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Statistical model to determine surface roughness when milling hastelloy C-22HS

机译:确定哈氏合金C-22HS铣削时确定表面粗糙度的统计模型

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摘要

The aim of this study is to develop the surface roughness prediction models, with the aid of statistical methods, for hastelloy C-22HS when machined by PVD and CVD coated carbide cutting tools under various cutting conditions. These prediction models were then compared with the results obtained experimentally. By using response surface method (RSM), first order models were developed with 95 % confidence level. The surface roughness models were developed in terms of cutting speed, feed rate and axial depth using RSM as a tool of design of experiment. In general, the results obtained from the mathematical models were in good agreement with those obtained from the machining experiments. It was found that the feed rate, cutting speed and axial depth played a major role in determining the surface roughness. On the other hand, the surface roughness increases with a reduction in cutting speed. PVD coated cutting tool performs better than CVD when machining hastelloy C-22HS. It was observed that most of the chips from the PVD cutting tool were in the form of discontinuous chip while CVD cutting tool produced continuous chips.
机译:这项研究的目的是借助统计方法,为在不同切削条件下由PVD和CVD涂层硬质合金刀具加工的哈氏合金C-22HS开发表面粗糙度预测模型。然后将这些预测模型与通过实验获得的结果进行比较。通过使用响应面方法(RSM),开发了具有95%置信度的一阶模型。使用RSM作为实验设计工具,在切削速度,进给速度和轴向深度方面开发了表面粗糙度模型。通常,从数学模型获得的结果与从机加工实验获得的结果非常吻合。发现进给速度,切削速度和轴向深度在确定表面粗糙度方面起着重要作用。另一方面,表面粗糙度随着切削速度的降低而增加。在加工哈氏合金C-22HS时,涂有PVD的切削刀具的性能优于CVD。观察到,PVD切削工具产生的大多数切屑呈不连续切屑形式,而CVD切削工具产生的是连续切屑。

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