Multi objective optimization of cutting parameters of end milling operation by Taguchi GreyRelational analysis (TGRA)

被引:0
|
作者
Shilpa Sahare [1 ]
Prashant Kamble [1 ]
Jayant Giri [1 ]
Neeraj Sunheriya [1 ]
T. Sathish [2 ]
Rajkumar Chadge [1 ]
A. Parthiban [3 ]
机构
[1] Yeshwantrao Chavan College of Engineering,Department of Mechanical Engineering
[2] SIMATS,Saveetha School of Engineering
[3] Vels Institute of Science,Department of Mechanical Engineering
[4] Technology and Advanced Studies (VISTAS),undefined
关键词
Grey relational analysis; ANOVA; Material removal rate; Optimization;
D O I
10.1007/s10751-024-02119-1
中图分类号
学科分类号
摘要
This study proposes an ideal milling process parameter setup for multi-responses. Due of this problem, Grey relational analysis with Taguchi approach is used. These approaches helped determine ideal machining conditions to improve surface roughness, material removal rate, cutting force, and tool wear. Compare results from wet and minimal amount lubrication studies. Further multiple flow rates of Minimum Quantity Lubrication were tested to find the “best” setting. The best gray relational analysis setting is used in tests with varied minimal Quantity Lubrication flow rates. ANOVA for MPCI showed that depth of cut affects several performance factors the most, followed by spindle speed, feed, tool diameter, and tool type. The response table and S/N ratio main effect plot show that 1500 rpm spindle speed, 0.5 mm depth of cut, 550 mm/min feed, 12 mm end mill cutter with coated (PVD), and minimal amount lubrication are the ideal machining settings. After experimenting with minimum amount lubricating flow rates, 80 ml/hr is the ideal setting. Finally, experimentation tests conformance.
引用
收藏
相关论文
共 50 条
  • [41] Optimization of cutting parameters in micro end milling operations in dry cutting condition using genetic algorithms
    Sreeram, Sonti
    Kumar, A. Senthil
    Rahman, M.
    Zaman, M. T.
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2006, 30 (11-12): : 1030 - 1039
  • [42] Optimization of cutting parameters in micro end milling operations in dry cutting condition using genetic algorithms
    Sreeram, Sonti
    Kumar, A. Senthil
    Rahman, M.
    Zaman, M.T.
    International Journal of Advanced Manufacturing Technology, 2006, 30 (11-12): : 1030 - 1039
  • [43] Study on Multi-objective Cutting Parameters Optimization of Titanium Alloy
    LI Deng-wan1
    2 Dongfang Steam Turbine Co.
    International Journal of Plant Engineering and Management, 2010, 15 (04) : 242 - 246
  • [44] Optimization of cutting parameters in micro end milling operations in dry cutting condition using genetic algorithms
    Sonti Sreeram
    A. Senthil Kumar
    M. Rahman
    M. T. Zaman
    The International Journal of Advanced Manufacturing Technology, 2006, 30 : 1030 - 1039
  • [45] Modified PSO algorithm for multi-objective optimization of the cutting parameters
    Toufik Ameur
    Mekki Assas
    Production Engineering, 2012, 6 (6) : 569 - 576
  • [46] Modified PSO algorithm for multi-objective optimization of the cutting parameters
    Ameur, Toufik
    Assas, Mekki
    PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT, 2012, 6 (06): : 569 - 576
  • [47] Optimization of Machining Parameters for End Milling of Inconel 718 Super Alloy Using Taguchi Based Grey Relational Analysis
    Maiyar, Lohithaksha M.
    Ramanujam, R.
    Venkatesan, K.
    Jerald, J.
    INTERNATIONAL CONFERENCE ON DESIGN AND MANUFACTURING (ICONDM2013), 2013, 64 : 1276 - 1282
  • [48] Process parameters optimization for micro end-milling operation for CAPP applications
    S. P. Leo Kumar
    J. Jerald
    S. Kumanan
    Nargundkar Aniket
    Neural Computing and Applications, 2014, 25 : 1941 - 1950
  • [49] Process parameters optimization for micro end-milling operation for CAPP applications
    Kumar, S. P. Leo
    Jerald, J.
    Kumanan, S.
    Aniket, Nargundkar
    NEURAL COMPUTING & APPLICATIONS, 2014, 25 (7-8): : 1941 - 1950
  • [50] Multi-objective Optimization of Cutting Performance of Variable Density Micro-texture Ball-end Milling Tool
    Tong X.
    Yang S.
    He C.
    Zheng M.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2019, 55 (21): : 221 - 232