• 정보저장시스템학회논문집
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• 제2권2호
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• pp.100-104
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• 2006

Stamper surface temperature is very critical in replicating the high density optical disc substrates using injection molding as the pit or land/groove patterns on the optical disc substrate have decreased due to the rapid increase of areal density. During the filling stage, the polymer melt in the vicinity of the stamper surfaces rapidly solidifies and the solidified layer generated during polymer filling greatly deteriorates transcribability and fluidity of polymer melt. To improve transcribability and fluidity of polymer melt, stamper surface temperature should be controlled such that the growth of the solidified layer is delayed during the filling stage. In this study, the effect of heating on replication process was simulated numerically. Then, an injection mold equipped with instant active heating system was designed and constructed to raise the stamper surface temperature over the glass transition temperature during filling stage of the injection molding. Also, the closed loop controller using the Kalman filter and the linear quadratic Gaussian regulator was designed. As a result. the stamper surface temperature was controlled according to the desired reference stamper surface temperature.

• Design & Manufacturing
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• 제18권2호
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• pp.64-73
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• 2024

The purpose of this paper is to introduce a fusion method that combines the design of experiments (DOE) and machine learning to optimize the bias of plastic products. The study focuses on the plastic motor housing used in automobiles, which is manufactured through plastic injection molding. Achieving optimal molding for the motor housing involves the optimization of various molding conditions, including injection pressure, injection time, holding pressure, mold temperature, and cooling time. Failure to optimize these conditions can lead to increased product deformation. To minimize the deformation of the motor housing, the widely used Taguchi method, which is one of the design of experiment techniques, was employed to identify the injection molding conditions that affect deformation. Machine learning was then applied to various models based on the identified molding conditions. Among the models, the Random Forest model emerged as the most effective in predicting deformation amounts. The validity of the Random Forest model was also confirmed through verification. The verification results demonstrated the excellent prediction accuracy of the trained Random Forest model. By utilizing the validated model, molding conditions that minimize deformation were determined. Implementation of these optimal molding conditions led to a reduction of approximately 5.3% in deformation compared to the conditions before optimization. It is noteworthy that all injection molding outcomes presented in this paper were obtained through robust injection molding simulations, ensuring both research objectivity and speed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 춘계학술대회 논문집
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• pp.1047-1048
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• 2012

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 추계학술대회논문집
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• pp.70-74
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• 2004

Pressure and temperature in the cavity of injection molding have been investigated. Special injection mold was designed to install pressure and temperature sensors. The sensors were supplied by KISTLER and the pressure and temperature were measured for various operational conditions, such as injection pressure, holding pressure, cooling time, mold temperature, and injection temperature. As injection pressure increased cavity pressure and temperature increase. There were no big differences in temperatures according to the holding pressures. As mold temperature increased pressure and temperature in the cavity increase. The flowability of resin increases as mold temperature increases subsequently the pressure in the cavity increases since the pressure loss is less in the low viscous medium than high ciscous medium. The cavity temperature highly depends upon mold temperature.

• Design & Manufacturing
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• 제12권3호
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• pp.5-12
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• 2018

Plastic containers which provides the opportunity to reduce transportation costs are lighter and less brittle than glass containers. As a results, efforts to replace glass with plastic are ongoing. The blow molding method is a typical approach in producing plastic containers. Single-stage injection blow molding (ISBM) is one of the blow molding methods. However, the difficulty in controlling the temperature during the injection molding process is considered its main disadvantage. In this study, ISBM process analysis of relatively thick walled containers such as cosmetic containers is carried out. The initial temperature distribution of the preform is deemed to be the most influential factor in the accuracy of blow molding for the thick vessel. In order to accurately predict this, all heat transfer processes of the preform are considered. The validity of this analytical procedure is verified by comparing the cross-sectional thickness with the actual product. Finally, the validated analytical method is used to evaluate the factors affecting the thickness of the final molded part. The ISBM analysis technique for thick walled vessels developed through this study can be used as an effective predictor for preform design and blow process.

• Design & Manufacturing
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• 제14권4호
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• pp.71-77
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• 2020

Various manufacturing technologies, including over-molding and insert-injection molding, are used to produce hybrid plastics and metals. However, there are disadvantages to these technologies, as they require several steps in manufacturing and are limited to what can be reasonably achieved within the complexities of part geometry. This study aims to determine a practical approach for producing metal/plastic hybrid components by combining plastic injection molding and metal die casting to create a new hybrid metal/plastic molding process. The integrated metal/plastic hybrid injection molding process developed in this study uses the proven method of multi-component technology as a basis to combine plastic injection molding with metal die casting into one integrated process. In this study, the electrical conductivity and ampacity were verified to qualify the new process for the production of parts used in electronic devices. The electrical conductivity was measured, contacting both sides of the test sample with constant pressure, and the resistivity was measured using a micro ohmmeter. Also, the specific conductivity was subsequently calculated from the resistivity and contact surface of the conductor path. The ampacity defines the maximum amount of current a conductive path can carry before sustaining immediate or progressive deterioration. The manufactured hybrid multi-components were loaded with increasing currents, while the temperature was recorded with an infrared camera. To compare the measured infrared images, an electro-thermal simulation was conducted using commercial CAE software to predict the maximum temperature of the power loaded parts. Overall, during the injection molding process, it was demonstrated that multifunctional parts can be produced for electric and electronic applications.

• 대한기계학회논문집A
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• 제21권11호
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• pp.1773-1785
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• 1997

The cooling stage is the very critical and most time consuming stage of the injection molding process, thus it cleary affects both the productivity and the part quality. Even through there are several commercialized package programs available in the injection molding industry to analyze the cooling performance of the injection molding coling stage, optimization of the cooling system has npt yet been accomplished in the literature due to the difficulty in the sensitivity analysis. However, it would be greatly desirable for the mold cooling system designers to have a computer aided design system for the cooling stage. With this in mind, the present study has successfully developed an interated computer aided design system for the injection molding cooling system. The CAD system utilizes the sensitivity analysis via a Boundary Element Method, which we recently developed, and the well-known CONMIN alforuthm as an optimization technique to minimize a weighted combination (objective function) of the temperature non-uniformity over the part surface and the cooling time related to the productivity with side constranits for the design reality. In the proposed objective function , the weighting parameter between the temperature non-uniiformity abd the cooling time can be adjusted according to user's interest. In this cooling system optimization, various design variable are considered as follows : (i) (design variables related to processing conditions) inlet coolant bulk temperature and volumetric flow rate of each cooling channel, and (ii) (design variables related to mold cooling system design) radius and location of each cooling channel. For this optimum design problem, three different radius and location of each cooling channel. For this optimum design problem, three different strategies are suffested based upon the nature of design variables. Three sample problems were successfully solved to demonstrated the efficiency and the usefulness of the CAD system.

• 한국정밀공학회지
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• 제33권1호
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• pp.23-29
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• 2016

In this paper, a real-time condition diagnosis system for the lens injection molding process is developed through the use of LabVIEW. The built-in-sensor (BIS) mold, which has pressure and temperature sensors in their cavities, is used to capture real-time signals. The measured pressure and temperature signals are processed to obtain features such as maximum cavity pressure, holding pressure and maximum temperature by the feature extraction algorithm. Using those features, an injection molding condition diagnosis model is established based on a response surface methodology (RSM). In the real-time system using LabVIEW, the front panels of the data loading and setting, feature extraction and condition diagnosis are realized. The developed system is applied in a real industrial site, and a series of injection molding experiments are conducted. Experimental results show that the average real-time condition diagnosis rate is 96%, and applicability and validity of the developed real-time system are verified.

• 한국전기전자재료학회논문지
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• 제34권6호
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• pp.426-432
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• 2021

Injection molding is used in many industrial fields such as home appliances, vehicle parts, and electronic device parts because various resins can be molded, leading to mass production of complex shapes. Generally, the empirical prediction method is used to set the initial processing conditions of injection molding. However, this approach requires a lot of cost and its presented solution is not accurate. In this paper, injection molding was simulated through the Moldflow^TM in order to manufacture the spacer for gas insulated switch. Through the simulation, the flow of the resin with respect to the diameter of the inlet was analyzed. It was found that the process was possible at a higher resin temperature as the diameter of the inlet increased. In addition, through thermal analysis during injection of the resin, it was confirmed that a stagnation phenomenon occurred at the insert portion during injection molding, and the temperature of the resin was higher than that of the mold. As in this paper, if the spacer is manufactured by optimizing the injection hole and the temperature of the injection process based on simulation, it is expected that the spacer can be manufactured with high productivity.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 춘계학술대회 논문집
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• pp.205-208
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• 2007

We injection molded a thin plate with micro prism patterns on its surface and investigated the fidelity of replication of the micro pattern depending on the process parameter such as mold temperature, injection rate or packing pressure. The size of the $90^{\circ}$ prism pattern is $50{\mu}m$ and the size of the plate is $400mm{\times}400mm$. The thickness is 1mm. The fidelity of the replication turned out quite different according to the process parameters and location of the patterns of the plate. We measured the cavity pressure and temperature in real-time during the molding to analyze the effect of the local melt pressure and temperature on the micro pattern replication.