• Journal of the Korean Society for Precision Engineering
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• v.12 no.4
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• pp.19-27
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• 1995

Face milling is required to study cutting process with a view of multipoint cutter. This experimental study mainly deals with the single and multi-insert cutting characteristics using coated tool. Because metal cutting of the single and multi-insert has a large relation to the improvement of productivity, the economic cutting process can be achieved by the analysis of proper metal cutting mechanism. Therefore, machining characteristics of face molling in this paper has been studied by investigating the role of different insert number which is concerned with mean cutting force, the RMS values of AE(acoustic emission) signal, tool life and surface roughness in milling SS 41 and SUS 304. The cutting force and AE signal are monitored to make an analysis of cutting process. The surface roughness of the specimens machined by inserts of different numbers is measured at different speeds, feeds and depth of cut. The width of flank wear is also observed.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.222-229
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• 1999

In order to regulate cutting torque in milling, monitoring system should be set to a certain threshold. Radial immersion ratio is an important factor to determine the threshold and should be estimated in process for automatic regulation. In this paper, on-line estimation of the radial immersion ration using spindle motor current in face milling is presented. When a tooth finishes sweeping, a sudden drop of cutting torque occurs. This torque drop is equal to cutting torque acting on a single tooth at the swept angle of cut and can be acquired form cutting torque signals. Average cutting torque per revolution can also be calculate form cutting torque signals. The ratio of cutting torque acting on a single tooth at the swept angle of cut to the average cutting torque per revolution is a function of the swept angle of cut and the number of teeth. Using the magnitude of this ratio, the radial immersion ratio is estimated. Identical algorithm is adopted to estimate the immersion ratio based on the spindle motor current measurement. The experiments performed under different cutting conditions show that the radial immersion ratio can be estimated within 10% error range by the proposed method using spindle motor current.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.178-185
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• 1999

In tool condition monitoring systems, parameters should be set to a certain threshold. In many cases, however, the threshold is dependent on cutting conditions, especially the radial immersion ratio. In this presented is a method of on-line estimation of the radial immersion ratio in face milling. When a tooth finishes sweeping, a sudden drop of cutting force occurs. The force drop is equal to the cutting force that acting on a tooth at the swept angle of cut and can be acquired from cutting force signals in feed and cross-feed directions. Average cutting force per tooth period can also be calculated from cutting force signals in two directions. The ratio to cutting forces in two directions acting on a tooth at a certain swept angle of cut and the ratio of average cutting forces in two directions per tooth period are functions of the swept angle of cut and the ratio of radial to tangential cutting forces. Using these parameters, the radial immersion ratio is estimated. Various experiments are performed to verify the proposed method. The results show that the radial immersion ratio can be estimated by this method regardless of other cutting conditions.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.3
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• pp.5-14
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• 1995

In recent years, the automization of cutting machine tools has been developed very fast. Hance, the in-process detection of cutting condition is very important for automatic manufacturing system in factory. Acoustic Emission(AE) has been widely used in monitoring the cutting conditions, because of high sensitivity of AE signal and low cost of AE equipment. This experimental study deals with the relations between AE signal, cutting force charcteristics and tool wear in the machining of SUS304. Face milling operation is used for the analysis between tool wear and AE signal.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.11
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• pp.100-105
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• 1996

In this paper presents a new technique (stain-telemetering) for detection of coated tool failure in face milling processes. In the cutter body, the strain signals received from the transmitter are transformed into frequency modulation(FM) signals in face milling processes. The receive which is placed near by the Vertical milling machine receives the FM signals, then the signals are sent to a computer, which shows the tool failure. In this paper, A on-line monitoring of the tool failure detection system based on the strain-telemetering apparatus has been represented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.225-229
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• 2000

Burrs formed during face milling operations are very hard to characterize like other machining burrs because there are many parameters which affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complicated combination effects between the parameters. In this paper, Taguchi method, which is a systematic optimization application of design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization. Optimized experimental conditions are provided to show the effectiveness of this approach.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.2949-2961
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• 1993

Dynamic cutting process can be represented by a closed-loop0 system consisted of machine tool structure and pure cutting process. On this paper, cutting system is modeled as a six degrees of freedom system using MARV(Modified Autoregressive Vector) model in face milling, and the modeled dynamic cutting process is used to predict dynamic cutting force component. Based on the double modulation principle, a dynamic cutting force model is developed. From the simulated relative displacements between tool and workpiece the dynamic force domponents can be calculated, and the dynamic force can be obtained by superposition of the static force and dynamic force components. The simulated dynamic cutting forces have a good agreement with the measured cutting force.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.39-52
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• 1995

In order to design and improve a new machine tool, there is a need for a better understanding of the dynamic cutting force. In this paper, the computer programs were developed to predict the dynamic cutting force by the mean specific cutting pressure in the face milling process. The simulated cutiing forces in X, Y, Z directions resulted from the developed dynamic cutting force model are compared with the measured cutiing forces in the time and frequency domains. The simulated cutting force model have a good agreement with the measured forces in comparison with those resulted from the existing cutting force model.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.3
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• pp.92-100
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• 1995

This experimental study is mainly investigated on the mean cutting forces and AE(acoustic emission) parameters in order to detect and estimate the tool failure in the pachinig of SUS304 by face milling Mean cutting forces and AE parameters can detect the tool failure in face milling. Effective detection parameters are AE RMS, AE energy, AE count, AE duration, and z-direction mean cutting force. From the analysis of cutting tool failure detection, the tool failure of face milling is caused by sudden increasing of the cutting force.