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Application of Response surface method and Fuzzy logic approach to optimize the process parameters for surface roughness in CNC turning

机译:响应曲面法和模糊逻辑法在数控车削表面粗糙度工艺参数优化中的应用

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This paper addresses optimization in cutting parameters to obtain minimum surface roughness using multiple metamodeling techniques like Design of Experiments (DOE), Response Surface Methodology (RSM) and Fuzzy inference system. The second order mathematical models in terms of machining parameters were developed for surface roughness prediction using RSM on the basis of experimental results. 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 cutting parameters using fuzzy logic approach for the surface roughness prediction models. Experimental results obtained in the machining of UNS C34000 medium leaded brass using coated carbide tool have been provided to verify the approach.
机译:本文介绍了使用多种元建模技术(例如实验设计(DOE),响应曲面方法学(RSM)和模糊推理系统)优化切削参数以获得最小表面粗糙度的方法。在实验结果的基础上,开发了基于加工参数的二阶数学模型,用于使用RSM预测表面粗糙度。选择用于优化的模型已通过F检验进行了验证。通过方差分析(ANOVA)确定了表面粗糙度模型的充分性。还已经尝试使用模糊逻辑方法对表面粗糙度预测模型来优化切削参数。提供了使用涂层硬质合金刀具加工UNS C34000中铅黄铜的实验结果,以验证该方法。

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