• 동력기계공학회지
• /
• 제6권2호
• /
• pp.68-72
• /
• 2002

Design of experiment was applied to analyze the shrinkage characteristics of the bobbin molded by injection molding. Among lots of design and processing conditions, the thickness of a bobbin and cooling conditions of a mold were considered. The temperature difference between top and bottom parts of the bobbin was considered as the objective to minimize the shrinkage of a bobbin. Optimal thickness of a bobbin was 2.0mm at the part of body and 1.5mm at the part of wing, respectively. Optimal cooling conditions such as cooling time and coolant inlet temperature were 12 second and $12^{\circ}C$, respectively.

• 한국유변학회:학술대회논문집
• /
• 한국유변학회 2006년도 춘계 학술발표회 논문집
• /
• pp.71-74
• /
• 2006

• 한국정밀공학회지
• /
• 제22권4호
• /
• pp.144-150
• /
• 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.

• 대한기계학회논문집
• /
• 제14권1호
• /
• pp.54-71
• /
• 1990

본 연구에서는 세라믹 기계요소를 생산하기 위한 기초연구로서, 세라믹 사출 성형에 대한 기본적인 가공조건과 여러변수들을 고찰하고 가능한한 최대의 세라믹체적 비를 갖고 세라믹입자와 완벽한 융합을 이룰수 있는 최적의 결합제 구성과 세라믹입자 의 충진비율에 따른 혼합체(mixture)의 유동특성을 규명하여 사출성형의 적부를 판별 함과 동시에 그 훈련된 상태를 고찰하여 이후의 공정에서 불균일에 의한 결함이 발생 하지 않도록 정확한 성형조건을 제시하고자 한다. 또한 사출성형에 가장 적절한 혼 합체를 선정하여 탈지공정 및 소결을 행하고 각 공정에서의 부품의 수축률 및 결함을 관찰하여 그 결함의 원인 및 제거방법에 대하여 논의할 것이다. 본 논문에서 제시한 각 공정 및 고찰은 중요한 모든 변수들의 경향 및 특성을 다루었으며 정밀한 세라믹부 품의 신속한 생산을 위한 기초 연구로서 실제 산업체에 응용될 수 있을 것으로 사료된 다.

• 한국산학기술학회논문지
• /
• 제7권3호
• /
• pp.271-277
• /
• 2006

사출 성형 공정은 저비용으로 고품질의 제품을 대량으로 얻을 수 있는 제조 공정이지만. 성형품의 품질에 영향을 주는 인자의 수가 너무 많아 모든 경우에 대하여 실험을 수행하는 것은 시간적, 경제적으로 불가능하다. 따라서 최근에 시뮬레이션 도구를 활용하여 이러한 실험을 보조하고 있고, 실험계획법 및 여러 가지 최적화 기법들이 다루어지고 있다. 인자수가 많은 경우 각 입력인자 간의 교호작용 등도 고려하면서도 실험 횟수를 줄이는 기법으로 정립된 실험계획법을 적용하여 시뮬레이션 소프트웨어를 이용한 모의 실험 데이터를 도출하였으며, 이를 바탕으로 주변의 잡음에서도 강건한 설계를 할 수 있는 다구찌 기법을 사출 성형 공정에 적용하여 최적의 사출 성형 공정 조건을 나타내었다.

• 한국산학기술학회논문지
• /
• 제17권11호
• /
• pp.610-615
• /
• 2016

자동차의 부속 장비들은 용도에 따라 네비게이션, 전방 및 후방카메라, 스포일러, 선 바이저 등 다양한 것들이 채택되어 사용되고 있다. 이 중에서 선 바이저는 햇빛을 차단시켜 줌으로써 운전자의 시야 확보를 통해 안전운전을 돕는 역할을 한다. 이런 장점으로 많은 차량에 채택되어 사용되고 있는 추세이다. 그러나 대형의 플라스틱 제품들은 사출성형을 통해 생산하기까지는 웰드 라인, 충전부족, 플로우 마크, 미성형 및 변형 등 여러 가지 문제로 인한 어려움이 따른다. 본 연구는 차량용 대형 선바이저에 관한 것으로써 대형 제품을 사출 성형하는 데 발생될 수 있는 문제점을 먼저 파악하기 위해 선(先)행된 결과를 토대로 CAE 시뮬레이션을 수행하였다. 연구를 수행한 결과 첫째, 용융수지가 완전 충전되기까지 유동의 흐름을 파악할 수 있었다. 둘째, 유동선단부의 온도 편차가 $10^{\circ}C$정도로 매우 안정적임을 확인 할 수 있었다. 셋째, 성형품의 콜드 러너 취출(取出) 가능시간(약 70sec)을 구하였다. 넷째, 사출압력 및 형 체결력을 예측하여 사출 성형기의 능력을 구할 수 있었다.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2013년도 춘계학술대회 논문집
• /
• pp.1055-1056
• /
• 2013

• 한국기계가공학회지
• /
• 제14권4호
• /
• pp.92-99
• /
• 2015

The deformation of injection molding is seriously affected by injection molding conditions, such as melt and mold temperature and injection and holding pressure. In these conditions, the mold temperature is controlled by flowing coolant, which can be classified by the Reynolds number in the mold-cooling channel. In this study, the deformation of the automotive side molding according to the variation of the Reynolds number in the coolant was simulated by Moldflow. In the results, as the Reynolds number was increased, the mold cooling was also increased. However, when the Reynolds number exceeded a certain range, the mold cooling was not increased further. In addition to the Moldflow verification, the mold cooling by the coolant was simulated by CFX. The CFX results confirmed that the Reynolds number significantly influenced the mold cooling. The coolant, which has a high Reynolds number value, quickly cooled the mold. However, the coolant, which has a low Reynolds number value, such as 0 points, hardly cooled the mold. In an injection molding experiment, as the Reynolds number was high, the deformation of the moldings was reduced. The declining tendency of the deformation was similar to the Moldflow results.

• 한국정밀공학회지
• /
• 제17권9호
• /
• pp.210-221
• /
• 2000

Plastic mold designers and frequently faced with optimizing multi-quality issues in injection molded parts. These issues are usually in conflict with each other and thus tradeoff needs to be made to reach a final compromised solution. in this study an automated injection molding design methodology has been developed to optimize multi-quality characteristics of injection molded parts. The features of the proposed methodology are as follows : first utility theory is applied to transform the original multi-objective problem into single-objective problem. Second is an implementation of a direct search-based injection molding optimization procedure with automated consideration of robustness against process variation. The modified complex method is used as a general optimization tool in this study. The developed methodology was applied to an actual mold design and the results showed that the methodology was useful through the CAE simulation using a commercial injection molding software package. Applied to production this study will be of immense value to companies in reducing the product development time and enhancing the product quality.

• Design & Manufacturing
• /
• 제17권4호
• /
• pp.72-78
• /
• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.