Friction Stir Welding of Aluminum Using a Multi-Objective Optimization Approach Based on Both Taguchi Method and Grey Relational Analysis

This work deals with the use of a multi-objective optimization method using a hybrid statistic algorithm to improve the Friction Stir Welding of aluminum alloy AA2195-T8. The hybrid approach combines the Taguchi Method with the Relational Grey Analysis technic. In order to optimize the Friction Stir...

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Published inExperimental techniques (Westport, Conn.) Vol. 47; no. 3; pp. 603 - 617
Main Authors Boukraa, M., Chekifi, T., Lebaal, N.
Format Journal Article Magazine Article
LanguageEnglish
Published Cham Springer International Publishing 01.06.2023
Springer Nature B.V
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Online AccessGet full text
ISSN0732-8818
1747-1567
DOI10.1007/s40799-022-00573-6

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Abstract This work deals with the use of a multi-objective optimization method using a hybrid statistic algorithm to improve the Friction Stir Welding of aluminum alloy AA2195-T8. The hybrid approach combines the Taguchi Method with the Relational Grey Analysis technic. In order to optimize the Friction Stir Welding process, the axial force, the rotational tool velocity, the welding velocity and the shoulder diameter were considered as input parameters while the heat input, the maximal temperature value and the Heat Affected Zone length were chosen as output parameters. In this method, the minimization of the heat input, the HAZ length and the temperature value in the stir zone is the main goal. In the process of improving the aluminum welding by FSW, the axial force is the most influential parameter with a contribution of 52.4%, followed by the rotational tool velocity with 37.4%, then the welding velocity with 6.3% and finally the tool diameter with a contribution of 3.6%. The obtained results from the application of three-dimensional numerical thermal model have confirmed the effectiveness and the robustness of the used optimization approach.
AbstractList This work deals with the use of a multi-objective optimization method using a hybrid statistic algorithm to improve the Friction Stir Welding of aluminum alloy AA2195-T8. The hybrid approach combines the Taguchi Method with the Relational Grey Analysis technic. In order to optimize the Friction Stir Welding process, the axial force, the rotational tool velocity, the welding velocity and the shoulder diameter were considered as input parameters while the heat input, the maximal temperature value and the Heat Affected Zone length were chosen as output parameters. In this method, the minimization of the heat input, the HAZ length and the temperature value in the stir zone is the main goal. In the process of improving the aluminum welding by FSW, the axial force is the most influential parameter with a contribution of 52.4%, followed by the rotational tool velocity with 37.4%, then the welding velocity with 6.3% and finally the tool diameter with a contribution of 3.6%. The obtained results from the application of three-dimensional numerical thermal model have confirmed the effectiveness and the robustness of the used optimization approach.
Author Chekifi, T.
Boukraa, M.
Lebaal, N.
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  surname: Lebaal
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  organization: Université Bourgogne Franche-Comté, UTBM, Laboratoire interdisciplinaire Carnot de Bourogne, UMR CNRS6303/90010
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Keywords Variance analyses
Multi-objective optimization
FSW
Taguchi orthogonal Array (OA)
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Heat transfer
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Snippet This work deals with the use of a multi-objective optimization method using a hybrid statistic algorithm to improve the Friction Stir Welding of aluminum alloy...
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SubjectTerms Alloys
Aluminum alloys
Aluminum base alloys
Axial forces
Characterization and Evaluation of Materials
Chemistry and Materials Science
Diameters
Friction stir welding
Genetic algorithms
Heat affected zone
Heat transfer
Materials Science
Multiple objective analysis
Optimization
Optimization algorithms
Parameters
Research Paper
Taguchi methods
Thermal analysis
Variance analysis
Velocity
Title Friction Stir Welding of Aluminum Using a Multi-Objective Optimization Approach Based on Both Taguchi Method and Grey Relational Analysis
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