• 한국기계가공학회지
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• 제14권4호
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• pp.92-99
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• 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.

• 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.

• Design & Manufacturing
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• 제10권3호
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• pp.30-33
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• 2016

It is true that the plastic shrinkage is inevitable. Shrinkage rate in effect at the time of mold design will soon determine the size of the global product. Process for the shrinkage of the plastic that provides how made, yet it has identified a process for making the question whether the shrinkage that can be trusted, and by the experimental results were as follows: as shrinkage, see ISO but, according to circumstances the process can go to the agreement between the parties. shrinkage ratio of the pressure sensor installed in the specimen mold is essential, amount of pressure sensor is that it is appropriate approximately 2-3. proper holding pressure is a significant effect on shrinkage Mitch, so that the effect of selecting the contraction ratio data according to the appropriate holding pressure during mold making. shrinkage CAE analysis results are difficult to utilize in the mold-making chamber. Based on these results, it concluded by looking forward to the improved products produced shrinkage.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.852-855
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• 2003

Gas-Assisted Injection Molding(GAIM) process, that can be used to provide a hollow shape in a molding, is a variant of the conventional injection molding process. GAIM has many advantages such as reduction of material, sink mark. warpage. and lower injection pressure. Thus, GAIM has been widely applied in the industry to make moldings with a hollow channel such as handles, TV frames and so on. On the other hand, GAIM has some disadvantages such as slow cooling time and flow marks. In the disadvantages, hot gas core causes slow cooling of a molding and the overflow. which is to prevent flow mark. is waste of materials. To solve these problems, we developed a new GAIM system that we called RGIM(Reverse Gas Injection Molding). The RGIM has two special units; one is the overflow buffer, which is used for reduction of a material, and the other tile air unit, which is used for faster cooling of a molding. We conducted an experiment and simulation to verify the efficiency of the RGIM system. Through experiments and simulation, we confirmed the effectively operating of the RGIM system and extracted the optimum process conditions.

• 소성∙가공
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• 제16권1호
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• pp.25-30
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• 2007

The present study covers an integrated simulation method to evaluate optical performance of an aspheric plastic lens by connecting a finite element (FE) analysis of injection molding with a ray tracing simulation. Traditional ray tracing methods have based on the assumption that the optical properties of a lens are homogeneous throughout the entire volume. This assumption is to a certain extent unrealistic for injection-molded plastic lenses because material properties vary at every point due to the injection molding effects. To take into account the effects of the inhomogeneous optical properties of the molded lens, a new.ay tracing scheme is proposed in conjunction with a FE analysis of the injection molding. A numerical scheme is developed to calculate ray paths on every element layer with more realistic information of the refractive indices which can be obtained through the FE analysis. This information is then used to calculate the ray paths based on the FE mesh of which nodal points have unique index values. The proposed tracing scheme is implemented on the tracing of an aspheric lens, and its validity is ascertained through experimental verification.

• 한국축산식품학회지
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• 제39권3호
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• pp.494-502
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• 2019

The quality characteristics and storage stability of chicken breast meat (CBM) was investigated following the injection of whey protein (WP) as a curing ingredient. The moisture content of CBM decreased with increasing concentration of WP. The highest concentration of WP (7%) resulted in the lowest moisture and fat content and the highest protein content of CBM. Injection of WP elevated the pH and water holding capacity (WHC) of CBM. The cooking loss of CBM was significantly decreased with WP injections of 3% and higher. All WP injections increased the $L^*$ of the CBM but decreased the $a^*$ and $b^*$. WP injection increased the springiness, cohesiveness, and chewiness and decreased the hardness of the CBM. WP injection increased 2-thiobarbituric acid reactive substances (TBARS) after 3 and 7 days of storage. The volatile basic nitrogen (VBN) content of the CBM increased with increased concentrations of WP. The total microbial count (TMC) of CBM injected with WP was higher initially and after 3 days of storage. Our results showed WP injection improved the WHC of CBM but decreased the storage stability by increasing TBARS, VBN and TMC.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.811-814
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• 2001

Warpage analysis of bobbin, molded by injection molding process was performed. Concerned with a mold design, cooling system was designed based on Taguchi method, the distance between cavity wall and cooling channel was most influent factor amongst four design variables like an inlet temperature of coolant, a coolant flow rate, a diameter of cooling channel, and the distance between cavity wall and cooling channel. Optimal packing processes to reduce the warpage of molded part was analyzed based on the response surface method by considering holding pressure. Their optimal processing conditions were 9.4 seconds, 5.3 seconds, 15.2 seconds, and 85MPa, respectively.

• 한국정밀공학회지
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• 제21권2호
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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.

• 한국분말재료학회지
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• 제24권3호
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• pp.223-228
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• 2017

Nanopowders provide better details for micro features and surface finish in powder injection molding processes. However, the small size of such powders induces processing challenges, such as low solid loading, high feedstock viscosity, difficulty in debinding, and distinctive sintering behavior. Therefore, the optimization of process conditions for nanopowder injection molding is essential, and it should be carefully performed. In this study, the powder injection molding process for Fe nanopowder has been optimized. The feedstock has been formulated using commercially available Fe nanopowder and a wax-based binder system. The optimal solid loading has been determined from the critical solid loading, measured by a torque rheometer. The homogeneously mixed feedstock is injected as a cylindrical green body, and solvent and thermal debinding conditions are determined by observing the weight change of the sample. The influence of the sintering temperature and holding time on the density has also been investigated. Thereafter, the Vickers hardness and grain size of the sintered samples have been measured to optimize the sintering conditions.

• 한국기계가공학회지
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• 제16권3호
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• pp.131-137
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• 2017

In this study, we evaluated the surface roughness of mold and injected parts manufactured by polycarbonate (PC) injection molding. The mold surface was polished to produce six differentiated roughnesses with 12 areas using stones (#800, #1200), sandpapers (#800, #1200), and diamond compounds (#8000, #14000). Injected parts were created using 20mm/s injection speed, 80 bar holding pressure for 5 seconds, and $70^{\circ}C$ cooling water. Injected parts surface roughness (Sa) was measured randomly in 10 of 30 using an interferometer (NewView8000, zygo, USA). In the same way, mold surface was measured randomly 10 times on 12 polished areas. Surface roughness of molds and injected parts were compared, and a regression equation to predict mold surface roughness was proposed for specific injection molding parameters.