Endmill Condition Monitoring and Failure Forecasting Method for Curvilinear Cuts of Non-Constant Radii

In this paper, an endmill condition monitoring technique is presented for curvilinear cutting. This algorithm operates without the need for prior knowledge of cutting conditions, tool type, cut curvature, cut direction, or directional rate of change. This technique is based on an autoregressive-type monitoring algorithm which is used to track the tool’s condition using a tri-axial accelerometer. Accelerometer signals are monitored due to the sensors relatively low cost and since use of the sensor does not limit the machining envelope. To demonstrate repeatability, eight life tests were conducted. The technique discussed herein successfully prognosis impending fracture or meltdown due to wear in all cases, providing sufficient time to remove the tools before failure is realized. Furthermore, the algorithm produces similar trends capable of forecasting failure, regardless of tool type and cut geometry. Success is seen in all cases without requiring algorithm modifications or any prior information regarding the tool or cutting conditions.