The effect of roller-bearing stiffness on the machining process stability

The industry uses machining process monitoring to predict the tool's life and workpiece quality. Its accuracy and prediction are crucial for producing higher quality parts and keeping productivity. Process monitoring systems measure the machining process in real time through several strategically placed sensors on the machine tool. The difference between a fingerprint signature and the actual data determines the quality of a good production cycle. The alarms appear when a deviation from the standard exceeds the pre-set tolerance limit. The fingerprint signature is the result of previous measurements and from dynamic models. These models only consider the excitation frequencies and neglect some of the nonlinearities related to the machine. Additionally, high-speed machining requires higher sample rates, and as a consequence, the signal has less resolution and fewer frequencies. In most cases, the machine is considered a linear system. This work presents a dynamic model that considers the bearings' excitation forces and their effect on chattering. The model produces numerical results, and these results are compared with experimental data. The results presented in this work show that the bearing excitation frequencies modify the chatter response.

Automated summary

The industry uses process monitoring to predict tool life and workpiece quality, which is crucial for producing higher quality parts and maintaining productivity. Process monitoring systems measure machining in real time through strategically placed sensors on the machine tool, to ensure product quality.