• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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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.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.136-142
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• 1996

Automatic monitoring of cutting process is one of the most important technology in machining. AE sensing technology has been applied to monitoring process and proved to be effective in detecting tool abnor- malities such as tool wear and fracture. In this experimental study. AE signals were detected from the tool holder for continuous and interrupted cutting, which obtained from changing workpice material configuration, under control of constant cutting speed from CNC lathe. From statistical and frequency analysis, the AE signals were analyzed to obtaining the characteristics of continuous and interrupted cutting conditions and tool failure. The Kurtosis values decreased but RMS voltages increased as the cutting speed increased, in both continuous and interrupted cutting. RMS voltage is suddenly increased but Kurtosis value is suddenly decreased when tool failure condition. Power spectrum density of AE signals when tool failure reaches extreme value around 0.065 cycles/ .mu. m.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.369-374
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• 2004

Web-based analysis programs for reliability assessment of machine tools were developed in this study. First, the reliability data analysis program was developed to search for failure rate using failure data and reliability test data of mechanical part. Second, failure mode analysis was developed through performance tests like circular movement test vibration test for machine tools. This analysis program shows correlation between failure mode and performance test result. Third, tool life was predicted by correlation between flank wear and cutting time, using the extended Taylor tool life equation in turning data and the equivalently converted equation in order to apply ball endmill data to Taylor tool life equation in milling data. All the information related to input and result data can be stored in theses programs.

• Transactions of Materials Processing
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• v.3 no.2
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• pp.147-155
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• 1994

The service life of tools in metal forming technology is to a large extent limited by wear and fatigue fracture of the active elements. This presents a basic request for tool cost minimization and reduction of extensive machine down time, caused by premature tool failure. Currents developments are dominated by steps to reduce the causes of tool failure. A main problem of forming technology remains the insufficient reliability of tools due to a large and incalculable life time fluctuation. Only a systematic investigation of the failure mechanisms and operational loading of tools can lead to future improvements in tool layout, that is optimization of tool usage.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.30-37
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• 1997

This thesis is concerned with the study on the characteristics of the tool failure occuring at the beginning of cutting in finish machining of hardened steels such as carbon tool steel and alloy tool steel by a ceramic tool (Al$_{2}$O$_{3}$+TiC) with nose radius. In the machining of hardened carbon steel STC3, the wear mechanism on the flank face of the ceramic tool is abrasion wear. The mode of tool failure is developed into catastropic fracture with flaking. It is thought that the fracture caused by FeO and TiO$_{2}$ results from the oxidation of Fe in the workpice and TiC in the ceramic tool and the deposit of Fe formed on the surface of the ceramic tool. In the machining of hardened alloy steel STD11, the wear mechanism on the flank face of the ceramic tool is that abrasion and adhesion wear exist simultaneously. The mode of tool failure at the beginning of cutting features is DOC notch wear. It is thought that the DOC notch wear caused by FeO and TiO$_{2}$results from the oxidation of Fe and TiC in the workpiece and ceramic tool, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.78-85
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• 2002

The wavelet transform is a popular tool fer 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.

• IE interfaces
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• v.15 no.1
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• pp.64-72
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• 2002

Broaching machine is widely used for machining inner shaped slots in the work-pieces, and provides vertical motion (usually hydraulically powered) between tool and work-piece. In this study, we modelled the tool life process and investigated economic tool life of broaching machine. Tool life process is divided into wear-process and succeeding failure process. Wear process is defined as machining wear and failure process as 'chipping' occurred by random shock. We modelled wear process as linear regression function for products amounts and assumed failure process as Poisson process. Economic tool life is defined as the number of lots which minimizes average tool related cost per lot and analyzed by using age replacement policy technique. As tool-related cost factors, we consider tool replacement cost, tool maintenance cost and quality costs of products. The results of this study can be applied to analyze life process of general machining tools.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.3
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• pp.73-79
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• 1996

In this paper present a new technique (strain-telemetering)for detection of coated tool failure in face milling processes. In the cutter body the strain signals received fro the transmitter is transformed in to frequency modulation(FM) signals in face milling processes. A receiver which is place near by the Vertical milling machine receives the FM signals, then the signals will be sent to a computer which determines whether th tool is failure. And machined surface of workpiece is detected by the SEM. In this paper, A on-line monitoring of the tool failure detection system based on the strain -telemetering apparatus has bee represented.

• 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.