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Application of response surface methodology In the optimization of cutting conditions for surface roughness

机译:响应面法在优化表面粗糙度切削条件中的应用

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This paper focuses on the development of an effective methodology to determine the optimum cutting conditions leading to minimum surface roughness in milling of mold surfaces by coupling response surface methodology (RSM) with a developed genetic algorithm (GA). RSM is utilized to create an efficient analytical model for surface roughness in terms of cutting parameters: feed, cutting speed, axial depth of cut, radial depth of cut and machining tolerance. For this purpose, a number of machining experiments based on statistical three-level full factorial design of experiments method are carried out in order to collect surface roughness values. An effective fourth order response surface (RS) model is developed utilizing experimental measurements in the mold cavity. RS model is further interfaced with the GA to optimize the cutting conditions for desired surface roughness. The GA reduces the surface roughness value in the mold cavity from 0.412 mum to 0.375 mum corresponding to about 10 percent improvement. Optimum cutting condition produced from GA is verified with the experimental measurement.
机译:本文致力于通过将响应表面方法(RSM)与已开发的遗传算法(GA)耦合,确定一种有效的方法,以确定最佳的切削条件,从而在模具表面铣削中达到最小的表面粗糙度,该方法的发展。 RSM用于为切削参数创建有效的表面粗糙度分析模型:进给,切削速度,轴向切削深度,径向切削深度和加工公差。为此,基于统计三级全因子设计实验方法进行了许多加工实验,以收集表面粗糙度值。利用模腔中的实验测量结果,开发了有效的四阶响应面(RS)模型。 RS模型进一步与GA配合使用,以优化切削条件以获得所需的表面粗糙度。 GA将模腔中的表面粗糙度值从0.412微米降低到0.375微米,相当于提高了约10%。实验测量证明了GA产生的最佳切削条件。

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