• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.86-89
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• 2002

In NC machining, the ability to automatically generate an optimal process plan is an essential step toward achieving automation, higher productivity, and better accuracy. For this ability, a system that is capable of simulating the actual machining process has to be designed. In this paper, a milling process simulation system for the general NC machining was presented. The system needs first to accurately compute the cutting configuration. ME Z-map(Moving Edge node Z-map) was developed to reduce the entry/exit angle calculation error in cutting force prediction. It was shorn to drastically improve the conventional Z-map model. Experimental results applied to the pocket machining show the accuracy of the milling process simulation system.

• Transactions of Materials Processing
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• v.18 no.4
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• pp.323-328
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• 2009

The prediction of drawing load is very important in the drawing process. However, it is not easy to calculate the drawing load for the shape drawing process through a theoretical model because of a complex arbitrary final cross section shape. The purpose of this study is to predict drawing load in shape drawing process. The cross section of product is divided with small angle as much as similar with fan-shape. The drawing load of each section was calculated by theoretical model of round to round drawing process. And the shape drawing load was determined by summation of drawing load of each section. The effectiveness of the proposed method was verified through the FE analysis and shape drawing experiment. It had a good agreement between proposed method, FE analysis and experiment within about 3% errors.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.821-825
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• 2000

Drawing is one of the oldest metal forming operations and has major industrial significance. This process allows excellent surface finishes and closely controlled dimensions to be obtained in long products that have constant cross sections. In drawing of the high carbon steel wire, exit speeds of several hundreds meters per minute are very common. Drawing is usually conducted at room temperature using a number of passes or reductions through consequently located dies. In multi-stage drawing process like this, temperature rise in each pass affects the mechanical properties of final product such as bend, twist and tensile strength. In this paper, therefore, to estimate the wire temperature in multi-stage wire drawing process, wire temperature prediction method was mathematically proposed. Using this method, temperature rise at deformation zone as well as temperature drop between die exit and the next die inlet were calculated.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.1
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• pp.90-96
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• 2013

During the cold forming, due to high working pressure acting on the die surface, failure mechanics must be considered before die design. One of the main reasons of die failure in industrial application of metal forming technologies is wear. Die wear affects the tolerances of formed parts, metal flow and costs of process etc. The only way to control these failures is to develop methods which allow prediction of die wear and which are suited to be used in the design state in order to optimize the process. In this paper, the wear experiments to obtain the wear coefficients and the upsetting processes was accomplished to observe the wear phenomenon during the cold forming process. The analysis of upsetting processes was accomplished by the rigid-plastic finite element method. The result from the deformation analysis was used to analyse the die wear during the processes and the predicted die wear profiles were compared with the measured die wear profiles.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.3
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• pp.241-245
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• 2001

In this paper, we present parameter optimization technique for GaAs/AlGaAs multiple quantum well avalanche photodiodes used for image capture mechanism in high-definition system. Even under flawless environment in semiconductor manufacturing process, random variation in process parameters can bring the fluctuation to device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. This paper will first use experimental design and neural networks to model the nonlinear relationship between device process parameters and device performance parameters. The derived model was then put into genetic algorithms to acquire optimized device process parameters. From the optimized technique, we can predict device performance before high-volume manufacturign, and also increase production efficiency.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.9
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• pp.741-746
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• 2009

Compare to conventional Indium Tin Oxide (ITO) film deposition methods, cesium assisted sputtering method has been shown superior electrical, mechanical, and optical film properties. However, it is not easy to use cesium assisted sputtering method since ITO film properties are very sensitive to Cesium assisted equipment condition but their mechanism is not yet clearly defined physically or mathematically. Therefore, to optimize deposited ITO film characteristics, development of accurate and reliable process model is essential. For this, in this work, we developed ITO film deposition process model using neural networks and design of experiment (DOE). Developed model prediction results are compared with conventional statistical regression model and developed neural process model has been shown superior prediction results on modeling of ITO film thickness, sheet resistance, and transmittance characteristics.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.6
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• pp.681-689
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• 2009

Disk grinding was often applied to deburring process in order to enhance the final product quality. Inherent chamfering capability of the flexible disk grinding process in the early stage was analyzed with respect to various process parameters including workpiece length, wheel speed, depth of cut and feed. Initial chamfered edge defined as arc zone was characterized with local radius of curvature. Averaged radius and arc zone ratio was well evaluated using neural network system. Additional neural network analysis adding workpiece length showed enhance performance in predicting arc zone ratio and curvature radius with reduced error rate. A process condition design parameter was estimated using remaining input and output parameters with the prediction error rate lower than 2.0% depending on the relevant input parameter combination and neural network structure composition.

• Journal of the korean Society of Automotive Engineers
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• v.3 no.3
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• pp.49-57
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• 1981

A cycle simulation of 4 cycle spark ignition engine using methanol-water blend as a fuel has been developed for study of prediction of power, specific fuel consumption, mean effective pressure and thermal efficiency. One-dimensional flow model for intake process and thermodynamic model for combustion process were selected. After, performance test was made with conventional engine which was modified in consideration of fuel properties. And computational results by simulation have been compared with experimental results. As the agreement between computational and experimental results was good, prediction of engine performance by was possible.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.13-17
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• 1993

Analytical models for the prediction of the size of hardened zone in laser surface hardening are presented. The models are based on the solutions to the problem of three-dimensional heat flow in plates with infinite thickness. The validity of the model was tested on medium carbon steel for Gaaussian mode of beam. Then the model for rectangular beam was used for the prediction of the size of harened zone on various hardening process parameters. From the calculation results it appeared that the size and shape of the hardened zone are strongly dependent on process parameters suchas beam mode, beam size, and traverse speed.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.1
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• pp.31-40
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• 1983

An uncertain dynamic evolving process has been a continuing challenge to decision problems. The dynamic random variable (drv) changes which characterize such a process are very important for the decision-maker in selecting a course of action in a world that is perceived as uncertain, complex, and dynamic. Using this subjective point prediction algorithm based on a modified recursive filter, the decision-maker becomes to have periodically changing plausible points with the passage of time.