Articles
  • A grey fuzzy approach based machining process parameters optimization for Al 6063 alloy

  • P. Saravana Kumara,*, Sujit Kumarb, S. Pradeepc, Tushar Yashawant Badgujard, B. Krishnavenie, G. Mahendranf, Dhivakar Poosapadig, M. Premalathah, G.S.V. Seshu Kumari and K.K. Arunj

  • aDepartment of Mechanical Engineering, University College of Engineering, Arni, Tamil Nadu, India
    bDepartment of Electrical and Electronics Engineering, Amrita School of Engineering, Bengaluru, India
    cDepartment of Electronics and Communication Engineering, S.A Engineering College, Tamil Nadu, India
    dDepartment of Mechanical Engineering, Late G. N. Sapkal College of Engineering, Nashik, Maharashtra, India
    eDepartment of Mathematics, Aditya University, Surampalem, Andhra Pradesh, India
    fDepartment of Mechanical Engineering, Chennai Institute of Technology, Chennai, Tamil Nadu, India
    gLead Engineer, Quest Global North America, Windsor, USA
    hDepartment of Mathematics, VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India
    iDepartment of Mechanical Engineering, SRKR Engineering College, Andhra Pradesh, India
    jDepartment of Mechanical Engineering, Kumaraguru College of Technology, Tamilnadu, India

  • This article is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

An experimental study was conducted to optimize both the surface roughness and material removal rate in the end milling process of Al-6063 alloy. Grey relational coefficients determined by using grey relational normalized formula. GRG values are analyzed and optimum level of process parameters that lead to highest GRG value indicates the overall performance of the output characteristics. ANOVA analysis is performed to determine the influencing parameter in end milling process. The optimum process parameters are determined using fuzzy logic and grey relational grade and it is found that grey relational grade is improved and provides minimum surface roughness and maximum material removal rate.


Keywords: ANOVA, End milling, Fuzzy logics, Grey relation analysis, MRR, Surface roughness.

This Article

  • 2025; 26(3): 502-506

    Published on Jun 30, 2025

  • 10.36410/jcpr.2025.26.3.502
  • Received on Apr 8, 2025
  • Revised on May 26, 2025
  • Accepted on Jun 2, 2025

Correspondence to

  • P. Saravana Kuma

  • Department of Mechanical Engineering, University College of Engineering, Arni, Tamil Nadu, India
    Tel : 04173244400

  • E-mail: psk.ucearni@gmail.com