transactions of Materials Processing
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• v.6 no.6
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• pp.489-499
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• 1997

The injection molding process is analyzed to get the information on the mold design parameters and the optimum process conditions for automotive plastic front fender. The gate position, runner size and cooling channel are determined by the estimation of the flow balance, packing time, uniform cooling and shrinkage and warpage in the injection molding analyses. The procedure can be used in the mold design in the early stage when developing plastic parts.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.51-56
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• 2006

A computer code was developed to simulate both the thermal stresses introduced during the post-filling stage and the in-plane deformation after ejection process by finite element method based on the plane stress theory. The computer simulation was applied to the mold design of a 2 inch light guide plate (LGP) for thin film transistor (TFT)-liquid crystal displays (LCD). With injection molding experiments based on the design of experiments (DOE) technique, the influences of the processing conditions in injection molding on brightness and uniformity of the LGP were investigated, and the optimal processing parameters were selected to increase the brightness and uniformity. The verification experiment showed that the brightness and uniformity of the LGP were increased dramatically under the selected optimal processing conditions.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.83-88
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• 2002

In order to predict the moldability of a injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to 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, the intelligent CAE system synergistically combines fuzzy-neural network (FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the experts' conventional methodology which is similar to the golden section search algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.581-592
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• 2000

To obtain an excellent product and decide on optimum molding conditions, it is important to establish the relationship between molding conditions and viscosity. The composites is treated as a pseudoplastic fluid, and the expansional/contractional viscosity of the fiber-reinforced polymeric composites is measured using the parallel plastometer, and the model for flow state has been simulated with the viscosity. The effects of expansional slip parameter $\alpha_{e}$, and expansional/contractional viscosity ratio ${\mu}_{\gamma}$, on the mold filling parameters are also discussed.