• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.64-71
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• 2006

Ultraprecision machining and MEMS technology have been taken more and more important position in machining of microparts. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. Also, the method of micro-grooving using micro endmill is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This investigation deals with state monitoring using acoustic emission(AE) signal in the micro-grooving. Characteristic evaluation of AE raw signal, AE hit and frequency analysis for condition monitoring is presented. Also, 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 the fuzzy C-means algorithm.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.3
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• pp.1-7
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• 2016

The cutting processes used for monitoring engineering includes analysis and feedback about strange conditions, tools collision and tools wear in real time, for improving the working ratio of equipment and productivity. In this study, we proposed monitoring using profibus to increase the reliability as the most important factor for cutting monitoring. The profibus can increase the reliability of cutting monitoring for cutting torque of a main spindle motor and a feed motors through PLC-based interface.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.155-159
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• 1993

최근 많은 생산 시스템의 자동화에 있어서 기계의 상태 진단 및 감시는 설비의 중요도 및 특수성를 고려할때 매우 중요한 비중을 차지하게 되며, 생산 작업을 최적화할 수 있는적당한 제어기술의 필요성과 그에 대한 관심이 날로 증가 하고있는 실정이다. 특히 가공분야에서 많은 부분을 차지하고 있는 절삭가공작업은 기구의 구성이 복잡하고 불확정한 요인을 포함하고있으며 공구의 파손이나 채터진동에 의한 공작물의 정도의 변화가 급속히 발생하기 때문에 이를 위하여 인프로세서 감시가 절실히 요구되고 있다. 그러므로 비정상적인 절삭을 사전에 감지하여 대처함으로써 최적의 작업조 건하에서 안정된 절삭을 할 수 있고 공작기계의 유지, 보수에 경제적인 절감을 기대할 수 있다. 본 연구에서는 2차원 절삭과정중에 발생하는 채터진도에 있어서 절삭 파라메타와 AE 신호와의 관계를 실험적으로 규명하며, AE를 이용한 절삭과정을 모니터링 할 수 있는 방법에 대하여 연구한다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.454-459
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• 2000

The high hardened materials that are remarkable in aspects of durability have been used for die and mold industry. As the high hardened materials are hard to machine, the high-speed machining is essential to manufacture these materials. Currently, in the general turning and milling, experiments to the tool wear monitoring have studied, but those have not applied in high-speed machining. In this study, the cutting mechanism was analysed by the cutting force according to cutting conditions, and the parameters to monitor the tool wear were selected from the tendency of the cutting force and acceleration according to cutting length in the high-speed machining of the high hardened materials(STD11).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.6
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• pp.43-50
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• 2010

This study aims to analyze the structural safety by comparing deformation and equivalent stress of door with a stiffener or no stiffener when the door crashes against something in case of overturn. Three types are classified on the basis of the no stiffener model in the vehicle door. One is the type which has a stiffener. Another is the type which has no stiffener and the other is the type which has a hole in the stiffener. These three types are compared with each other by analyzing. This side door of vehicle is the automotive part about the kind of vehicle as Mercedes Benz E-Klasse scaled down as 1/18 times as the real size. The study model of vehicle door is modelled by CATIA program and it is analyzed by ANSYS.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.75-81
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• 1997

Automatic monitoring the cutting state is one of the important problems to increase the reliability of modern machining processes. In this study, cutting force signals were used in order to monitor the tool wear and fracture in the turning process. Turning experiments were performed using cemented carbide insert tools(K20) and STS304 steel as a workpiece. Cutting force signal characteristics and histogram analysis method were used to recognize the cutting states. It was found that tool wear and fracture can be diagnosed from the cutting force signal coefficient of variation(C.V.) and histogram analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.47-51
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• 1997

The high speed machining which can improve the production and quality in machining has been adopted remarkably in dietmold industry. As the speed of machine tool spindle increases, the machinability evaluation and monitoring of high speed machining is necessary. In this study, the machinability of 30, 000rpm class spindle was evaluated by using the developed tool dynamometer and the machining properties of high hardened and toughness materials in high speed were examined. Finally, the in-process monitoring technologies of tool wear were presented through the prediction by the experimental formula and pattern recognition by the neural network.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.334-339
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• 2004

Ultraprecision machining and MEMS technology have been taken more and more important position in machining of microparts. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. 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 investigation deals with state monitoring using acoustic emission(AE) signal in the micro-grooving. Characteristic evaluation of AE raw signal, AE hit and frequency analysis for state monitoring is also presented in the paper.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.2
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• pp.7-12
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• 2012

In order to cope with the requirements of smaller patterns, larger surfaces and lower costs in the fields of displays, optics and energy, greater attentions are now being paid to the development of micro-pattern machining technology. Compared with flat moulds, large drums with micro patterns (roll moulds) have the advantages of short delivery, ease of manufacturing larger surfaces, and continuous moulding. This paper introduced the machining process technology of the roll moulds for display industry. The environmental effects were discussed and the importance of temperature maintenance was experimentally emphasized. The real time monitoring system for micro machining was introduced. A commercial solution was used to simulate the micro grooving and a deformation model of micro machined pattern was finally introduced.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.14-21
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• 1998

The in-process detection of the state of cutting tool is one of the most important technical problem in Intelligent Machining System. This paper presents a method of detecting the state of cutting tool in turning process, by using Artificial Neural Network. In order to sense the state of cutting tool. the sensor fusion of an acoustic emission sensor and a force sensor is applied in this paper. It is shown that AErms and three directional dynamic mean cutting forces are sensitive to the tool wear. Therefore the six pattern features that is, the four sensory signal features and two cutting conditions are selected for the monitoring system with Artificial Neural Network. The proposed monitoring system shows a good recogniton rate for the different cutting conditions.