• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.159-173
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• 2002

The goal of this research is to develop of an intelligent injection mold process planning system using Case-Based Reasoning. Injection mold process planning is the planning of manufacturing process to produce an injection mold economically and efficiently. Automation of the process planning is required because the problems of handmade scheduling, the difficulty of training experts for process planning, the lack of domain experts, the spread of CAD/CAM system and flexible manufacturing. This research uses Case-Based Reasoning because the injection mold process planning is devised variously and complicatedly, but the process planning of similar injection molds is very similar to each other. The system that is developed by this research uses cases that are collected in a case base when planning the process of new injection mold. New injection mold process planning is devised by retrieving a case that was made from the most similar injection mold. This research presented and composed the cases of injection mold process planning, and devised a method of search and adaptation, and developed an intelligent injection mold process planning system with the experimental results.

• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.5
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• pp.94-101
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• 2013

Injection molding process is one of the most important methods to produce plastic parts with high efficiency and low cost. The objective of this study is to implement the best plastic injection molding process for LED TV speaker frame. Moldflow analysis and simulation of plastic injection molding process were carried out in order to predict optimal modeling operation conditions and then injection molded part was produced various type of resin temperature, filling time and injection pressure variation. the result was that the best injection molding condition is set as 60bar pressure, 2sec filling time and $310^{\circ}C$ degree. The study result would be useful to variety of plastic injection molding process.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.144-150
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• 2005

Gas-assisted injection molding (GAIM) process is reducing the injection pressure during mold filling required as well as the shrinkage and warpage of the part and cycle time. Despite of these advantages, this process introduces new parameters and makes the application more difficult because the process interacts between gas and melt during injection molding process. Important GAIM factors that involved in this process include gas penetration design, locations of gas injection points, shot size, gas injection delay time as well as common injection molding parameters, gas pressure and gas injection time. In this study, the experiments were conducted to investigate effects of GAIM process variables on the gas penetration for PP and ABS moldings by changing gas injection point. Taguchi method was used fer the design of experiment. When the gas was injected at cavity's center, the most effective factor was shot size. When the gas was injected at cavity's end, the most effective factor was melt temperature. Injection speed was also an effective factor in GAIM process.

• Transactions of Materials Processing
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• v.20 no.1
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• pp.5-10
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• 2011

The main objective of the present study is to predict the process window of injection-compression molding corresponding to the capability of an injection machine for fabricating 7 inch LGP. The open distance and volume filled after injection stage were found to be two important factors that affect critical requirements such as flow length, injection pressure and clamping force for the process. Process window for the key factors was also predicted by response surface method. As a result, predicted process window for open distance and volume filled after injection stage satisfying the critical requirement with a given injection machine was in the range of 60 ~ 75%, and 104.00 ~ 104.25%, respectively.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.3
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• pp.92-97
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• 2012

Injection mold is a manufacturing process used to produce parts of complicated shape at a low cost. Many factors affect the quality of injection molded part during injection molding process. A study on the optimization of injection mold is progressed by using a simulation software like Moldflow. Filling, packing and cooling phases of injection molding processes are analyzed according to the mold design considering the shrinkage of molded part, the degree of filling rate and the wearing of a mold. Taguchi method is applied to analyze the significance of processing parameter and the dynamic characteristics according to the variation of processing parameters. From the results, the mold temperature and packing pressure influenced the shrinkage of injection molded part.

• Transactions of the Society of Information Storage Systems
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• v.1 no.2
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• pp.192-196
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• 2005

In this paper, we investigated the possibility of replicating patterned media by nano-injection molding process with a metallic nano-stamper. The original nano-master was fabricated by E-beam lithography and ICP etching process. The metallic nano-stamper was fabricated using a nanoimprint lithography and nano-electroforming process. The nano-patterned substrate was replicated using a nano-injection molding process without additional etching process. In nano-injection molding process, since the solidified layer, generated during the polymer filling, deteriorates transcribability of nano patterns by preventing the polymer melt from filling the nano cavities, an injection-mold system was constructed to actively control the stamper surface temperature using MEMS heater and sensors. The replicated polymeric patterns using nano-injection molding process were as small as 50 nm in diameter, 150 nm in pitch, and 50 nm in depth. The replicated polymeric patterns can be applied to high density patterned media.

• 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.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.2
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• pp.8-11
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• 2006

Gas-assisted injection molding (GAIM) process reduces the required injection pressure during mold filling stage as well as the shrinkage and warpage of the part and cycle time. Despite of these advantages, this process needs new parameters and makes the application more difficult because gas and melt interact during the injection molding process. Important GAIM factors involved in this process are gas penetration design, locations of gas injection points, shot size, delay time to inject gas as well as common injection molding parameters. In this study, the experiments are conducted to investigate effects of GAIM process variables on the gas penetration for PP (Polypropylene) and ABS (Acrylonitrile Butadiene Styrene) moldings by changing the gas injection point. Taguchi method is used for the design of the experiments. When the gas is injected at a cavity's center, the most effective factor is the shot size. When the gas is injected at a cavity's end, the most effective factor is the melt temperature. The injection speed is also an effective factor in GAIM process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.882-885
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• 2002

Magnesium alloys are very attractive materials for appling to the development of autemobile parts or electric goods where light weight and higher stiffness. Due to higher ratio of strength vs. weight and stillness vs. weight, various magnesium alloys are well applied in much weight saving design applications though extrusion or die-casting process. However for the requisites of higher strength and weight savings, some new fabrication processes has been and it can be realized though the aid of injection modeling technology. To obtain the parametric data base for the injection molding process, various experiments were executed for AZ91D magnesium alloy. This paper propose the optimum condition of injection temperature, first and second pressure. the process was lined-up successfully often changing the injection unit. fluid pressure system from the conventional plastic injection molding process.