• 한국정밀공학회지
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• 제6권4호
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• pp.61-70
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• 1989

A new analytical method is proposed to monitor the chip form of cutting forces applying the techinque of signal process. Cutting experiments are carried out under various cutting conditons and cutting forces are measured in-processing through Tool Dynamometer. In this report, auto-correlation functions, frequency characteristics of dynamic force, high frequency distribution and Peak/RMS values are calculated from the measured cutting forces, and the concept of method is also discussed. The experimental results show that six types of the form of chips are possible to classify from the signal of cutting forces not related to cutting conditions.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.73-78
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• 1994

Wear and fracture mode of ceramic tool for hardened SKD11 steel was investigated by face milling in this study. The cutting force and Acoustic Emission(AE) signal were utilized to detect the wear and fracture of ceramic tool. The following conclusions were obtained : (1) The wear and fracture modes of ceramic tool are characterized by three types: \circled1wear which has normal wear and notch wear, \circled2 wear caused by scooping on the rake face, \circled3 large fracture caused by thermal crack in the rake face. (2) The wear behaviour of ceramic tool can be detected by the increase of mean cutting force and the variation of the AE RMS voltage. (3) The catastrophic fracture of ceramic tool can be detected by the cutting force(Fz-component). (4) As the hardness of work material increased, Acoustic Emission RMS value and mean cutting force(Fz) increased linearly, but the tool life decreased.

• 한국기계가공학회지
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• 제1권1호
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• pp.29-37
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the diagnosis of grinding conditions in grinding process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. STD11 workpiece was 85 times of machined pieces cut by the WA wheel and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At dressing time, the approximation signals were slowly increased and 45 machined times noticed dressing time.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.1063-1066
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• 한국생산제조학회지
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• 제9권5호
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• pp.157-164
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• 2000

A machine tool generally has some serious stability problems in the form of tool chatter during the cutting process. Chatter vibration deteriorates the surface finish, reduce tool and machine life, accelerates machine tool system component wear, and may lead to an unacceptable noise sound in the working environment. In this study, the behavior of spectral density of AE signal and principal cutting force signal in order to monitor the chatter vibration in the cutting process has been investigated. From the results, the reliability of proposed monitoring method has been confirmed.

• 반도체디스플레이기술학회지
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• 제15권4호
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• pp.86-91
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• 2016

End milling is an important and common machining operation because of its versatility and capability to produce various profiles and curved surfaces. This paper presents an experimental study of the cutting force variations in the end milling of SM25C with HSS(high speed steel) and carbide tool. This paper involves a study of the Taguchi design application to optimize cutting force in a end milling operation. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer resources than a factorial design. This study included feed rate, spindle speed and depth of cut as control factors, and the noise factors were different cutting tool in the same specification. An orthogonal array of $L_9(3^3)$ of ANOVA analyses were carried out to identify the significant factors affecting cutting force, and the optimal cutting combination was determined by seeking the best cutting force and signal-to-noise ratio. Finally, confirmation tests verified that the Taguchi design was successful in optimizing end milling parameters for cutting force.

• 한국생산제조학회지
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• 제7권6호
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• pp.90-96
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• 1998

The ductile cast iron is austempered at 300, 350 and 40$0^{\circ}C$ temperature in order to investigate the basic factors for monitoring drill wear in automatic production process, and cutting force and AE RMS signals are measured with changing cutting condition for ADI(Austempered Ductile Cast Iron) with different mechanical properties. The signals of cutting force were influenced by cutting speed and feedrate greatly. On the other hand AE RMS signals are influenced by cutting speed where as it is not related with feedrate. As the depth of drilling increases, cutting force shows a slow increase and the value of AE RMS increases until the range of h/d=4. But over the range it increases greatly due to an amount of chip discharge and friction with inner wall of drilling hole, etc. As the drill diameter increases at a constant depth of drilling. Cutting force increases linearly, but the level of AE RMS does not increases linearly due to circumferential velocity and great influence of h/d.

• 한국정밀공학회지
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• 제7권2호
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• pp.47-57
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• 1990

In-process recognition of the cutting states is one of the very important technologies to increase the reliability of mordern machining process. In this study, practical methods which use the dynamic component of the cutting force are proposed to recognize cutting states (i.e. chip formation, tool wear, surface roughness) in turning process. The signal processing method developed in this study is efficient to measure the maximum amplitude of the dynamic component of cutting force which is closely related to the chip breaking (cut-off frequency : 80-500 Hz) and the approximately natural frequency of cutting tool (5, 000-8, 000 Hz). It can be clarified that the monitoring of the maximum apmlitude in the dynamic component of the cutting force enables the state of chip formation which chips can be easily hancled and the inferiority state of the machined surface to be recognized. The microcomputer in-process tool wear monitor- ing system introduced in this paper can detect the determination of the time to change cutting tool.

• 반도체디스플레이기술학회지
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• 제16권2호
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• pp.79-84
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• 2017

This paper outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in end milling when machining STS304 with TiAlN coated SKH59 tool under up and down end milling conditions. The end milling parameters evaluated are depth of cut, spindle speed and feed rate. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to analyze the effect of these end milling parameters. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer resources than a factorial design. An orthogonal array of $L_9(33)$ was used. The most important input parameter for cutting force, however, is the feed rate, and depending on the cutter rotation direction. Finally, confirmation tests verified that the Taguchi design was successful in optimizing end milling parameters for cutting force.

• 한국정밀공학회지
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• 제16권3호통권96호
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• pp.18-24
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• 1999

ThisPaper investigates the feasibility of using acoustic emission signal analysis for the detection of built-up edge during machining. Experiments were conducted on a CNC-lathe using conventional carbide insert tools under various cutting conditions. The cutting forces were also measured for comparisons. Experimental evidence is presented which indicates that the presence of a built-up edge can significantly affect the generation of acoustic emission in metal cutting. It is shown that under conditions in which a built-up edge is generated, the variation of $AE_{rms}$ signal with cutting speed can be quite different from the generally accepted linear, monotonic increase as previously reported. The feasibility of utilizing $AE_{rms}$ in built-up edge sensing is suggested.