Articles
  • Optimization of welding parameters for better tensile strength through Coupled Genetic Algorithm and Firefly Algorithm for AA7010-SiC-Al2O3 hybrid composite

  • P. Gopi Krishnana,*, R. Srinivasanb, D. Pritimac and A. Bovas Herbert Bejaxhind

  • aAssistant Professor, Department of Mechanical Engineering, Dr.N.G.P. Institute of Technology, Coimbatore, Tamil Nadu, India
    bAssociate Professor, Department of Mechanical Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
    cProfessor, Department of Mechatronics Engineering, Sri Krishna College of Engineering & Technology, Coimbatore, Tamil Nadu, India
    dAssociate Professor, Department of Mechanical Engineering, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, 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

Friction stir welding (FSW) is a green manufacturing process that does not liberate smoke, fume and odour unlike the conventional arc welding. This research article aims at finding the ultimate tensile strength of the Aluminium matrix composites welded by FSW with the process parameters such as tool rotation speed, weld traverse speed and axial force. The search optimization is carried out in two phases using MATLAB environment. Firstly, the regression equation of the experiments is utilized to find the better design points by Genetic Algorithm (GA) through pool generation, cross-over and mutation. Secondly, the top design points obtained in GA are stored in a new pool, from which the global best optimal design is selected by Firefly Algorithm (FA). Since, every algorithm has different features and highlights, the coupled GA-FA algorithm is utilized to obtain the optimal point that gives the best ultimate tensile strength of the welded composite. The results demonstrate that the optimal points are distributed in several points of design space that needs to be searched out by the effective optimization strategy. The convergence rate, speed of the optimization and coverage of the design points are also improved. The algorithm shows good agreement with the confirmation tests also with errors less than 5%.


Keywords: Optimization, Metaheuristics, Genetic algorithm, Firefly algorithm, Friction stir welding.

This Article

  • 2023; 24(6): 1050-1059

    Published on Dec 31, 2023

  • 10.36410/jcpr.2023.24.6.1050
  • Received on Aug 23, 2023
  • Revised on Nov 13, 2023
  • Accepted on Dec 16, 2023

Correspondence to

  • P. Gopi Krishnan

  • Assistant Professor, Department of Mechanical Engineering, Dr.N.G.P. Institute of Technology, Coimbatore, Tamil Nadu, India
    Tel : +91-8940585563 Fax: +91-422-2369106

  • E-mail: gopikrishnan2864@gmail.com