Abstract
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.
Highlights
Friction stir welding (FSW) was invented at The Welding Institute (TWI) and has been successfully employed to weld aluminum alloys, 2XXX or 7XXX series aluminum alloys, which are especially difficult to weld by using fusion welding techniques [1]
In Equations (9) and (10), I and E represent the maximum possible immigration and emigration rate, respectively; k i is the rank of habitat i after sorting all habitats according to their habitat suitability index (HSI); and n is the number of solutions in the population
The optimal value of the ultimate tensile strength, elongation, and hardness function is obtained by implementing the evolutionary algorithm based on the multi objective biogeography based optimization (BBO) algorithm
Summary
Venkateswarlu et al [19] developed a mathematical model using RSM regression analysis to predict the effects of tool geometry and process variables (i.e., rotational speed, axial force, and traverse speed) on the dissimilar FSW of the AA2219 and AA7039 alloys joint. The objective of this research is to model the relationship between the FSW process parameters (tool rotational speed, tool traverse speed, tool tilt angle, tool offset) and the mechanical properties of interest (i.e., tensile strength, minimum hardness in the HAZ zone, and elongation), while a solution algorithm, the multi-objective biogeography based optimization algorithm (MOBBO), is employed to compute the Pareto optimal frontier in objective space. The best optimal value of the Pareto frontier for three and two objective functions is selected through two different decision making techniques, TOPSIS and Shannon’s entropy
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