Magnesium alloy has attracted more attentions due to its excellent mechanical properties. However, in process of dry cutting operation, many problems restrict its further development. In this article, the effect of cutting parameters on machinabilities of magnesium alloy is explored under dry milling condition. This research is an attempt to investigate the impact of cutting speed at multiple feed rates on cutting force and surface roughness, while a statistical analysis is adopted to determine the influential intensities accurately. The results showed that cutting force is affected by the positively constant intensity from feed rate and the increasingly negative intensity from cutting speed. In contrast, surface roughness is determined by the gradually increasing negative tendency from feed rate and the positive effect with constant intensity from cutting speed. Within the range of the experiments, feed rate is the leading contribution for cutting force while the cutting speed is the dominant factor for surface roughness according to the absolute intensity values. Meanwhile, the trends of influencing intensities between cutting force and surface roughness are opposite. Besides, it is also found that in milling magnesium alloy, chip morphology is highly sensitive to cutting speed while the chip quality mainly depends on feed rate.
This paper studied an effective method based on Taguchi's method with the grey relational analysis, focusing on the optimization of milling parameters on surface integrity in milling TB6 alloy. The grey relational grade that is derived from the grey relational analysis is mainly used to determine the optimum cutting process operations with multiple performance characteristics. Specifically, surface roughness (Ra), hardness, and residual stress were important characteristics in surface integrity of milling TB6 alloy. Based on the combination of these multiple performance characteristics, the feed per tooth, cutting speed, and depth of cut were optimized in this study. Additionally, the analysis of variance (ANOVA) was also applied to determine the most significant factor for the surface integrity of milling TB6 alloy according to the contribution of the ANOVA, and the most significant factor is the cutting speed in this paper. Based on the analysis, the experimental test results have been improved prominently through the grey relational analysis. Hence this method can be an effective approach to enhance the surface integrity of milling TB6 alloy.
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