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Mathematical modeling of surface roughness for evaluating the effects of cutting parameters and coating material

机译:表面粗糙度的数学模型,用于评估切削参数和涂层材料的影响

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The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) onto the surface roughness through the mathematical model developed by using the data gathered from a series of turning experiments performed. An additional investigation was carried out in order to evaluate the influence of two well-known coating layers onto the surface roughness. For this purpose, the experiments were repeated for two CNMG 120408 (with an ISO designation) carbide inserts having completely the same geometry and substrate but different coating layers, in a manner that identical cutting conditions would be ensured. The workpiece material machined was cold-work tool steel AISI P20. Of the two types of inserts employed; Insert 1 possesses a coating consisting of a TiCN underlayer, an intermediate layer of Al{sub}2O{sub}3 and a TiN outlayer, all deposited by CVD; whilst Insert 2 is PVD coated with a thin TiAlN layer (3 ± 1μm). The total average error of the model was determined to be 4.2% and 5.2% for Insert 1 and Insert 2, respectively; which proves the reliability of the equations established.
机译:本文提出的工作通过使用从一系列车削实验中收集的数据开发的数学模型,研究了切削参数(切削速度,进给速度和切削深度)对表面粗糙度的影响。为了评估两个众所周知的涂层对表面粗糙度的影响,进行了另外的研究。为此,以确保相同的切削条件的方式,对两个具有完全相同的几何形状和基材但涂层不同的CNMG 120408(ISO名称)硬质合金刀片重复实验。加工的工件材料是AISI P20冷作工具钢。在使用的两种刀片中;插入物1具有由TiCN底层,Al {sub} 2O {sub} 3的中间层和TiN外层组成的涂层,这些涂层均通过CVD沉积。而插入物2则用TiAlN薄层(3±1μm)进行PVD涂层。插入件1和插入件2的模型总平均误差分别确定为4.2%和5.2%;证明了所建立方程的可靠性。

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