• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.21-28
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• 2007

Injection molding process factors such as molding temperature, injection pressure, flow rate and flow velocity, must be controlled properly in filling and packing phases in the injection molding process. In this study, effects of these factors on the injection molding were investigated through the flow analysis for birefringence and refractive index for pickup lens. This paper presents the birefringence and refractive index reduced with increasing the holding pressure and also the holding pressure time. And there are interaction with birefringence and fill time in the injection process. The optimal conditions through DOE are validated by using injection molding analysis.

• Journal of the Korean Ceramic Society
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• v.32 no.5
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• pp.559-566
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• 1995

Alumina powder was coated with stearic acid and then mixed with isotactic polypropylene, atactic polypropylene as binders at 15$0^{\circ}C$ for 2 hours. The mixture was then injection molded at various mold temperatures using injection molding machine to investigate the effect of the molding temperature and debinding parameters on the formation of the defects. The molded specimens were debinded in both air and nitrogen atmospheres. Wicking and solvent methods were also used to enhance debinding efficiency. The specimens were prefired at 120$0^{\circ}C$ and then sintered at 150$0^{\circ}C$ for 3 hours. Various defects were formed at mold temoperature of 3$0^{\circ}C$, 6$0^{\circ}C$ and 10$0^{\circ}C$ and any noticeable defect was not formed at 85$^{\circ}C$. The density of green body increased with mold temperature. Debinding in air atmosphere was more effective than in nitrogen atmosphere. Results also proved that wicking and solvent treatments helped minimize the number of defects.

• Transactions of Materials Processing
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• v.14 no.6 s.78
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• pp.491-495
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• 2005

Micro injection molding analysis for microneedle fabrication was performed in the present study. The dimensions of width and thickness for in-plane microneedle are $600{\mu}m$, $500{\mu}m$, respectively. A delivery system based on guidelines for traditional injection molding was designed for four-cavities molding system. To investigate the effects of processing conditions in the mirconeedle fabrication, injection molding analysis using commercial code was performed. It was shown that the total injection time has a significant effect on the fabrication of in-plane microneedles.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.55-59
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• 2005

Micro injection molding analysis for microneedle fabrication was performed in the present study. The dimensions of width and thickness for microneedle are 600um, 500um, respectively. A delivery system based on guidelines for traditional injection molding was designed for four-cavities molding system. To investigate the effects of processing conditions in the mirconeedle fabrication, injection molding analysis using commercial code was performed. It was shown that the total injection time has a significant effect on the fabrication of microneedles.

• Design & Manufacturing
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• v.17 no.3
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• pp.1-7
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• 2023

Blow molding is a manufacturing process in which thermoplastic preforms are preheated and then pneumatically expanded within a mold to produce hollow products of various shapes. The two-step process, a type of blow molding method, requires the output of multiple infrared lamps to be adjusted individually, so the process of finding initial conditions hinders productivity. In this study, digital twin technology was applied to solve this problem. A blow molding simulation technique was established and simulation-based metadata was generated. A response surface ROM (Reduced Order Model) was built using the generated metadata. Then, a dynamic ROM was constructed using the results of 3D heat transfer analysis. Through this, users can quickly check the product wall thickness uniformity according to changes in the control value of the heating lamp for products of various shapes, and at the same time, check the temperature distribution of the preform in real time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2543-2551
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• 2000

Precision injection molding is an important technology for improving productivity and lowering costs in the fields of medical components, lenses and electrical connectors. The quality of injection molded parts is affected by various processing conditions such as filling time and packing pressure profile. It is difficult to consider all the variables at the same time for prediction of the quality. In this study, the genetic algorithm was used to obtain the optimal processing conditions for minimizing the volumetric shrinkage of molded parts. For a higher convergence rate, the method of design of experiments was used to analyze the relationship between processing conditions and volumetric shrinkage of molded parts, which served as analysis tool for the capability of searching optimal processing conditions but also greatly reduces the calculation time by utilizing the information of searching area. As a practical example, compact disks that require micron-level precision were chosen for the study.

• Transactions of Materials Processing
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• v.29 no.4
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Transactions of Materials Processing
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• v.14 no.4 s.76
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• pp.368-374
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• 2005

In the present study we used a diagrammatic analysis of 6 sigma quality control and Taguchi method for injection molding of monitor back-cover, evaluated the influence on the cycle time with part design, mold design, molding process and standardization activity involving design and molding, adopted analysis of sensitivity and effective factors of the part design and molding process conditions for productivity, identified main design molding factors. The contributing factors for the final cycle time could be enumerated as follows; the thickness of hot spot, main nominal part thickness, coolant inlet temperature, melt temperature and cooling line layout, etc.. As a first step, all the critical factors of design process applied to the current monitor housing were investigated through 6 sigma process. Thereafter, the optimal and better critical factors found in the first step were applied to new product design to prove that our process was correct. The Moldflow was used for injection molding simulation, and Minitab software for the statistical analysis, respectively. Finally, the productivity of new design was increased about 33 percents for our specific case.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.05a
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• pp.269-272
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• 2004

The present study used a diagrammatic analysis of 6 sigma quality control and Taguchi method for injection molding process of monitor back-cover, evaluated the influence on the cycle time with part design, mold design, molding process and standardization activity involving design & molding, adopted analysis of sensitivity and effective factors of the part design and molding process conditions for productivity, identified main design molding factors, as critical ones influencing on the quality and productivity, of which is summarized as design guidance. The main contribution factors for cycle time can be sequentially enumerated as follows; hot spot, part thickness, coolant inlet temperature, melt temperature cooling line layout, etc.. As a first step critical factors of the design process of current monitor housing were investigated. And the optimal and better critical factors found in the first step were applied to a new product proving our process was correct. Moldflow software was used for injection molding simulation, and Minitab software for the statistical analysis. Finally, the productivity was increased by about 33 percents for our specific case.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.1-6
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• 2010

This study presents the preform injection molding and the blow molding of the injection stretch-blow molding process for PET bottles. The numerical analysis of the injection molding and the blow molding of a preform is considered in this paper using CAE with a view to minimize the warpage and the thickness. In order to determine the design parameters and processing conditions in injection/blow molding, it is very important to establish the numerical model with physical phenomenon. In this study, a three dimensional model has been introduced for the purpose and flow simulations of filling, post-filling and cooling process are carried out. The simulations resulted in the warpage in good agreement with the measurements. Also, from the result of numerical analysis, we appropriately predicted the warpage, deformation and thickness distribution along the product walls.