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Surface roughness analysis and optimization for the CNC milling process by the desirability function combined with the response surface methodology

机译:期望函数与响应曲面法相结合的数控铣削表面粗糙度分析与优化

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摘要

The present study is aimed for an optimization strategy for the CNC pocket millingprocess based on the desirability function approach (DFA) combined with the response surface methodology (RSM). Firstly, the milling parameters such as cutting speed, feed rate and depth of cut are designed using the rotatable central composite design (CCD). The AISI 1050 medium carbon steel is machined by a flat end 8 mm high speed steel (HSS) tool on a zigzag cutting path under air flow condition. The influence of milling parameters is examined. Secondly, the model for the surface roughness, as a function of milling parameters, is obtained using the RSM. Finally, the power and adequacy of the quadratic mathematical model has been proven by the analysis of variance (ANOVA) method. The results indicate that the feed rate is the dominant factor affecting the surface roughness, which is minimized when the feed rate and depth of cut are set to the experimental range. A high correlation coefficient of R-2 = 0.99 has been obtained between the predicted and the experimental surface roughness. This reveals that the prediction system established in this study produces satisfactory results with an improved performance compared to other models in the literature. The enhanced method proposed in this study can be readily applied to different metal cutting processes with greater confidence.
机译:本研究旨在基于期望函数方法(DFA)与响应面方法(RSM)相结合的CNC腔铣削工艺的优化策略。首先,使用可旋转的中央复合设计(CCD)设计铣削参数,例如切削速度,进给速度和切削深度。 AISI 1050中碳钢是在空气流动条件下,在锯齿形切割路径上由8毫米平端高速钢(HSS)工具加工而成的。检查了铣削参数的影响。其次,使用RSM获得作为铣削参数的函数的表面粗糙度模型。最后,通过方差分析(ANOVA)方法证明了二次数学模型的功效和充分性。结果表明,进给速度是影响表面粗糙度的主要因素,当进给速度和切削深度设置为实验范围时,该影响最小。在预测的和实验的表面粗糙度之间已获得高的相关系数R-2 = 0.99。这表明与文献中的其他模型相比,本研究中建立的预测系统可产生令人满意的结果,并具有改进的性能。这项研究中提出的增强方法可以很容易地应用于不同的金属切割工艺,并且具有更高的置信度。

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