• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.9-14
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• 1997

From the experimental study of wire-cut Electric Discharge Machining for alloyed steel and tungsten carbide, the characteristics such as hand drum form has been observed and evaluated for various conditions. Hand drum form can be improved when gap voltage and spark cycle become smaller, their thickness become thinner, wire tension become larger and number of cutting is done so many times. When wire-cut 60mm thickness tungsten carbide in normal condition, Hand drum form becomes larger due to the low conductivity inducing cobalt composite rising by electrolysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.26-31
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• 1994

The analysis of acoustic emission signals generated during machining has been proposed as a technique for studying both the fundamentals of the cutting process and process and as a methodology for detecting tool fracture on line. In this study, AE signals detected during End Milling were applied as the experimental test to sensing tool fracture on the CNC vertical milling machine. Because automatic monitoring of the cutting condition is one of the most important technologies in machining, the in-process detection of cutting tool life including fracture has been investigated by performing experimental test.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.137-142
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• 1996

Magnetic-electrolytic-abrasive polishing system(MEAPS) was developed for machining national standard electrode and its finishing characteristics was analyzed. The paper describes the operational principle of MEAP system by experimental results. The finishing characteristics and optimal finishing condition for national standard electrodes were experimented and analyzed. As a result, MEAPS can improve straightness as well as surface roughness.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.104-118
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• 1998

In this paper, the motion of ballscrew and shape of workpiece are the main objective variables varying with load conditions. To verify feed mechanism in NC lathe, the monitoring system is designed and cutting condition variables are spindle speed depth of cut and feed. During machining, rotation number of ballscrew motion of ballscrew in direction to gravity center and cutting force are measured. After machining, the roughness of workpiece is measured.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.162-167
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• 2005

Recently, the advanced industries using micro parts are rapidly growing. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro to micro parts. Also, the method of micro-grooving using micro endmilling is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This study deals with condition monitoring using acoustic emission(AE) signal in the micro-grooving. First, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by using the fuzzy C-means algorithm, which is one of the methods to recognize data patterns. These result is effective monitoring method of micro endmill state by the AE sensing techniques which can be expected to be applicable to micro machining processes in the future.

• 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 Manufacturing Technology Engineers
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• v.4 no.2
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• pp.46-53
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• 1995

In this study, Wear of a ceramic cutting tool for hardened STD11 steel was investigated. Under the finish machining condition. DOC notch wear of a ceramic cutting tool was mostly occurred earlier than flank and crater wear were proceeded. The relations of DOC notch wear, which was characteristically produced at the beginning of cutting. to cutting speed, feed, depth of cut, and nose radius of a ceramic cutting tool were examined. Effective approach angle, which is a function of cutting conditions, and boundary area were suggested, and then the influence of those was investigated, The following conclusions were obtained: (1)as cutting speed was increasing. DOC notch wear was decreasing (2) the cutting condition that magnitude of slendermess ratio was made small, was favorable for DOC notch wear, (3) as depth of cut was smaller, the influence of feed on DOC notch wear was also smaller, (4) DOC notch wear was mainly influenced by effective approach angle, but by boundary area in the range of low feed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.161-164
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• 1995

Nonlinear analysis of various phenomena has been developed with improvement of computer. The characteristics form nonlinear analysis are available in monitoring and diagnosis state of system. There are many nonlinear property in cutting process, but nonlinear signals have been considered as noise. In this study, nonlinear analysis technique is applied and it will be verified that cutting force is chaos by calculating Lyapunov exponents,fractal dimension and embedding dimension. The relation between characteristic parameter calculated form sensor signal and various cutting condition is investigated.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.53-60
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• 1998

In this study, it is experimented to find factors effecting surface roughness using the system of experiments. in the mirror surface finishing system. (1) The film feed and oscillation frequency in $40{\mu}m$ abrasive film, grinding speed in $30{\mu}m$, and machining time in $15{\mu}m$15 are the main factors effecting the surface roughness. (2) Applying the optimal finishing condition to $40{\mu}m$, $30{\mu}m$, $15{\mu}m$ abrasive finishing film in sequence, it is possible to obtian about Ra 10 nm surface roughness on SM45C workpiece. (3) Application of the system of experments to the micro abrasive grain film finishing was very effective method in the extraction of main factor and optimal condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.269-273
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• 1997

In order to maker unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstations to provide the required intelligence of the expert. This paper deals with condition monitoring for chatter, tool wear and fracture during turning operation. To develop economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique were proposed. We suppressed chatter by stability control methodology, which was studied through manipulation of spindle speeds regarding to chatter frequencies. It was shown that tool wear and fracture were identified and to be estimated by using the wear indices. The validity of the proposed system was confirmed through the large number of cutting tests.