A surface roughness prediction model using response surface methodology in micro-milling Inconel 718

被引：0

作者：

Lu X. ^{[1
]}

Wang F. ^{[1
]}

Wang X. ^{[1
]}

Lu Y. ^{[1
]}

Si L. ^{[1
]}

机构：

[1] Key Laboratory for Precision and Non-traditional Machining Technology, Ministry of Education, Dalian University of Technology, No. 2 LingGong Road, DaLian, LiaoNing Province

来源：

Lu, Xiaohong (lxhdlut@dlut.edu.cn) | 2017年 / Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland卷 / 19期

关键词：

Analysis of variance; ANOVA; Inconel; 718; Micro-milling; Response surface methodology; RSM; Surface roughness;

D O I：

10.1504/IJMMM.2017.084006

中图分类号：

学科分类号：

摘要：

In this paper, a surface roughness prediction model of micro-milling Inconel 718 by applying response surface methodology (RSM) is presented. The experiments based on centre composite rotatable design (CCRD) are designed to conduct the experiments. The cutting parameters considered are depth of cut, spindle speed and feed rate. Statistical methods, analysis of variance (ANOVA), are used to analyse the adequacy of the predictive model. The influence of each micro-milling parameter on surface roughness is analysed; also the magnitude order of parameters is determined. Depth of cut is found to be the critical influence factor. At last, the parameters interaction on surface roughness of micro-milling Inconel 718 is discussed by graphical means through MATLAB. © 2017 Inderscience Enterprises Ltd.

引用

页码：230 / 245

页数：15

共 25 条

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