• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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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.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.32-38
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• 1998

For the purpose of monitoring the abnormal state in proportion to cutting in automatic production process, the 3 kinds of specimens different from mechanical properties by austempering through temperature variation were manufactured, and the effects of tool wear on thrust and AE RMS was analyzed with sequential drilling in in-process. When the ADI specimens were drilled, the relationship of thrust and AE RMS with flank wear was studied through experiments, and it is confirmed that the reliable wear state is able to be monitored by using these signals. It was shown that thrust and AE RMS increased slowly till flank wear reached to V$_{B}$ = 0.25mm, and they increased steeply over the value. The effective tool exchange time was able to be pre-estimated by using this fact. It was validated that the tool breakage was able to be detected on the real time by monitoring in in-process.s.