• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.53-63
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• 2022

Recently, the use of aluminum components in the reduction of the vehicle weight to improve fuel efficiency and reduce carbon dioxide emissions has increased. In the aluminum machining cutting process, hole-making is an important process that accounts for 30% of the machining process. Although many studies have been conducted using the continuously advancing hole processing technology, studies on the machinability of the tool depending on the type of chuck on the workpiece are still lacking. In this study, the machining performance of cemented carbide burnishing drills was compared and analyzed according to chuck type. The burnishing drill was used to create a hole in the AL6061 workpiece, and the surface roughness and dimensional accuracy of the hole were examined according to the type of chuck while monitoring the spindle load.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.142-151
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• 1993

An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.101-104
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• 1995

A acoustic emission (AE) sensor has been used to monitor tool were during milling process. The relation between tool wear and AE RMS (Root mean Square) signal was investigated experimentally. A avaliable monitoring index for monitoring toolwear was newly extracted form AE RMS. And on-line monitoring program was developed. The proposed monitoring system has verified experimentally by roughing end milling titanium alloy with TIN coated HSS tool.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1324-1327
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• 1996

This paper presents an open architecture controller (OAC) for machining systems and describes the OAC testbed at Seoul National University. Because our OAC is designed for fully open systems, it does not depend on any specific hardware or software components. This openness includes software reusability which enables integration of a wide range of monitoring and control features. In addition to openness, our OAC system provides guaranteed real-time performance, an important requirement for advanced manufacturing.

• Journal of IKEEE
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• v.23 no.1
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• pp.22-28
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• 2019

This paper presents the monitoring method of machining error and quality check to improve the productivity of boring manufacturing process. Machining error usually appears as the offset of spatial location of actual cutting path compared to ideal cutting path. In order to monitor an error of workpiece, multiple factors affecting quality of boring, such as distortion of workpiece, clamping error, radial rotation error of the spindle and motion error of machine tools, were took into account. To verify the productive quality, we propose the quality check system. The system based on IT convergence analyzes the process error rate and saves the analyzed data in memory. Also, these play important roles in detecting an inferior production goods and can decrease the production cost and loss of bearing.

• Journal of the Korean Society of Safety
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• v.16 no.2
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• pp.22-26
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• 2001

The machining process on be considered as a planned interaction of the workpiece, the tool and the machine tool. In an unmanned situation, the results of this interaction are to be continuously monitored so that any changes in the machining environment on be sensed to corrective actions. In order to design the process monitoring system for unmanned manufacturing, the identification of chip formation is proposed. The system proposes the method of using acoustic emission(AE) signal analysis to identify the chip formation during cutting.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.971-974
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• 2001

In this study, the static and dynamic characteristics of endmilling process was modelled and the analytic realization of chatter mechanism was discussed. In this regard, We have discussed on the comparative assessment of recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental work were performed to show the malfunctional behaviors. For this purpose, new recursive(RLSM) were adopted for the on-line system identification and monitoring of a machining process, we can apply these new algorithms in real process for detection of abnormal chatter. Also, the stability lobe of chatter was analysed by varying parameter of cutting dynamices in regenerative chatter mechanics.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.76-83
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• 2001

In this study, the static and dynamic characteristics of turning process was modelled and the analytic realization of regen-erative chatter mechanism was discussed. In this regard, we have discussed on the comparative assessment of recursive times series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision turning operation. In this study, simulation and experimental work were performed to show the malfunction behaviors. For this purpose, new Recursive Extended Instrument Variable Method(REIVM) was adopted for the on-line system identification and monitoring of a machining process. Also, we can apply REIVE algorithms in real process for the detection of chatter frequency and dynamic property and analyze the stability lobe of the system by changing a parameter of cutting dynamics in regenerative chatter mechanics, if it is stable or unstable, Also, The stability lobe of chatter was analysed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.131-134
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• 1995

The high efficiency and accuracy in machining the die material can be abtained in high speed machining, so it is necessary to analyze the mechanism of high speed cutting process : cutting force, flank wear. The tool dynomometer with high natural frequency is newly developed. With this device, the mechanism of high speed cutting process is investigated according to speed and feedate.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.435-440
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• 2000

In this study, we aims to develop the machining technology for the ultra precision surface and profile accuracy. For this purpose, we construct the electrolytic in process grinding system (ELID grinding) and apply to the cylindrical and internal grinding. Through the various machining experiments such as SCM steel., ceramics, tungsten carbide etc., we have obtained nanometer surface roughness. And we have applied this mirror grinding technique to hydraulic manual valve and mold core of mini disk optical pick-up base. For the development of fine mechanical part machining technology, e have made multi fiber optical connector using fine grinding technology. And constructed micro drilling system with process monitoring system which is possible to drill 50${\mu}{\textrm}{m}$ diameter hole.