Prediction of micro milling force and surface roughness considering size-dependent vibration of micro-end mill

When the characteristic structure size of the component is at the micron level, the internal crystal grains, grain boundaries, and pore defects of the component material with the same size at the micron level cannot be ignored, so the micro-sized component will show different physical properties from the macro-sized component, which is called size effect. Since the tool diameter of a micro-end mill is in the micron level, the micro-end mill will also show a significant size effect phenomenon. In addition, in the micro milling process, because the surface roughness that affects the performance and service life of micro parts is mainly influenced by the vibration of the micro-end mill, in order to enhance the machined surface quality, it is crucial to research the formation mechanism of surface topography in the micro milling process. In this paper, a comprehensive method is proposed to predict micro-end mill vibration, micro milling force, and surface roughness. At first, a size-dependent dynamic model of micro-end mill is presented based on the strain gradient elasticity theory (SGET). Secondly, considering the feedback of a micro-end mill vibration, the micro milling force model is presented and solved through the iterative method. Then the machined surface topography is simulated through the actual cutting edge trajectory considering the micro-end mill size-dependent vibration and material elastic recovery. The results show that the vibration of the micro-end mill will increase the micro milling force and surface roughness. In order to verify the accuracy and efficiency of the presented method, experiments are performed, and it is found that the predicted results are consistent with the experimental results.

Automated summary

This article investigates the size effect phenomenon and surface topography formation mechanism of micro-end mills in micro milling processes, and presents a comprehensive method to predict micro milling force and surface roughness. Experimental results confirm the accuracy and efficiency of this method.