SUMMARY
Analytical force and dynamic models for material removal processes such as end and face milling do not account for material and process related uncertainties such as tool wear, tool breakage and material inhomogeneity. Optimization of material removal processes thus requires not only optimal process planning using analytical models but also on-line monitoring of the process so that adjustments, if needed, can be initiated to maximize the productivity or to avoid damaging expensive parts. In this work, a Polyvinylidene Fluoride (PVDF) sensor based and cutting conditions and material independent method for measuring the cutting forces and/or torque in milling is proposed. The proposal includes the development of methods and hardware for real-time wireless acquisition of high fidelity time-varying strain signals from PVDF sensor-instrumented milling tools rotating at high speeds and transformation of the strains into cutting forces/torque using physics-based models of the measurement system. Various PVDF sensor configurations are proposed for measuring different components of the forces/torque in milling. In addition, a computationally efficient algorithm for milling chatter recognition that can adapt to different cutting conditions and workpiece geometry variations based on the measured cutting forces/torque signals is proposed. Both the cutting forces/torque measurement methodology and the chatter detection algorithm have great potential for shop floor application. The cutting forces/torque measurement system can be integrated with adaptive feedback controllers for process optimization and can also be extended to the measurement of other physical phenomena.