Chatter Stability of Serrated Milling Tools in Frequency Domain

Serrated milling tools are widely used for chatter suppression in roughing difficult-to-cut Titanium and Nickel alloys in the aerospace industry. Due to the complexity of chip generation and serration wave geometries ground on the flutes, the chatter stability diagrams are predicted with time marching numerical simulation or semi-discrete time-domain methods, which are computationally too costly to use in practice. This paper presents a frequency domain model of milling dynamics with variable delays caused by the flute serrations. The endmill is divided into discrete cylindrical elements, each having a different radius from the cutter axis. As the cutter rotates and cuts metal, the angular distance between the subsequent tooth varies as a function of serration amplitudes and feedrate; hence the regenerative delays vary. The angular delays and effective directional factors are averaged for each tooth to form a time-independent but serration-dependent characteristics equation for all discrete cutter elements. The stability of the resulting characteristic equation of the system is solved using Nyquist theory and compared against the experimental results and existing time marching and semi-discrete time-domain solutions. The proposed analytical model predicts the stability charts about thirty times faster than the time-domain models while providing acceptable accuracy.

Transmissibility Enhanced Inverse Chatter Stability Solution

The structural dynamics of a machine tool at the tool center point characterizes its vibration response and machining stability which affects productivity. The dynamics are mostly dominated by the spindle-holder-tool assembly whose main vibration mode can change during machining due to centrifugal forces, thermal expansion, and gyroscopic moments generated at high spindle speeds. This paper proposes the identification of the spindle's in-process modal parameters: natural frequency, damping ratio and modal constant, by using a limited number of vibration transmissibility and critical chatter stability measurements. The classical inverse stability solution, which tunes the modal parameters to minimize prediction errors in chatter stability limits, is augmented with vibration transmissibility under two methods: (1) transmissibility-enhanced inverse stability solution: the modal parameters are updated to minimize prediction errors in chatter stability, and vibration transmissibility; (2) artificial neural network (ANN)-integrated inverse stability solution: the ANN uses vibration transmissibility to estimate the natural frequency and damping ratio, such that the inverse stability solution only needs to identify the modal constant. While both methods are experimentally validated, it is shown that the transmissibility-enhanced inverse stability solution is a more effective approach than the time-consuming ANN alternative for the estimation of in-process spindle dynamics.