|
CSME 2020/08
Volume 41 No.4
:
513-520
|
|
Predicting the Tensile Strength of Metal Matrix Composites Joined by Friction Stir Welding and Optimization of Parameters using Firefly Algorithm
C.Devanathan a, A.Suresh Babu b, R.Giri c and A.Azad b
aDepartment of Mechanical Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India.
bDepartment of Manufacturing Engineering, Anna University, Chennai, Tamil Nadu, India.
cDepartment of Mechatronics Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India.
|
Abstract:
Friction stir welding is a novel green welding technique developed primarily to weld lightweight materials like aluminum alloys, now extended to variety of materials including steels and metal matrix composites. In the present work, an attempt was made to join Metal Matrix Composites of Al 5083 reinforced with B4C particles using AlCrN Coated tool with square pin profile in order to observe the tensile strength of the welded joint. Joints were prepared by changing the spindle speed, tool traverse feed and axial force in three different levels based on Box Behnken method. A mathematical model for tensile strength of the joints was developed in terms of process parameters. To ensure the adequacy of the developed mathematical model ANOVA technique was used and results showed that, model was adequate to 95% confidence level. The effect of process parameters on Tensile strength of welded composites has been analyzed in detail. In order to find the optimized process parameters the newly developed metaheuristic algorithm firefly was applied and obtained the best results of 152.72MPa for the parameters of spindle speed 1500 rpm, tool traverse feed 20 mm/min, and axial force 6 kN. To understand the behavior of the welded specimen Macrostructure and microstructural analysis was carried out. Condition of the tool after welding was discussed briefly with SEM analysis.
|
|
Keywords: Friction Stir Welding, AlCrN Coated tools, Fire fly Algorithm, parameter optimization, Metal Matrix Composites.
|
Download PDF
|
|
*Corresponding author; e-mail:
|
©
2020
CSME , ISSN 0257-9731
|