• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.22 no.1
• /
• pp.145-149
• /
• 2013

The performance of injection molding machine's control system, such as reproducibility, repeatability, etc, is widely studied nowadays. Since screw stroke, injection cylinder body pressure and barrel temperature are the most important terms of injection unit, interval linearity and repeatability to each parameter are analyzed here. Barrel temperature is analyzed according to the repeatability of the thermocouple at $150^{\circ}C$, $210^{\circ}C$, $300^{\circ}C$ using a precise oven. The result temperature is within ${\pm}0.5^{\circ}C$ Through the reliability evaluation of the most important terms of injection unit, the method of evaluating the linearity and repeatability is proposed and verified.

• Transactions of Materials Processing
• /
• v.29 no.4
• /
• pp.218-228
• /
• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Fibers and Polymers
• /
• v.7 no.4
• /
• pp.404-413
• /
• 2006

This study examines multiple quality optimization of the injection molding for Polyether Ether Ketone (PEEK). It also looks into the dimensional deviation and strength of screws that are reduced and improved for the molding quality, respectively. This study applies the Taguchi method to cut down on the number of experiments and combines grey relational analysis to determine the optimal processing parameters for multiple quality characteristics. The quality characteristics of this experiment are the screws' outer diameter, tensile strength and twisting strength. First, one should determine the processing parameters that may affect the injection molding with the $L_{18}(2^1{\times}3^7)$ orthogonal, including mold temperature, pre-plasticity amount, injection pressure, injection speed, screw speed, packing pressure, packing time and cooling time. Then, the grey relational analysis, whose response table and response graph indicate the optimum processing parameters for multiple quality characteristics, is applied to resolve this drawback. The Taguchi method only takes a single quality characteristic into consideration. Finally, a processing parameter prediction system is established by using the back-propagation neural network. The percentage errors all fall within 2%, between the predicted values and the target values. This reveals that the prediction system established in this study produces excellent results.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.6
• /
• pp.114-120
• /
• 2021

This study is focused on the root mean square and peak-to-valley based on the injection conditions of the f-theta lens, one of the main components of laser printers and laser scanning systems. The f-theta lens of an aspherical plastic lens requires ultra-preaction. Injection molding is typically used for the mass production of aspherical plastic lenses. In the injection-molding method, the resin in the lens shape is filled with the resin after melting the plastic pellets at a constant temperature and then cooled. It is necessary to maintain a uniform injection molding system to produce high-quality lenses. These injection-molding systems are influenced by different factors, such as pressure, speed, temperature, mold, and cooling. It is possible to obtain a lens that exhibits the optical characteristics required to achieve harmony. We investigated the root mean square and peak-to-valley caused by variations in temperature, a critical parameter in the melting and cooling of plastic resins generated inside and outside the injection mold.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2007.05a
• /
• pp.205-208
• /
• 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.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.1537-1541
• /
• 2007

We injection molded a wedge type of plate with micro prizm patterns on its surface and investigated the fidelity of replication of the micro pattern depending on the process parameter such as mold temperature, melt temperature, injection rate or packing pressure. The size of the size of the $90^{\circ}$ prizm pattern is $50{\mu}m$ and the size of the plate is about 300㎜${\times}$200㎜. The thicknesses are 2.6㎜. and 0.7mm at each edge of the wedge type of plate. The fidelity of the replication turned out quite different according to the process parameters and location of the patterns on 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.

• Transactions of Materials Processing
• /
• v.15 no.1 s.82
• /
• pp.65-70
• /
• 2006

In recent industry, with the miniaturization and high-precision of machine part, the development of mold manufacturing technology for mass production is accompanied by the development of new technology such as IT and BT In this study, the spiral type injection mold with a $200{\mu}m$ thickness is made to. investigating the influence of injection molding parameter and the flow length is measured through an experiment. Besides, Taguchi method is used in this experiment and the obtained data are analyzed using ANOVA method.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2006.05a
• /
• pp.81-85
• /
• 2006

In this study, we have been examined nano Injection Molding process which can improve transcription of 100nm-level pattern. We changed the various parameter (temperature of injection mold, clamp force, temperature of nozzle) which can be influence for improving transcription. And we measured and analyzed shapes of 100nm-level pattern by Automic Force Microscope for proving transcription. We made the Blu-ray Disc sample for proving transcription. And we measured HF-Signal and jitter. As a result, when the temperature of mold is more than $120^{\circ}C$ and the clamp force is more than 10 ton, We reached over 95 percent of transcription compared with stamper pattern. And we reached in-spec. value for HF-Signal and Jitter. Then we reached over 95 percent of transcription compared with stamper pattern.

• Advances in materials Research
• /
• v.3 no.2
• /
• pp.91-103
• /
• 2014

A study that demonstrates how to investigate the molded part quality and the consistency of injection process based on the rheological concept is proposed. It is important for plastic material whose melt viscosity is variable with respect to the processing condition. The formulations to couple the melt viscosity with injection pressure and fill time are derived first. Taking calculations of the measured pressure and the time by using these formulations, the melt viscosity in injection process can be determined on machine. As the relation between the injection speed and the melt viscosity is constructed, the influences of the setting parameter of injection machine on the molded part quality can be investigated through evaluating the state of the melt viscosity. In addition, a pressure sensor bushing (PSB) designed with a quick installation feature is also provided and validated. The results show that a higher injection speed improves the tensile strength of the molded part but also the consistency of the molded part quality. This work provides an alternative to evaluate the molding quality scientifically.

• The Korean Journal of Rheology
• /
• v.11 no.2
• /
• pp.159-167
• /
• 1999

Sandwich injection molding is one of the remarkable polymer processes recently developed from conventional injection molding. But it is almost impossible to do theoretical investigation that we've researched it through numerical simulation. In this paper, numerical simulation on the study of sandwich injection molding is based on Finite Element Method and FAN/Control Volume method. In addition to conventional filling parameter that can confirm skin polymer melt front, new filling parameters have been introduced to confirm core polymer melt front advancement. These filling parameters are defined in each layer which is divided to solve temperature field along the thickness direction. One can notice different filling patterns resulted from the variation of material properties such as viscosities and power-law indexes, and processing conditions such as switch-over times and wall temperatures. It gives us a better understanding of the sandwich injection molding process. And we can recognize that it's the core polymer spatial distribution after the completion of filling that is the most important key point to use this process for industrial molding process.