Indirect drill condition monitoring based on machine tool control system data

Abstract

Automatic process monitoring, including tool wear monitoring, is a key aspect of improving the energy efficiency and cost of the machining process. The tool flank wear continuously increases during drilling operations. The intensity of tool wear may vary depending on the local properties of the material and the process settings. This paper shows the potential of drill condition monitoring based on machine tool control system data, namely spindle drive current and Z slide current. The workpiece vibration measurement is used as a reference method. Correlations of various features of monitored signals are evaluated. These features are shown to depend, in general, on the instantaneous drilling depth. Among the features investigated, the RMS signal has been shown to exhibit a significant correlation with tool wear. The results were compared for two values of cutting speed. The correlation of selected features is shown to be independent of the total lifetime of the tool, thus demonstrating the attractiveness of these features for tool wear prediction. Specifically, the root mean square of the vibration and spindle torque signals strongly correlate with flank wear near the bottom of the hole while the root mean square of the drive current of the drilling axis strongly correlates with flank wear near the middle of the hole.