Investigation, modeling, and optimization of surface roughness in micro-milling of graphite electrodes

The control of surface roughness in micro-milling of graphite electrodes is needed for achieving high quality of electro-discharge machined molds. The tool deflection in micro-milling of ultrafine grain graphite is drastically lower in comparison to micro-milling of hardened tool steel due to lower cutting forces. Therefore, micro-end-mills with higher aspect ratios are often used. In this paper, the influence of cutting parameters, such as depth of cut, step over, feed rate, and spindle speed at different workpiece inclination angles on surface roughness was investigated experimentally. The experiments were carried out according to Taguchi's 3(4) factorial design of experiments. The effects of surface angle and four micro-machining parameters on the surface quality were analyzed using main effect plots and response surfaces, whereas the analysis of variance (ANOVA) was utilized to determine highly significant parameters. Polynomial regression was utilized to formulate mathematical models of the performance characteristics in terms of selected micro-machining parameters. In addition, developed models were further interfaced with the evolutionary algorithm based on differential evolution (DE) to obtain optimum process parameters for minimizing the surface roughness in micro-milling of graphite.

Automated summary

This paper investigates the influence of cutting parameters on surface roughness during micro-milling of graphite electrodes, and uses experimental design and mathematical models to optimize process parameters for minimizing surface roughness.