Gao Honghong, Ma Baoji, Singh Ravi Pratap, Yang Heng
School of Mechatronic Engineering, Xi'an Technological University, Xi'an 710021, China.
Materials (Basel). 2020 May 16;13(10):2303. doi: 10.3390/ma13102303.
Surface roughness is used to quantitatively evaluate the surface topography of the workpiece subjected to mechanical processing. The optimal machining parameters are critical to getting designed surface roughness. The effects of cutting speed, feed rate, and depth of cut on the areal surface roughness of AZ31B Mg alloys were investigated via experiments combined with regression analysis. An orthogonal design was adopted to process the dry turning experiment of the front end face of the AZ31B bar. The areal surface roughness Sa and Sz of the end face were measured with an interferometer and analyzed through direct analysis and variance analysis (ANOVA). Then, an empirical model was established to predict the value of Sa through multiple regression analysis. Finally, a verification experiment was carried out to confirm the optimal combination of parameters for the minimum Sa and Sz, as well as the availability of the regression model for predicting Sa. The results show that both Sa and Sz of the machined end face reduce with the decrease in feed rate. The minimum of Sa and Sz reaches to 0.577 and 5.480 µm, respectively, with the cutting speed of 85 m/min, the feed rate of 0.05 mm/rev, and a depth of cut of 0.3 mm. The feed rate, depth of cut, and cutting speed contribute the greatest, the second and the smallest to Sa, respectively. The linear regression model can predict Sa of AZ31B machined with dry face turning, since the cutting speed, feed rate and depth of cut can explain 97.5% of the variation of Sa.
表面粗糙度用于定量评估经过机械加工的工件的表面形貌。最佳加工参数对于获得设计的表面粗糙度至关重要。通过实验结合回归分析，研究了切削速度、进给速度和切削深度对AZ31B镁合金表面粗糙度的影响。采用正交设计对AZ31B棒材前端面进行干式车削实验。用干涉仪测量端面的表面粗糙度Sa和Sz，并通过直接分析和方差分析（ANOVA）进行分析。然后，通过多元回归分析建立经验模型来预测Sa的值。最后，进行验证实验，以确定获得最小Sa和Sz的最佳参数组合，以及回归模型预测Sa的有效性。结果表明，加工端面的Sa和Sz均随进给速度的降低而减小。当切削速度为85 m/min、进给速度为0.05 mm/rev、切削深度为0.3 mm时，Sa和Sz的最小值分别达到0.577和5.480 µm。进给速度、切削深度和切削速度对Sa的贡献分别最大、第二和最小。线性回归模型可以预测干式端面车削加工的AZ31B的Sa，因为切削速度、进给速度和切削深度可以解释Sa变化的97.5%。
