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首页> 外文期刊>Journal of Advanced Manufacturing Technology >Development of Surface Roughness Prediction Model using Response Surface Methodology for End Milling of HTCS-150
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Development of Surface Roughness Prediction Model using Response Surface Methodology for End Milling of HTCS-150

机译:基于响应面方法的HTCS-150铣削表面粗糙度预测模型的开发

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In the present study, a regression mathematical model has been developed to predict the surface roughness in end milling of High Thermal Conductivity Steel 150 (HTCS-150). A number of milling experiments were conducted using the Response Surface Methodology (RSM) approach using CNC variaxis machining centre. The cutting speeds (484-553 m/min), feed rates (0.31-0.36 mm/tooth) and depth of cut (0.1-0.5 mm) were selected as the control factors. Analysis of variance (ANOVA) was used to analyze the most significant control factors affecting the surface roughness. Box-behnken experimental design was employed to create a mathematical model. The results show that the mathematical modeling developed in this study able to predict the output values of the surface roughness for milling HTCS-150. Cutting speed appeared to be the most influencing parameter for fine surface roughness, followed by depth of cut and feed rate. The differences between measured and calculated values stated about 4 % error.
机译:在本研究中,已经开发了一种回归数学模型来预测高导热钢150(HTCS-150)的立铣刀的表面粗糙度。使用CNC可变轴加工中心,使用响应表面方法(RSM)方法进行了许多铣削实验。选择切削速度(484-553 m / min),进给速度(0.31-0.36 mm /齿)和切削深度(0.1-0.5 mm)作为控制因素。方差分析(ANOVA)用于分析影响表面粗糙度的最重要的控制因素。采用Box-behnken实验设计来创建数学模型。结果表明,本研究开发的数学模型能够预测HTCS-150铣削表面粗糙度的输出值。对于精细的表面粗糙度,切削速度似乎是影响最大的参数,其次是切削深度和进给速度。测量值和计算值之间的差异表示约4%的误差。

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