Abstract

As fully automated and intelligent machine tools are highly developed and expected to be realized in the near future, which can autonomously determine the cutting states regardless of any cutting conditions and can change them automatically as required, it is hence necessary to develop a methodology to identify the cutting states automatically. In ball-end milling process, the chatter is one of the major limitations of productivity in metal cutting. It always affects the surface finish, the dimensional accuracy, the tool life and machine life. The aim of this research is to develop an in-process monitoring system for detection of the chatter regardless of the cutting conditions by using the dynamic cutting force obtained during the cutting. The method proposed introduces three parameters, which are calculated and obtained by taking the ratio of the average variances of the dynamic cutting forces of three force components, to classify the chatter. The new algorithm was developed and implemented on 5-axis CNC machining center to detect the chatter in ball-end milling process. The experimentally obtained results showed that the proposed method can be used efficiently to detect the chatter during the cutting even though the cutting conditions are changed.

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