Optimization of cutting conditions for surface roughness in CNC end milling

被引：0
|
作者：
Kantheti Venkata Murali Krishnam Raju
Gink Ranga Janardhana
Podaralla Nanda Kumar
Vanapalli Durga Prasada Rao
机构：
[1] S. R. K. R. Engineering College,Department of Mechanical Engineering
[2] J. N. T. U. College of Engineering,Department of Mechanical Engineering
[3] Narayanadri Institute of Science and Technology,Department of Mechanical Engineering
来源：
International Journal of Precision Engineering and Manufacturing | 2011年 / 12卷
关键词：
End milling; Cutting parameters; Surface roughness; Multiple regression; Genetic algorithm; Optimization;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The aim of this research is to develop an integrated study of surface roughness to model and optimize the cutting parameters when end milling of 6061 aluminum alloy with HSS and carbide tools under dry and wet conditions. A multiple regression analysis using analysis of variance is conducted to determine the performance of experimental measurements and to show the effect of cutting parameters on the surface roughness. The second-order mathematical models in terms of machining parameters have been developed for each of these conditions on the basis of experimental results. Genetic algorithm (GA) supported with the regression equation is utilized to determine the best combinations of cutting parameters providing roughness to the lower surface through optimization process. The value obtained from GA is compared with that of experimental value and found reliable. It is observed from the results that the developed study can be applied to other machining processes operating under different machining conditions.
引用
收藏
页码：383 / 391
页数：8
相关论文
共 50 条
  • [21] Response Ant Colony Optimization of End Milling Surface Roughness
    Kadirgama, K.
    Noor, M. M.
    Alla, Ahmed N. Abd
    SENSORS, 2010, 10 (03): : 2054 - 2063
  • [22] Modeling of machined surface roughness and optimization of cutting parameters in face milling
    Bajic, D.
    Lela, B.
    Zivkovic, D.
    METALURGIJA, 2008, 47 (04): : 331 - 334
  • [23] Optimization of Cutting Parameters Based on Surface Roughness and Cutting Force During End Milling of Nimonic C-263 Alloy
    Reddy, P. Giridhar
    Gowthaman, S.
    Jagadeesha, T.
    3RD INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING (ICAME 2020), PTS 1-6, 2020, 912
  • [24] Experimental investigation on surface roughness in CNC end milling process by uncoated and TiAlN coated carbide end mill under dry conditions
    Masooth, P. Haja Syeddu
    Jayakumar, V
    Bharathiraja, G.
    MATERIALS TODAY-PROCEEDINGS, 2020, 22 : 726 - 736
  • [25] Surface roughness prediction in CNC end milling machining using artificial neural networks
    Chang, Ming-Kun
    Chang, Wen-Jie
    ICIC Express Letters, Part B: Applications, 2016, 7 (04): : 759 - 764
  • [26] Optimization of process parameters for cutting force for aluminium 7010 in CNC end milling process
    Kishanth M.
    Rajkamal P.
    Karthikeyan D.
    Anand K.
    International Journal of Vehicle Structures and Systems, 2018, 10 (06) : 399 - 403
  • [27] Kernel based regression and genetic algorithms for estimating cutting conditions of surface roughness in end milling machining process
    Wibowo, Antoni
    Desa, Mohammad Ishak
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (14) : 11634 - 11641
  • [28] Estimation of fractal dimension and surface roughness based on material characteristics and cutting conditions in the end milling of carbon steels
    Zuo, Xue
    Zhu, Hua
    Zhou, Yuankai
    Yang, Jianhua
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2017, 231 (08) : 1423 - 1437
  • [29] Modeling the surface roughness in face-end milling process by using general insert at stable cutting conditions
    Le Hong Ky
    Nhu-Tung Nguyen
    Duc Trung Do
    Tien Dung Hoang
    Hoang Anh Le
    INTERNATIONAL JOURNAL OF MODERN PHYSICS B, 2020, 34 (22-24):
  • [30] Effect of Cutting Variables of End Milling Process on Surface Roughness and Machining Vibrations
    Sonawane, Sachin Ashok
    Pawar, Akshay P.
    TECHNO-SOCIETAL 2018: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SOCIETAL APPLICATIONS - VOL 2, 2020, : 661 - 670
12345