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
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
收藏
页码:230 / 245
页数:15
相关论文
共 50 条
  • [31] Burr formation and surface roughness characteristics in micro-milling of microchannels
    Liang Chen
    Daxiang Deng
    Guang Pi
    Xiang Huang
    Wei Zhou
    The International Journal of Advanced Manufacturing Technology, 2020, 111 : 1277 - 1290
  • [32] Experimental evaluation of surface roughness in orthogonal micro-milling processes
    Wu Jihua
    ADVANCED MATERIALS AND PROCESS TECHNOLOGY, PTS 1-3, 2012, 217-219 : 1912 - 1916
  • [33] Characterization of 3D Surface Roughness in Micro-Milling
    Li, Wenqin
    Yu, Zhanjiang
    Yu, Huadong
    Xu, Jinkai
    2019 IEEE INTERNATIONAL CONFERENCE ON MANIPULATION, MANUFACTURING AND MEASUREMENT ON THE NANOSCALE (IEEE 3M-NANO), 2019, : 156 - 161
  • [34] Burr formation and surface roughness characteristics in micro-milling of microchannels
    Chen, Liang
    Deng, Daxiang
    Pi, Guang
    Huang, Xiang
    Zhou, Wei
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2020, 111 (5-6): : 1277 - 1290
  • [35] PREDICTION OF SURFACE ROUGHNESS IN END MILLING OPERATION OF DUPLEX STAINLESS STEEL USING RESPONSE SURFACE METHODOLOGY
    Philip, S. D.
    Chandramohan, P.
    Rajesh, P. K.
    JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY, 2015, 10 (03) : 340 - 352
  • [36] PREDICTION OF SURFACE ROUGHNESS IN HIGH SPEED MACHINING OF INCONEL 718
    Suhaily, M.
    Amin, A. K. M. Nurul
    Patwari, Md Anayet U.
    ADVANCES IN MATERIALS AND PROCESSING TECHNOLOGIES II, PTS 1 AND 2, 2011, 264-265 : 1193 - 1198
  • [37] Prediction of tool wear during micro-milling Inconel 718 thin-walled parts
    Lu, Xiaohong
    Hou, Pengrong
    Luan, Yihan
    Yang, Kun
    Ruan, Feixiang
    Zhao, Ning
    INTERNATIONAL JOURNAL OF MANUFACTURING RESEARCH, 2022, 17 (01) : 82 - 94
  • [38] Optimization of cutting force in cryogenic high-speed milling of Inconel 718 using response surface methodology
    Halim, Nurul Hayati Abdul
    Haron, Che Hassan Che
    Ghani, Jaharah A.
    Azhar, Muammar Faiq
    PROCEEDINGS OF MECHANICAL ENGINEERING RESEARCH DAY 2018 (MERD), 2018, : 138 - 140
  • [39] Modeling of laser-assisted micro-milling Inconel718
    Lu, Xiaohong
    Xv, Kai
    Wang, Xinxin
    Cong, Chen
    Zeng, Fanmao
    Liang, Steven Y.
    PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY, 2024, 88 : 854 - 866
  • [40] Investigation of Laser-Assisted Micro-Milling Process of Inconel 718
    Zhang, Haijun
    Chen, Fei
    Li, Zengqiang
    Hu, Wangjie
    Sun, Tao
    Zhang, Junjie
    JOURNAL OF MANUFACTURING AND MATERIALS PROCESSING, 2023, 7 (04):