Abstract
In this study, by using Taguchi method, with four controllable factors-three levels (milling type, axial depth of cut, feed rate, and spindle speed), the orthogonal array L27 was used to investigate the effects of milling type and cutting conditions on the surface roughness. By analysis of variance (ANOVA), the influences degree of milling type, axial cutting depth, feed rate, and spindle speed on the surface roughness were 9.26 %, 12.85 %, 12.69 %, and 63.08 %, respectively. The interaction factors of these factors that have a quite small influence on the surface roughness. The surface roughness was modeled as a quadratic regression with the confidence level is more than 99.82%. This model was successfully verified by comparison of experimental and predicted results. The optimization process of surface roughness was performed by both Taguchi method and the ANOVA analysis with the same results. The optimum value of surface roughness was 0.374 µm that was obtained in the half up milling, at a cutting depth of 0.4 mm, a feed rate of 480 mm/min, and a spindle speed of 5000 rpm.
Highlights
In the milling processes, the relationship between mach ining conditions and machining characteristics is very important to predict the quality o f machining product, and predict the consumption of power, energy, as well
In order to investigate the influence of machin ing condition on mach ining characteristics, many approaches were applied such as Taguchi method, response surface methodology (RSM), statistical methods of signal to noise ratio (SNR), Analysis of variance (ANOVA), and so on
The contributions of each factor on the surface roughness were listed in the last colu mn. It is clear fro m the results of ANOVA that the most important factor affecting on the surface roughness was spindle speed
Summary
The relationship between mach ining conditions and machining characteristics is very important to predict the quality o f machining product, and predict the consumption of power, energy, as well. In order to investigate the influence of machin ing condition on mach ining characteristics (surface roughness, tool wear, cutting forces, etc.), many approaches were applied such as Taguchi method, response surface methodology (RSM), statistical methods of signal to noise ratio (SNR), Analysis of variance (ANOVA), and so on. The Taguchi method employs a special design of orthogonal array through reducing the nu mber of experiments to investigate the effect of the entire machin ing parameters This method has been widely employed in several industrial fields, and research work. This study was carried out to determine the influence of milling types, cutting conditions, and the interaction factors of them on the surface roughness, and to improve the surface roughness of machined part by application of optimization methods. Almost all Response surface methodology problems use one or both of the first-order model and second-order model of polynomial that are given by Eq (1) and Eq (2), respectively [22]
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