The accurate measurement of forces at the tool tip is required for calibration of cutting force coefficients, adaptive control of maximum cutting forces, detection of tool failure, and monitoring of the force history applied to a workpiece during production. However, the majority of the present sensor systems are not effective due to low frequency bandwidths, limited workpiece size, wiring complexities, and susceptibility to harsh machining environments. To overcome the limitations, the Spindle Integrated Force Sensor (SIFS) system is developed, which can be used in production machines to measure cutting forces by integrating piezoelectric force sensors to the stationary spindle housing. Since the sensors are part of the spindle, the structural dynamics of the spindle assembly directly affect the accuracy and bandwidth of the force measurement. The thesis presents a systematic methodology to compensate the distortions caused by structural dynamic modes of the spindle and tool system.

The structural dynamic model between the cutting forces acting on the tool tip and the measured forces at the spindle housing is identified. A disturbance Kalman Filter is designed to remove the influence of structural modes on the force measurements. The frequency bandwidth is increased from 350 Hz to 1000 Hz by compensating the first three dominant structural modes of the spindle with the proposed sensing and the signal processing method. In addition, the mathematical coupling of Frequency Response Functions (FRFs) of the spindle and arbitrary cutting tool dynamics is proposed and verified using the Receptance Coupling (RC) method with the identification of the joint dynamics to automate the dynamic compensation regardless of end mills. Based on the reconstructed cutting force measurements from the spindle integrated sensors, the adaptive control scheme is used to maximize productivity by optimizing the feed rate of the CNC machine, and the chatter and tool breakage detections are performed to monitor the milling processes.