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Multi-Performance Optimization in Friction Stir Welding of AA6082/B4C Using Genetic Algorithm and Desirability Function Approach for Aircraft Wing Structures

Multi-Performance Optimization in Friction Stir Welding of AA6082/B4C Using Genetic Algorithm and... This study intended to optimize the process parameters of the friction stir welding (FSW) technique to maximize the mechanical properties of the AA6082/B4C composite weldments. The metal matrix composites are prepared with aluminum alloy 6082 and boron carbide particles of 10µm size by using a stir casting technique. The central composite design technique is applied to design the FSW experiments. The experiments were carried out in butt joint configuration by varying welding transverse speed, axial load, plunge depth, and tool rotational speed. The optimum parameters are estimated by considering output responses such as ultimate tensile strength and microhardness. The effect of process parameters on output responses was analyzed graphically. Two optimization techniques, namely genetic algorithm and desirability function approach, are implemented to identify the optimal values of process parameters. The results obtained by both optimization techniques are in good agreement. The optimum values are validated with experimental results. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Materials Engineering and Performance Springer Journals

Multi-Performance Optimization in Friction Stir Welding of AA6082/B4C Using Genetic Algorithm and Desirability Function Approach for Aircraft Wing Structures

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Publisher
Springer Journals
Copyright
Copyright © ASM International 2021
ISSN
1059-9495
eISSN
1544-1024
DOI
10.1007/s11665-021-05842-w
Publisher site
See Article on Publisher Site

Abstract

This study intended to optimize the process parameters of the friction stir welding (FSW) technique to maximize the mechanical properties of the AA6082/B4C composite weldments. The metal matrix composites are prepared with aluminum alloy 6082 and boron carbide particles of 10µm size by using a stir casting technique. The central composite design technique is applied to design the FSW experiments. The experiments were carried out in butt joint configuration by varying welding transverse speed, axial load, plunge depth, and tool rotational speed. The optimum parameters are estimated by considering output responses such as ultimate tensile strength and microhardness. The effect of process parameters on output responses was analyzed graphically. Two optimization techniques, namely genetic algorithm and desirability function approach, are implemented to identify the optimal values of process parameters. The results obtained by both optimization techniques are in good agreement. The optimum values are validated with experimental results.

Journal

Journal of Materials Engineering and PerformanceSpringer Journals

Published: May 19, 2021

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