In face milling processes, the surface roughness of the machined part reflects the cutting performance of face milling cutter. Surface roughness depends on different factors including feed direction, axial and radial run-out errors, and cutting tool geometry. In this paper, an algorithm considering the effects of static and dynamic factors on surface roughness for predicting the surface roughness is proposed. This work is focusing on straight-edged square insert. The dynamic characteristics of the milling process are also introduced. An electronic impact hammer is used to identify the dynamic parameters of the cutting system. Milling experiments are conducted to validate the prediction model. Results show that the prediction model can estimate the surface roughness of the machined parts after face milling. This paper provides an in-depth understanding of the relationship between machined surface roughness and process conditions especially for axial and radial run-out errors induced by static deformation and Z-axial relative displacement induced by forced vibration. The outcome of this research will lead to methodologies for costeffective monitoring and surface roughness control.
Self-excited vibrations of the face milling process can result in instability, poor surface finish and machine tool failure. In order to avoid chatter vibrations, this article develops an algorithm for predicting the stability lobes for face milling processes. It considers the factors including radial instantaneous chip thickness, entry and exit angles and the dynamic interaction between cutting tool and workpiece which is often neglected by many researchers. An electronic impact hammer is used to identify the dynamic parameters of the face milling system. Milling experiments have been conducted to validate the predictive capability of the developed algorithm for stability lobes. The results show that the prediction model can estimate the stable and unstable zones for face milling process. This article provides a frequency-domain method for establishing stability lobes which can predict stability zones rapidly. The outcome of this research will bring about methodologies for cost-effective monitoring of face milling processes and maximize the material removal rate.
In high speed face milling, noise can be broadly categorized as idling noise and cutting noise. Idling noise mainly consists of aerodynamic noise. A mathematical model is developed based on the Ffowcs Williams-Hawkings Equation. The noise predicted with the mathematical model compares well with the experimental observations. The characteristics of aerodynamic noise with the different model parameters (number of teeth, tooth spacing) and locations of observation points are investigated. The directivity of noise is found and the peak value of sound power can be moved from the rotating frequency to higher frequency. This investigation can provide theoretical foundation for the design of face milling cutters with low noise. face milling cutter, aerodynamic noise, numerical simulation Citation:Ji C H, Liu Z Q, Liu L N. Simulation and analysis of aerodynamics for high speed face milling cutters.
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