A new experimental methodology for identification of stability lobes diagram in milling operations

Abstract Chatter is a self-excited vibration that can occur during machining operations. This undesirable phenomenon is one of the most common limitations when it comes to improving productivity and part quality. For this reason, several methods have been developed with the aim of preventing, avoiding, reducing, suppressing or controlling the occurrence of chatter. A stability lobes diagram (SLD) shows the boundary between chatter-free machining operations and unstable processes, in terms of axial depth of cut as a function of spindle speed. These diagrams are used to select chatter-free combinations of machining parameters. This paper presents an experimental method for identifying SLDs in milling operations. The methodology is based on empirical tests where the workpiece permits a gradual increase of the axial depth of cut in the feed direction, which represents the y coordinate of the SLD while the spindle speed (the x coordinate of the SLD) is increased between passes. This is possible thanks to the inclined plane shape presented by the workpiece. The cutting process is interrupted as soon as chatter is detected and the frontier between stable and unstable cutting, i.e. the stability lobes diagram, is identified. This permits to obtain the SLD physically machined onto the workpiece. The methodology is good for those small and medium enterprises which have no technical knowledge and sophisticated resources, because the SLD can be identified with a microphone and prepared workpiece. At first, we present the results obtained when chatter is detected by the operator by analyzing the sound emission. Then, in order to eliminate the subjective component of the human hearing intervention, a computer application is presented. It permits to monitor the milling process sound and analyze its amplitudes and frequencies to identify chatter as soon as its occurrence starts. The results provided by the computer application are quite better.

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