• Design & Manufacturing
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• v.16 no.1
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• pp.43-49
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• 2022

As technologies in various industrial fields develop, high-quality parts are required. In the past, precision parts were produced by the contact machining method, but the contact machining method has clear limitations. In order to solve this problem, research on a non-contact processing method has been conducted, and laser processing and electric discharge processing are representative. However, the non-contact method has a problem in that productivity is insufficient, and there is a problem that it takes a lot of time to continuously process microholes. Researchers have developed an electron beam drilling equipment for continuous processing of fine holes, and a vaporization amplification sheet to increase the processing efficiency of the equipment. In this study, a cylindrical vaporization amplification sheet using room temperature curing type silicon was fabricated, and the metal distribution and thickness uniformity of the produced sheet were analyzed. In order to manufacture a cylindrical vaporization amplification sheet, an equipment capable of using centrifugal force was developed, and a sample in which metal powder was evenly distributed and a constant thickness was produced.

• Design & Manufacturing
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• v.17 no.4
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.141-148
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• 2017

A process comprising a hot extrusion process and a warm forging process was designed to form a T-shaped aluminum structural component with a high degree of difficulty by the plastic forming method. A circular cylindrical part was extruded with a hot extrusion process, and then an embossing part was formed with a warm forging process. The formability and the maximum load required for forming were then determined using a forming analysis program. The hot extrusion process was executed at $450^{\circ}C$ under the extrusion speed at 6 mm/s, while the warm forging process was executed at $260^{\circ}C$ under the forging speed at 150 mm/s. For both the processes, a condition by which friction would not be generated between the mold and the material was implemented. The analysis results showed that the load required for hot extrusion was 1,019 tons, while the load required for the warm forging was 534 tons. The T-shaped part was manufactured by using a 1,600 tons capacity press. The graphite lubricant was coated on the mold as well as the material. A forming experiment was performed under the same condition with the analysis condition. The measured values from the load cell were 1,210 tons in the hot extrusion process and 600 tons in the warm forging process.

• Design & Manufacturing
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• v.16 no.3
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• Design & Manufacturing
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• v.16 no.4
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• pp.46-51
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• 2022

The piercing process of creating holes in sheet metals for mechanical fastening generates high shear force. Real-time monitoring technology could predict tool damage and product defects due to this severe condition, but there are few applications for piercing high-strength aluminum. In this study, we analyzed the load signal to predict the punch's wear level during the process with a piezoelectric sensor installed piercing tool. Experiments were conducted on Al6061 T6 with a thickness of 3.0 mm using piercing punches whose edge angle was controlled by reflecting the wear level. The piercing load increases proportionally with the level of tool wear. For example, the maximum piercing load of the wear-shaped punch with the tip angle controlled at 6 degrees increased by 14% compared to the normal-shaped punch under the typical clearance of 6.7% of the aluminum piercing tool. In addition, the tool wear level increased compression during the down-stroke, which is caused by lateral force due to the decrease in the diameter of pierced holes. Our study showed the predictability of the wear level of punches through the recognition of changes in characteristic elements of the load signal during the piercing process.

• 한국금형공학회:학술대회논문집
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• 2008.06a
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• pp.203-208
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• 2008

Recently, the modern society in development and industrial growth is investing a lot of time and much effort to improvement and environment of life quality. Thus, the casting tape which uses environmentally friendly and human body friendly water hardening process Polymer is rapidly substituted for the gypsum cast product which has been plentifully used in medical treatment. Until currently, prior researches have a tendency to focusing the analysis about chemical creation expense and reaction quality rather than the issue about optimization of the process for this polymerization. In the polymerization process which has been accomplished with actual same chemical creation expense, there has been a problem which is the possibility of getting a different result. This is because the optimization of respectively control factors is not accomplished which affect at polymerization process. Therefore, this research sees the chemical qualities of casting tape Polymer, consequently selects the polymerization process which is suitable. And, by using a experimental design, this research will evaluate the affects which the respective factors have on remaining NCO and viscosity. futhermore, this research will carry out the process optimization which can get the above results.

• 한국금형공학회:학술대회논문집
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• 2008.06a
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• pp.45-50
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• 2008

In previous study, it showed that the MAP was greatly effective polishing process for magnesium plate. But it had lower efficiency than magnetic materials such as SM45C. It was very difficult to cut non-magnetic materials using the MAP process because the process was fundamentally possible by help of a magnetic force. This study aimed to verify analytically formation of the magnetic field in a case of the non-magnetic materials especially focused on magnesium plate. So, In this study, the magnetic density flux was predicted using simulation program. As a result, the magnetic density flux was lower at the center of pole on inductor than outside. It had same result on the experimental verification. And magnetic force was lower according to increase of working gap. So, to improve the magnetic force, permanent magnet was installed under the workpiece. In that case, the magnetic density flux not only at center but also at outside of pole was increased. Therefore, the efficiency of magnetic abrasive polishing was also increased. A design of experimental method was adopted for assessment of parameters' effect on the MAP results of magnesium plate for improving the magnetic force.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.3-7
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• 2006

For the purpose to improve and to automate designing of high-speed spindle units (SU's), we have developed the mathematical models and software to estimate SU performance characteristics, including the run-out of spindles running on ball bearings. In order to understand better the mechanics of high-speed SUs, the dynamic interaction of ball bearings and SU, and the influence of the bearing imperfections and SU's operational conditions on the run-out, we have carried out computer simulation and experimental studies. Through the study of SU's, we have found out that run-out of SU can vary drastically with variation of rpm. The influences of rotation speed and of accuracy parameters of bearings on the SU accuracy have the greatest importance. The influence of bearing preload has a secondary importance. Comparison of the results of these studies has demonstrated adequacy of the models and software developed to the real SU's.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.8
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• pp.50-55
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• 2020

This study investigates the injection molding of a plastic rack gear and focuses on deflections in the part. The causes of deflections were found and resolved through a trade-off study by injection molding analysis. Based on a warpage analysis, the fiber orientation was found to be a dominant factor in the occurrence of deflections. Changes in the part design and various injection conditions were analyzed for their effects in reducing deflections. Based on the trade-off study, a new part bottom design, injection time, and melt temperature were recommended. A trial injection was done for the new plastic rack gear, and measurements showed that its flatness surpassed that of the original part and met the specified requirement. The short injection time, low melt temperature, and symmetric similar configuration of the part contributed to the reduction in deflections. Therefore, optimized gate design and injection conditions as well as a new part design were validated through injection molding analysis in this study.

• Design & Manufacturing
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• v.17 no.2
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• pp.62-69
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• 2023

In this study, we conducted a study on the optimization of injection molding conditions to minimize deformation of plastic product. The charging management system housing of the vehicle was selected as the research subject. Melting temperature, cooling temperature, packing time, and packing pressure were selected as the main factors expected to affect the deformation of molded products. Each main factor was divided into 5 levels. Optimization of injection molding conditions to minimize deformation was performed using the Taguchi Method. We performed an analysis of variance (ANOVA) to identify significant factors affecting the deformation of plastic product. In order to select injection molding conditions that minimize deformation of plastic products, injection molding analysis was additionally performed for insignificant factors. We then compared the deformation of the molded part before and after optimization. As a result of comparing the injection analysis results of the basic conditions and the injection analysis results of the optimal conditions, it was confirmed that the amount of deformation after optimization was improved by about 10.9%.