• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.644-653
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• 1998

In resistance spot weld, the assurance of weld quality has been a long-standing problem. Since the weld nuggets if resustance spot welding form between the workpieces, visual detection of defects in usually impossible. Welding quality of resistance spot welding can be verified by non destructive and destructive inspections such as X-Ray inspection and testing of weld strength. But these tests, in addition to being time-consuming and costly, can entail risks due to sampling basis. The purpose of this study is the development of the monitoring system based on fuzzy inference, aimed at diagonosis of quality in resistance spot welding. The fuzzy inference system consists of fuzzy input variables, fuzzy membership functions and fuzzy rules. For inferring the welding quality(strength), the experimental data of the spot welding were acquired in various welding conditions with the monitoring system designed. Some fuzzy input variables-maximum, slop and difference values of electrode movement signals-were extracted from the experimental data. It was confirmed that the fuzzy inference values of strength have a .${\pm}$5% error in comparison with actual values for the selected welding conditions(9-10.5KA, 10-14 cycle, 250-300 $kg_f$). This monitoring system can be useful in improving the quality assurance and reliability of the resistance spot welding process.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.30 no.5
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• pp.301-306
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• 2017

Wire electrical discharge machining (WEDM) process was evaluated to slice Silicon (Si) for various applications. Specifically, various Si workpieces with various resistances, such as single and multi crystalline Si bricks and wafers were used. As conventional slicing processes, such as slurry-on or diamond-on wire slicing, are based on mechanical abrasions between Si and abrasive, there is a limitation to decrease the wafer thickness as well as kerf-loss. Especially, when the wafer thickness is less than $150{\mu}m$, wafer breakage increases dramatically during the slicing process. Single crystalline P-type Si bricks and wafers were successively sliced with considerable slicing speed regardless of its growth direction. Also, typical defects, such as microcracks, craters, microholes, and debris, were introduced when Si was sliced by electrical discharge. Also, it was found that defect type is also dependent on resistance of Si. Consequently, this study confirmed the feasibility of slicing single crystalline Si by WEDM.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.16-23
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• 2017

For most machine tools, it is necessary to remove chips and coolant oil because it they will continue to be created during the manufacture of workpieces. Existing products that are in use are installed and used as they reflect depending on the characteristics of each device separately. This study proposes a method to remove the security chip as well as developing an integrated system capable of reducing coolant damage. The Leverage AutoCAD and CATIA program was used for 2D and 3D design, shapes were identified by utilizing the KeyShot program, and the load and displacement analysis of the development apparatus was performed utilizing the ANSYS program. After the prototype underwent sufficient design review, the mixed oil separation device had a complete sensor control program using the LabVIEW program. The chip design process for transferring experiments and experiments on the mixed oil cooling device were developed for performance tests of the product. The final product resulted in an increase in space utilization during commercialization, reduced installation costs, and caused social effects such as pulmonary flow reduction, which, through the economic costs, reduces pollution, resulting in various benefits to the industry, such as deceased errors in the workplace decreases.

• Advances in materials Research
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• v.6 no.2
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• pp.169-184
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• 2017

Electro-Discharge machining (EDM) is a thermal process comprising a complex metal removal mechanism. This method works by forming of a plasma channel between the tool and the workpiece electrodes leading to the melting and evaporation of the material to be removed. EDM is considered especially suitable for machining complex contours with high accuracy, as well as for materials that are not amenable to conventional removal methods. However, several phenomena can arise and adversely affect the surface integrity of EDMed workpieces. These have to be taken into account and studied in order to optimize the process. Recently, artificial neural networks (ANN) have emerged as a novel modeling technique that can provide reliable results and readily, be integrated into several technological areas. In this paper, we use an ANN, namely, the multi-layer perceptron and the back propagation network (BPNN) to predict the mean surface roughness of electro-discharge machined surfaces. The comparison of the derived results with experimental findings demonstrates the promising potential of using back propagation neural networks (BPNNs) for getting a reliable and robust approximation of the Surface Roughness of Electro-discharge Machined Components.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.51-57
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• 2001

A light beam reflected from a machined surface generally containes information concerning about its surface roughness. This study examines and proposes a surface roughness measurement technique for on-machine measurement of machined surfaces. The technique is based on the measurement of a reflected laser beam pattern and the statistical analysis of its light intensity distribution. The surface roughness was found to be closely related to the standard deviation of the light intensity on the primary axis of the reflected pattern. An image acquisition device is made up of a laser diode, a half mirror, a screen, and a CCD camera. The exact image with the primary and secondary axes of a reflected laser beam pattern is calculated through such image processing algorithm as thresholding, edge detection, image rotation, segmentation, etc. A median filter and a surrounding light correction algorithm are improve the image quality and reduce the measuring error. Using the developed measuring device the effect of screen materials and workpiece and workpiece materials was investigated. Experimental results regarding to relatively high-quality surfaces machined by grinding, polishing, lapping processes have shown the measurement error is within 10% in the range of $0.1{mu}m~0.8{\mu}m R_q.$Therefore, the proposed method is thought to be effectively used when quick measurements is needed with workpieces fixed on the machine.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1456-1464
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• 1993

The achievable machining accuracy depends upon the level of the micro-engineering, and the dimensional tolerances in the order of 10 nm and surface roughness in the order of 1 nm are the accuracy targets to achieved today. Such requirements cannot be satisfied by the conventional machining processes. Single point diamond turning is one of the new techniques which can produce the parts with such accuracy limits. The aims of this thesis are to get a better understanding of the complex cutting forces. A cutting model for describing the influence of cutting conditions (cutting speed, feedrate and depth of cut), material properties of the workpiece and tool geometry has been proposed after estimating the two cutting force models-the Recht model and the Dautzenberg model. The experiments with Al-alloy workpieces, which have been carried out in order to estimate the models, show that the proposed model in this thesis is better than the two models. As the depth of cut and feedrate are increased in the operations settings (depth of cut 8-100$\mu{m}$, feedrate 8-140$\mu{m}$/rev, and cutting speed 8 m/sec), the relation of dimensionless cutting forces from experiments are similar to the proposed model. With the undeformed chip area of $30-80{\times}10^{2}$\mu{m}^2$, the experimental cutting forces accord with the force prediction.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.63-68
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• 2017

This study determines the selection of an appropriate jig material for the blade edge of the medical sapphire knife. The physical properties of the jig material affects the edge shape and chipping phenomenon in machining of the medical sapphire knife. If a grinding wheel is used, brittle workpieces such as sapphire are easily damaged by the propagation of cracks because the grinding force significantly increases. It is important to constantly maintain the grinding force in the grinding process of the brittle materials. The grinding force can be kept constantly by inducing the elastic deformation of the Jig material because the elastic deformation of brittle work-piece is negligibly low. The chipping phenomenon may be reduced by selecting the proper Jig material. Aluminum, copper, stainless steels and carbon steel were used as Jig materials. The experiment was conducted using a cast iron grinding wheel, which was installed on a conventional grinding machine with the ELID grinding system. The thickness and width of the chipping area were measured using an optical microscope and FE-SEM to analyze the shape of the blade edge. According to the experiment result, the chipping phenomenon decreased, and the sharp edge was formed when the jig materials with low elastic modulus were used.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.1
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• pp.105-111
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• 2013

The spindle is the main component in machine tools. The static and dynamic characteristics of the spindle directly affect the machining accuracy of workpieces. The characteristics of the spindle depend on the shaft size, bearing span, built-in motor location, and so on. Therefore, the appropriate selection of these parameters is important to improve the spindle characteristics. This paper presents the analysis of the static and dynamic characteristics and optimization design of a 40,000-rpm high-speed spindle. Statistical analysis for optimization and finite element analysis were performed. This study uses the response surface method to optimize the objective function and design factors. The targets are the natural frequency and displacement. The design factors are the shaft length, shaft diameter, bearing span, and motor location. The optimized design provides better results than the initial model, and these results are expected to improve the static and dynamic characteristics of the spindle.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.161-167
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• 2020

In the process of cutting large aircraft parts, the tool may be abnormally worn or damaged due to various factors such as mechanical vibration, disturbances such as chips, and physical properties of the workpiece, which may result in deterioration of the surface quality of the workpiece. Because workpieces used for large aircrafts parts are expensive and require strict processing quality, a maintenance plan is required to minimize the deterioration of the workpiece quality that can be caused by unexpected abnormalities of the tool and take maintenance measures at an earlier stage that does not adversely affect the machining. In this paper, we propose a method to indirectly monitor the tool condition that can affect the machining quality of large aircraft parts through real-time monitoring of the current signal applied to the spindle motor during machining by comparing whether the monitored current shows an abnormal pattern during actual machining by using this as a reference pattern. First, 30 types of tools are used for machining large aircraft parts, and three tools with relatively frequent breakages among these tools were selected as monitoring targets by reflecting the opinions of processing experts in the field. Second, when creating the CNC machining program, the M code, which is a CNC auxiliary function, is inserted at the starting and ending positions of the tool to be monitored using the editing tool, so that monitoring start and end times can be notified. Third, the monitoring program was run with the M code signal notified from the CNC controller by using the DAQ (Data Acquisition) device, and the machine learning algorithms for detecting abnormality of the current signal received in real time could be used to determine whether there was an abnormality. Fourth, through the implementation of the prototype system, the feasibility of the method proposed in this paper was shown and verified through an actual example.

• Industry Promotion Research
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• v.8 no.3
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• pp.1-7
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• 2023

This study is an empirical study on the influence of workpieces on the research results until it became a marketing field, and a total of 94 questionnaires were used as research analysis data for the Chungcheongnam-do area. As a result of the analysis, first, among marketing orientations, business orientation was found to have a significant effect on growth (β=.405) and customer satisfaction (β=.330). Customer satisfaction of business orientation shows a low number, so there is a need for improvement. Second, customer satisfaction and growth showed a high correlation coefficient of .746, and showed a significant correlation of p<.01 or higher, so the correlation between variables was confirmed to be appropriate. Third, it was confirmed that there was a significant difference between groups in customer satisfaction according to the age and work experience of the survey subjects. The significance probability was .006, which showed a statistically significant result. This study is meaningful in providing basic data for improving the management strategy and actual performance of SMEs as a research on marketing orientation and management performance.