Micro burrs are likely to occur due to the size effect associated with cutting edge radius in a micro-scale milling process. Micro burrs reduce the machined surface quality and cause damages to the contact surfaces of micro parts, so it should be removed through the deburring process. However, the micro burrs formed by micro cutting process are not easy to remove, and require much time and cost for deburring process. Therefore, it is necessary to suppress the generation of micro burrs by the optimization of machining process. Also, it is important to detect the generation of micro burrs in advance through real-time monitoring of cutting signals to change in cutting conditions. In this paper, the influence of each cutting variables on the size of micro burrs and the correlation between micro-burrs and cutting signals are investigated through micro channel machining experiments in micro-scale milling process. The feed per tooth and spindle speed in the cutting variables are selected as independent variables. Each variable is divided into 3 levels and a total of 9 cutting conditions are derived. The size of micro burrs formed on the micro-channels is measured, and the effect of each cutting variable on the generation of micro burrs. Also signal characteristics such as AE RMS, band energy, AE count are extracted through signal processing of AE signals and the correlation between the size of micro burrs and the AE signal characteristics is figured out.
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