On-line cutting force coefficients identification for bull-end milling process with vibration

Abstract

The foundation of newest cutting forces models still is cutting force coefficients that represent material behaviors. They are combined with cutter-workpiece contact algorithms, material properties and so on in the model to accomplish the prediction. Even though cutting force coefficients are significant, identification methods are still involved with onerous experiments, over-idealized measurement conditions, serious results fluctuation caused by many unquantifiable factors. To enlarge cutting database for the optimization of cutting process, utilizing the abundant real-time process monitoring data is a possible choice, in which novel identification methods are needed. To settle this problem, this paper proposed an online identification method considering stiffness property of cutter-holder-spindle system. This investigation considers the fluctuation of cutting forces caused by cutter vibration in two steps: First, a cutting force model that is combined with dynamic undeformed chip thickness is built for bull-end milling. Second, on the foundation of previous step, a corresponding identification method is developed, in which the dynamic undeformed chip thickness is obtained using measured data and utilized in cutting force coefficient identification. The comparison of experimental results and predicting results proves the reliability of cutting force model. Under different conditions, the application of identification method output promising results. In this section, the results show that it is possible to use new method in realizing real-time identification and eliminating machine tool stiffness effect. Also, the shortcomings of the method and the potential improvements are discussed.