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Optimal Selection of process parameters in CNC end milling of Al 7075-T6 aluminium alloy using a Taguchi-Fuzzy approach

机译:使用TAGUCHI-FUZZY方法的AL 7075-T6铝合金CNC端铣削过程参数的最佳选择

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This paper describes the application of the fuzzy logic integrated with Taguchi method for minimizing the surface roughness and maximizing the material removal rate simultaneously, in CNC end milling of Al 7075 T6 aerospace aluminium alloy. The input parameters taken into consideration are speed, feed, depth of cut and nose radius. Al 7075 T6 is one of the highest strength aluminium alloys in 7000 series family. In Taguchi method, L_(27) orthogonal array with 4 factors and 3 levels are chosen and S/N ratios are calculated. The S/N ratios of roughness and material removal rate are fed as inputs to fuzzy logic system and output received is Multi response performance index (MRPI). With application of ANOVA, the nose radius and depth of cut are identified as the most significant parameters contributing about 31% of the variance. Further a confirmation test showed that, there was a significant improvement in MRPI of optimal process parameters as compared to MRPI of initial process parameters.
机译:本文介绍了模糊逻辑与Taguchi方法的应用,以使表面粗糙度最小化并同时最大化材料去除率,在AL 7075 T6航空航天铝合金的CNC端铣削中。考虑的输入参数是速度,饲料,切割深度和鼻径。 Al 7075 T6是7000系列系列中最高强度铝合金之一。在Taguchi方法中,选择具有4个因素和3个级别的L_(27)正交阵列,并计算S / N比。粗糙度和材料去除率的S / N比被馈送为模糊逻辑系统的输入,并且收到的输出是多响应性能指数(MRPI)。凭借Anova的应用,鼻径半径和切割深度被识别为最重要的参数,其中占所述方差的约31%。此外,与初始过程参数的MRPI相比,确认测试表明,与MRPI相比,最佳过程参数的MRPI显着改善。

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