Stiffness variation method for milling chatter suppression via piezoelectric stack actuators

- The milling dynamic model of stiffness variation with two degrees of freedom is proposed.
- The influences of different types of stiffness variation on stability lobe diagram are analyzed.
- The model and analysis results are verified by a number of milling tests.

In cutting process, chatter is an inevitable phenomenon that greatly affects workpiece surface quality, tool life and machining efficiency. The stiffness variation (SV) method has been proposed and applied in chatter suppression for a long time. However, the early studies focused on boring and turning with one degree of freedom. For milling process with two degrees of freedom, there is no related research about SV. In this paper, SV method is employed through modulating the stiffness around a nominal value in order to suppress milling chatter. The milling dynamic model of SV with two degrees of freedom is constructed. In this model, the classical delay differential equation (DDE), which governs the milling process, is replaced with a DDE with a time-varying stiffness term. The stability analysis with different SV is completed using the semi-discretization method (SDM) and results show that the stable region with SV is larger than that under most of the traditional conditions. The results of stability analysis are verified by time domain simulation. In addition, the influences on stability lobe diagram (SLD), which is caused by different waveforms, amplitudes and frequencies of SV, are also analyzed specifically. The analysis results can provide the optimal parameters combination for milling. Cutting experiments are implemented on a three-axis milling machine to validate the effectiveness of SV. In the experiment, piezoelectric stack actuators are used to modulate the stiffness with time-varying preload. The milling forces signals are acquired by data collecting instrument, whose root-mean-square (RMS) is used as the metric of cutting vibrations. Experiment results are in good agreement with theoretical prediction.