• Design & Manufacturing
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• v.15 no.1
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• pp.21-25
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• 2021

When the product is removed from the mold after molding during the sheet metal molding process, elastic recovery causes a springback phenomenon. Much research has been done to minimize this phenomenon. In this study, V-bending experiments were conducted using galvanized steel sheets, stainless steel, and aluminum sheet materials, using a total of nine types of thin sheet materials of 1.0t, 1.5t, and 2.0t, respectively. Molding analysis and experimental data were compared and analyzed. In the case of galvanized steel sheets, it was considered that the springback phenomenon occurs more frequently in molding analysis than in experiments. It was considered that the springback phenomenon occurs greatly in the experiment, not the interpretation of the molding of the stainless steel plate and the aluminum plate. It was considered that the springback occurrence tendency of the molding analysis and the experiment was the same, and the springback occurrence error rate of the molding analysis and the experimental result was about 4.0%.

• Design & Manufacturing
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• v.16 no.4
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• pp.1-6
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• 2022

Fine blanking is a press processing technology that can process most of the product thickness into a smooth surface with a single stroke. In this fine blanking process, shear is an essential step. The punches and dies used in the shear are subjected to impacts of tens to hundreds of gravitational accelerations, depending on the type and thickness of the material. Therefore, among the components of the fine blanking mold (dies), punches and dies are the parts with the shortest lifespan. In the actual production site, various types of tool damage occur such as wear of the tool as well as sudden punch breakage. In this study, machine learning algorithms were used to predict these problems in advance. The dataset used in this paper consisted of the signal of the vibration sensor installed in the tool and the measured burr size (tool wear). Various features were extracted so that artificial intelligence can learn effectively from signals. It was trained with 5 features with excellent distinguishing performance, and the SVM algorithm performance was the best among 33 learning models. As a result of the research, the vibration signal at the time of imminent tool replacement was matched with an accuracy of more than 85%. It is expected that the results of this research will solve problems such as tool damage due to accidental punch breakage at the production site, and increase in maintenance costs due to prediction errors in punch exchange cycles due to wear.

• Design & Manufacturing
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• v.10 no.3
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• pp.20-24
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• 2016

Foaming is a step of forming by the ratio of the internal combustion chamber in a state where the in flow of the material is suppressed, if the diameter is small and a high to a crack generated on the molding is not possible. The present study, we studied using as part experiments for forming the circular shape of the forming height of 10 mm without the occurrence of cracks, results preformed primary, the need to set the height of the forming than the height of the product, preformed secondary. It was able to increase the height of the molded product with less than the height of the next step to be carried out compression processing to create a small comer of the desired shape. In addition, it was found that on a great influence on the quality of the final quality on the final molding of the primary preformed, secondary.

• Design & Manufacturing
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• v.17 no.4
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• pp.72-78
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• 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.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.10a
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• pp.36-39
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• 2004

Glass molding is an advantageous method to manufacture glass micro optical components. However, it is difficult to make Tungsten Carbide core for glass microlens array. We have developed novel method to fabricate Tungsten Carbide core for micro glass components using pressure forming. Silicon masters were fabricated by micro machining. Tungsten Carbide core was fabricated by pressure forming and sintering. And we made high quality surface of Tungsten Carbide core by using the magnetic-field-assisted polishing process.

• Transactions of Materials Processing
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• v.11 no.7
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• pp.581-588
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• 2002

Among the processes to produce micro lens, the process using press molding is a new technology to simplify the process, but it contains many unknown variables. The press-molding process proposed in this paper was simplified into two step process, the first step is the pressing to design the preform for glass element, the second step is the annealing to reduce the residual stress. It is important to estimate the amount of shrinkage of glass gob and the residual stress during process. It Is difficult to evaluate the process variables as mentioned above through the experiment. The influences due to process variables was evaluated by using FEM parametric analysis. The results in this paper can be applicable to produce micro lens.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.26 no.5
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• pp.209-214
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• 2016

Foam reaction injection molding (FRIM) is a widely used process for manufacturing polyurethane foam with complex shapes. Numerical model for polyurethane foam forming reaction during FRIM process has been intensively investigated by a number of researchers to precisely predict final shapes of polyurethane foams. In this study, we have identified a problem related with a previous theoretical model for polyurethane foam forming reaction. Thus, previous theoretical model was modified based on experimental and computational results.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.996-999
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• 2008

Aspheric polymer lens fabrication using isothermal compression molding is presented in this paper. Due to increasing definition of an image sensor, higher precision is required by a lens which can be used as a part of an imageforming optical module. Injection molding is a factory standard method for a polymer optical lens. But achievable precision using injection molding has a formidable limitation due to the machining of complex mold structure and melting and cooling down a polymer melt under high pressure condition during forming process. To overcome the precision requirement and limitation using injection molding method, isothermal compression molding is applied to fabrication of a polymer optical lens. The fabrication condition is determined by numerical simulations of temperature distribution and given material properties. Under the found condition, the lens having a high precision can successfully be reproduced and does not show birefringence which results often in optical degradation.

• Design & Manufacturing
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• v.2 no.1
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• pp.39-43
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• 2008

There occur not only many problems in the injection process but also low quality productivity due to the injection conditions of various injection factors. Injection molding process factors such as molding temperature, injection pressure, flow rate and flow velocity, must be controlled properly in filling and packing phases in the injection molding process. In this study, effects of these factors on the injection molding were investigated through the flow analysis for the holding pressure affecting cooling time. Results of this study would be helpful to setting of holding pressure for optimization of forming condition in order to reduce cooling time in injection molding.

• Advanced Composite Materials
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• v.16 no.4
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• pp.335-347
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• 2007

Green composites composed of long maize fibers and poly $\varepsilon$-caprolactone (PCL) biodegradable polyester matrix were manufactured by the thermo-mechanical processing termed as 'Sequential Molding and Forming Process' that was developed previously by the authors' research group. A variety of processing parameters such as fiber area fraction, molding temperature and forming pressure were systematically controlled and their influence on the tensile properties was investigated. It was revealed that both tensile strength and elastic modulus of the composites increase steadily depending on the increase in fiber area fraction, suggesting a general conformity to the rule of mixtures (ROM), particularly up to 55% fiber area fraction. The improvement in tensile properties was found to be closely related to the good interfacial adhesion between the fiber and polymer matrix, and was observed to be more pronounced under the optimum processing condition of $130^{\circ}C$ molding temperature and 10 MPa forming pressure. However, processing out of the optimum condition results in a deterioration in properties, mostly fiber and/or matrix degradation together with their interfacial defect as a consequence of the thermal or mechanical damages. On the basis of microstructural observation, the cause of strength degradation and its countermeasure to provide a feasible composite design are discussed in relation to the optimized process conditions.