Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm

The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process par...

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Bibliographic Details
Main Authors: Tamjidy, Mehran, Baharudin, B. T. Hang Tuah, Paslar, Shahla, Matori, Khamirul Amin, Sulaiman, Shamsuddin, Fadaeifard, Firouz
Format: Article
Language:English
Published: MDPI 2017
Online Access:http://psasir.upm.edu.my/id/eprint/43947/1/materials-10-00533.pdf
http://psasir.upm.edu.my/id/eprint/43947/
http://www.mdpi.com/1996-1944/10/5/533
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Summary:The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon’s entropy.