Determination of Optimal Process Parameters of Friction Stir Welding to Join Dissimilar Aluminum Alloys Using Artificial Bee Colony Algorithm

• Published in: Transactions of the Indian Institute of Metals Vol. 71; no. 2; pp. 453 - 462
• Main Authors: Prasanth, R. S. S., Hans Raj, K.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.02.2018; Springer Nature B.V
• Subjects: Algorithms; Aluminum alloys; Aluminum base alloys; Axial stress; Chemistry and Materials Science; Corrosion and Coatings; Dissimilar material joining; Elongation; Empirical analysis; Friction stir welding; Materials Science; Mechanical properties; Metallic Materials; Parameter estimation; Process parameters; Response surface methodology; Search algorithms; Swarm intelligence; Technical Paper; Tribology; Ultimate tensile strength; Variance analysis; Welded joints; Welding parameters; Artificial bee colony; Response surface methodology; Design of experiments; Friction stir welding; Optimization
• ISSN: 0972-2815; 0975-1645
• DOI: 10.1007/s12666-017-1176-9

This paper presents the efforts of joining dissimilar aluminum alloys (AA6351-T6 and AA6061-T6) by friction stir welding (FSW) process. FSW experiments are conducted according to the three factors five level central composite rotatable design method, and the response surface methodology was used to establish the empirical relationship between FSW process parameters such as tool rotational speed ( N ), tool traverse speed ( S ) and axial force ( F ), and the response variables such as ultimate tensile strength, yield strength, and percentage of elongation. The developed empirical models’ adequacies are estimated using the analysis of variance technique. This paper also presents the application of the artificial bee colony algorithm to estimate the optimal process parameters to achieve good mechanical properties of FS weld joints. Results suggest that the estimations of the algorithm are in good agreement with the experimental findings.