• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.114-118
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• 1996

Evaluation of cutting condition is one of the most important aspect to improve productivity and quality. In this study, the wear and cutting characteristics(cutting force, acoustic emission signal and surface roughness) of ceramic cutting tool for hardened die material(SKD11) were investigated by experiment. Flank wear on relief face of tool was occurred more dominant than crater wear on rake face. Experiments were performed under the various cutting condition.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.259-264
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• 1995

Recently, in order to achieve high flexibilty, monitoring and control strategies of a new type have been developed. This paper investigates the fesability of using scoustic emission signal analysis for the detection of built-up edge during machining. Results for maching SM45C steel show that the presence of a built-up edge can significantil affect the generation of acoustic emission in metal cutting. When the cutting speed comes to the conditions conducive to development of built-up edge, it is shown that the slope of curve-fitted AErms signal undergoes a change. The fesability of utilizing AErms in built-up edge sensing is sugested.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.11
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• pp.25-31
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• 1996

In this paper, three different types of commercial tools -P20, NC123K and ceramic- have been used to cut austempered ductile iron(ADI). In the austempered condition the materials are hard, strong and difficult to machine. Thus, we selected a optimum tool material among three different types of used tools in machining of austempered ductile iron. It was used acoustic emission (AE) to know cutting characteristic for selected tool and investigate characteristic of AE signal according to cutting condition and relationship between AE signal and flank wear land of the ceramic tool. The obtained results are as follows ; (1) The ceramic tool among three different types of tools is the best in machining austempered ductile iron. (2) In case of ceramic tool, the amplitude level of AE signal(AErms) is mainly affected by cutting condition and it is proportional to cutting speed. (3)There have been the relationship of direct proportion between the amplitude level of AE signal and flank wear land of the tool. (4) It was observed that the value of AErms was only affected by cutting speed. Therefore it is possible to in-process detec- tion of ceraic tool's wear in case the initial value of AErms at each cutting speed decided.

• Transactions of Materials Processing
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• v.18 no.2
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.112-118
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• 1997

Characteristics of AE(Acoustic Emission) signal is related to cutting conditions, tool materials, and tool geometry in metal cutting. Relation between AE signal and tool wear was investigated experimentally. Experiment is carried out by interrupted cutting for SCM420 workpiece with TiN coating tool on HSS material. AE RMS voltage and count per event were increased according to tool wear. The major results are as follows : 1) AE RMS value is nearly constant as cutting speed changes, but is rapidly increase as feed rate increases. 2) AE RMS value and Count per Event increase as tool wear increases. 3) It is more effective to monitor tool wear by Incremental rate of AE RMS value than by Incremental rate of count per event.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.1
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• pp.74-83
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• 1991

A study on the Correlation of Orthogonal Cutting Parameter (Cutting speed, Depth of cut, Feed Rate) and Acoustic Emission Signal. It is well known that acoustic emission (AE) is the emission of elastic wave resulting from the deformation and fracture of materials. This study estabished correlation of orthogonal cutting parameter and AE signal, and researched into in-process monitoring of tool wear and failure. The results are as follow; 1. AE RMS was under the influence of cutting speed but hardly influenced by depth of cut and feed rate. 2. AE RMS was under the influence of flank wear. 3. AE count rate increased by increased cutting speed. 4. AE RMS value was rapidly increased in 130 m flank wear.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.3
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• pp.150-159
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• 2000

In-process diagnosis of the cutting state is essential for the automation of manufacturing systems. Especially when the cutting process becomes unstable it induces self-exited vibrations a frequent case of poor tool life rough surface finish damage to the workpiece and the machine tool itself and excessive down time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time monitoring and controlling chatter. This paper describes the detection method of chatter vibration using cutting force in turning process. In order to detect a chatter vibra-tion the dynamic fluctuation of radial force is analyzed since this components is sensitive to the chatter. The envelope sig-nal of radial force has been calculated by the use of FIR Hilbert transformer and it was useful to classify the chatter signal from the dynamically unstable circumstances. It was found that the mode and the mode width were closely correlated with the chatter amplitude was well. Finally back propagation(BP) neural network have been applied to the pattern recognition for the classification of chatter signal in various cutting conditions. The validity of this systed was confirmed by the experiments under the various cutting conditions.

• 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.