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Response Surface Methodology and Genetic Algorithm used to Optimize the Cutting condition for Surface Roughness Parameters in CNC Turning

机译:响应面方法和遗传算法用于优化CNC转动中表面粗糙度参数的切割条件

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In the present study, response surface methodology has been applied to determine the optimum cutting conditions leading to minimum surface roughness in CNC turning operation on EN-8 steel. The second order mathematical models in terms of machining parameters were developed for surface roughness prediction using response surface methodology (RSM) on the basis of experimental results. The experimentation was carried out with coated carbide tool for machining of EN-8 steel. The model selected for optimization has been validated with F-test. The adequacy of the models on surface roughness has been established with Analysis of Variance (ANOVA). An attempt has also been made to optimize the surface roughness prediction model using Genetic Algorithm to find optimum cutting parameters.
机译:在本研究中,应用了响应面方法,以确定EN-8钢上的CNC转动操作中的最小表面粗糙度的最佳切削条件。在基于实验结果的基础上,开发了用于加工参数的二阶数学模型,用于使用响应面方法(RSM)的表面粗糙度预测。通过涂层碳化物工具进行实验,用于加工EN-8钢。选择优化的模型已被F-Test验证。通过对方差(ANOVA)的分析建立了表面粗糙度模型的充分性。还尝试使用遗传算法优化表面粗糙度预测模型,以找到最佳切削参数。

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