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Optimisation of Machining Parameters in Hard Turning by Desirability Function Analysis Using Response Surface Methodology

机译:利用响应面法测定函数分析的硬转向机加工参数的优化

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In this study, the effects of cutting speed, feed rate and depth of cut on surface roughness in the hard turning were experimentally investigated. AISI 4140 steel was hardened to (56 HRC). The cutting tool used was an uncoated AL_2O_3/TiC mixed ceramics which is approximately composed of 70% of AL_2O_3 and 30% of TiC. Three factor (cutting speed, feed rate and depth of cut) and three-level factorial experiment designs completed with a statistical analysis of variance (ANOVA) were performed. Mathematical model for surface roughness was developed using the response surface methodology (RSM) associated with response optimization technique and composite desirability was used to find optimum values of machining parameters with respect to objectives surface roughness. The results have revealed that the effect of feed is more pronounced than the effects of cutting speed and depth of cut, on the surface roughness. However, a higher cutting speed improves the surface finish. In addition, a good agreement between the predicted and measured surface roughness was observed. Therefore, the developed model can be effectively used to predict the surface roughness on the machining of AISI 4140 steel with in 95% confidence intervals ranges of conditions studied.
机译:在这项研究中,实验研究了在硬转弯中切割速度,进料速率和切割表面粗糙度深度的影响。 AISI 4140钢硬化为(56 HRC)。使用的切削刀具是未涂覆的Al_2O_3 / TIC混合陶瓷,其大致由70%的Al_2O_3和30%的TIC组成。进行三个因素(切割速度,进料速率和切割深度)和三级因子设计,随着对方差统计分析(ANOVA)完成的。使用与响应优化相关的响应表面方法(RSM)开发了表面粗糙度的数学模型,并且使用复合期望来寻找关于目标表面粗糙度的加工参数的最佳值。结果表明,饲料的效果比切割速度和切割深度的影响更加明显,在表面粗糙度上。然而,更高的切削速度改善了表面光洁度。此外,观察到预测和测量的表面粗糙度之间的良好一致性。因此,可以有效地使用开发的模型来预测AISI 4140钢加工的表面粗糙度,以95%的置信区间研究的条件范围。

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