• 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.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.27-34
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• 2004

In the injection molding of plastic optical lenses, the molding conditions have critical effects on the quality of the molded lenses. Since there are many molding parameters involved in injection molding process, determination of the molding conditions for lens molding is very important in order to precisely control the surface contours of an optical lens. Therefore this paper presents the application of neural network in suggesting the optimized molding conditions for improving the quality of molded parts based on data of FE Analysis carried out through CAE software, Timon-3D. Suggested model in this paper, which serves to learn from the data of FE Analysis and induce the values for optimized molding conditions. has been implemented for searching the molding conditions without void and with minimized thickness shrinkage at lens center of injection molding optical lens. As the result of this study. we have confirmed that void creation at the inside of lens is primarily determined by mold temperature and thickness shrinkage at center of lens is primarily determined by the parameters such as holding pressure and mold temperature.

• Elastomers and Composites
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• v.52 no.4
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• pp.317-325
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• 2017

Molding conditions can be described as factors that determine the quality of a product obtained from injection molding. Many studies have been performed on the injection molding pressure, injection temperature, packing pressure and other molding conditions related to part quality. However, the most accessible factor among the adjustable molding conditions during actual injection is the injection speed. In this study, we simulated the variation of the physical quantity according to injection speed and performed experiments to understand the effect of injection speed on the actual product. A CAE analysis program (Moldflow) was used to simulate and analyze the results using PC and PBT for two models. In order to compare these results with the experimental results, an actual injection molding was performed for each injection speed, and the correlation between simulation and injection molding, especially for the shrinkage of the molded article, was discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1619-1625
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• 2011

The objective of this study determine the molding conditions of a double-shot injection mold for fabricating a computer mouse using different materials, by performing three-dimensional injection molding analysis. In order to select the optical injection molding conditions, the effects of the injection time, the maximum injection pressure, the effect of packing time on the injection molding characteristics, and the product qualities were quantitatively examined. From the results of the injection molding analysis, the optimal injection molding conditions of the double-shot injection mold, which leads the molded product to the minimized shrinkage and deflection, were estimated. The results of the injection molding experiments, showed that an appropriate computer mouse can be fabricated using different materials when the identified optimal injection molding conditions are adopted.

• 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 Machine Tool Engineers Conference
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• 2005.05a
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• pp.109-114
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• 2005

The large injection molded parts technology such as instrument panel, front and rear bumper are presented for a precision molding. Some lead time and cost are required to product these part from design to mass product. Recently, CAE is widely used in product design, mold design and analysis of molding conditions to reduce time and cost. The optimal molding conditions can be obtained by DOE(Design of Experiment). The optimal design applications with CAE and DOE have been used in small molded parts. However, application to the large molded body is not reported. In this paper, optimization of injection molding process is studied for quality control in mass production of automobile bumper. Mold temperature difference is chosen through robust design of injection molding process, the molding process being optimized in term of shrinkage and deflection. The optimal conditions through DOE are validated by using injection molding analysis.

• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.5 no.4
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• pp.46-52
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• 2006

From the past, most of the studies about thermoplastic elastomers(TPEs) have been conducted for theirs compounded materials and morphology. However these studies do not directly affect on injection molding processing. Therefor this study is focus on the variation of mechanical properties on TPEs moldings by increasing injection molding conditions which included injection molding conditions include injection pressure, holding pressure, melt temperature, mold temperature. The used experimental TPEs is a group of styrene(TPS). Injection pressure slightly affected on tensile strength, shrinkage and hardness. Holding pressure only affected on hardness. The melt temperature was the most affective condition on tensile strength.

• Design & Manufacturing
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• v.2 no.2
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• pp.33-37
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• 2008

This paper describes the optimization of injection molding conditions to minimize sink marks. Sink marks, which refer to a small depression on the surface opposite a thick wall thickness, are often encounted in injection molded plastic parts. Part geometry, material properties and processing conditions during injection molding can affect the sink mark depth. We designed the runner system which is possible balanced filling to cavities using CAE program and then obtained optimal processing conditions by Taguchi's Robust Design technique. By actual injection molding using optimized mold and molding conditions, it confirmed that sink mark depth decreased zero compared to 1mm level in the conventional mold and process.