• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.221-221
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• 2004

플라스틱의 사출성형중 용용 수지에 가스를 주입하는 가스사출성형(Gas Assisted Injection Molding GAIM)에 의해 성형품을 만드는 생산방법은 약 30년 전부터 유럽지역을 중심으로 시작되었다 GAIN의 개발 배경은 발포성형을 대체하기 위한 공법으로 개발되었다. 발포성형은 싱크마크(sink mark) 제거, 치수안정성, 강도보강의 목적으로 사용하는 공법이지만, 가스기포가 표면으로 빠져나오고 표면에 가스 기포가 발생하여 외관부품에 부적당하며, 두께가 5-6mm이하의 성형품에는 적용할 수 없고, 성형시간이 긴 문제점을 가지고 있어 이러한 문제를 보강한 공법을 연구할 결과로 GAIM이 탄생하게 되었다.(중략)

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.71-72
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1195-1196
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• 2010

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.2
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• pp.289-295
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• 2010

Injection molding process is one of the most important methods to produce plastic parts with high efficiency and low cost. Today, injection molded parts have been increased dramatically the demand for high strength and quality applications. In this study, In-line skates are made of Al alloy and plastic materials to replace the frame for the optimization process is all about. I interpreted through mold design, Injection molding process that minimizes the runner and the gate dimension will determine the size and shape. Runner and gate dimensions of change based on availability of the product, I'll discuss the injection molding. This report investigates that the optimum injection molding condition for minimum of shrinkage. The FEM Simulation CAE tool, Moldflow, is used for the analysis of injection molding process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.111-114
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• 1992

과거 사출금형 설계 및 성형은 대부분의 단편적인 경험에 의존하여 왔으며 이는 단납기, 고품질화에의 대응에 있어서 가장 큰 문제점중의 하나로 인식되어 왔다. 그러나 최근에는 컴퓨터의 성능이 급격히 향상되고 보편화되면서 대기업을 선두로 한 컴퓨터 시뮬레이션이 활발히 응용되고 있으며 이는 앞으로 더욱 활성화될 전망이다. 본 연구에서는 사출성형 자동평가 시스템을 개발하였으며 이는 전처리 모듈, CAE해석 모듈 및 자동분석 모듈, 후처리 모듈등으로 구성되어 있다. 본 시스템에서는 주입장치 설계 표준 DATA BASE가 구축되어 있으며 특히 설계자가 설계 및 성형조건에 대한 기준만 정의하면 그 이후의 모든 평가 및 최적조건이 자동으로 계산, 도출될 수 있도록 하였다. 이번에 개발한 시스템에서의 핵심기술은 수치해석을 응용한 고분자 가공공정해석기술, 최적화 기술, DATA BASE구축기술 그리고 컴퓨터 그래픽 기술 등으로 위에서 언급한 바와 같은 사용시스템이 갖고 있는 현장 활용시 문제점들을 근본적으로 해결하여 차별화 시킨 것이다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.1097-1103
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• 2010

Injection pressure, an important factor in the filling procedure, should be minimized to enhance injection molding quality. In addition, warping deformation and weld lines, which are representative failures, should be avoided to enhance injection molding quality. To improve injection molding quality, the design procedure for an automotive fog blank cover is divided into two stages. In the first stage, we optimally obtain injection molding process variables that minimize injection pressure and warping deformation by using design of experiments, approximation and optimization techniques equipped in PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration and Design Optimization) tool. Then, we determine the thickness of the automotive fog blank cover that enables us to avoid generating weld lines. The design results we obtain in this study are found far better than those of the initial design, which demonstrates the effectiveness of our design method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.9
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• pp.893-899
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• 2015

In the design of injection molds, the temperature distribution and deformation of the mold is one of the most important parameters that affect the flow characteristics, flash generation, and surface appearance, etc. Plastic injection analyses have been carried out to predict the temperature distribution of the mold and the pressure distribution on the cavity surface. As the input loads, we transfer the temperature and pressure results to the structural analysis. We compare the structural analysis results with the thermal expansion effect using the actual flash and step size of a smartphone cover part. To reduce the flash problem, we proposed a new mold design, and verified the results by performing simulations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1361-1366
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• 2010

This research aims to develop polymer composites which can be used for PEMFC separators by injection molding process. Considering the moldability and stiffness, we used PPS(Poly(phenylene sulfide)) and PP(Polypropylene) as base resin. In order to improve electrical conductivity and physical properties, we chose glass fiber, carbon fiber, carbon black, and both expanded graphite and synthetic graphite. The 3 type composites are prepared for injection molding of PEMFC separators. and CAE(Computer Aided Engineering) analysis was conducted to optimize injection processing parameters(injection pressure, heat time, mold temperature etc.). We did successfully fabricate the separators by injection molding, and measure the electrical conductivity of the samples by using four point probe device. Conclusively, PP/SG/CB composite showed better both electrical conductivity and moldability than the others.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.3 s.168
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• pp.68-77
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• 2005

The set-up of an injection molding process is a ye complicated and time-consuming job because it is required to well determine a lot of variables closely related to products. Thus, the productivity of the set-up process mainly depends on operators' expertise and know-how. To solve the problem mentioned before, this research constructs a support system which helps operators determining the condition of the injection molding easily and systematically. The construction of the support system consists of the following four steps: 1) to determine the control variables which affect the target defect types, 2) to design and implement UI(user interface) using a scenario of set-up process, 3) to design and implement the search algorithms for the initial and optima] condition, and 4) to construct the embedded system which integrates the support system with the operating system of a plastic injection molding machine. The test experiments of some typical products are performed using the embedded system to verify the validity of the support system.

• 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.