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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| Language: | English |
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MDPI
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/43947/ http://psasir.upm.edu.my/id/eprint/43947/1/materials-10-00533.pdf |
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| author | Tamjidy, Mehran Baharudin, B. T. Hang Tuah Paslar, Shahla Matori, Khamirul Amin Sulaiman, Shamsuddin Fadaeifard, Firouz |
| author_facet | Tamjidy, Mehran Baharudin, B. T. Hang Tuah Paslar, Shahla Matori, Khamirul Amin Sulaiman, Shamsuddin Fadaeifard, Firouz |
| author_sort | Tamjidy, Mehran |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T10:05:09Z |
| format | Article |
| id | upm-43947 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:05:09Z |
| publishDate | 2017 |
| publisher | MDPI |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-439472018-08-13T02:20:13Z http://psasir.upm.edu.my/id/eprint/43947/ Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm Tamjidy, Mehran Baharudin, B. T. Hang Tuah Paslar, Shahla Matori, Khamirul Amin Sulaiman, Shamsuddin Fadaeifard, Firouz 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. MDPI 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/43947/1/materials-10-00533.pdf Tamjidy, Mehran and Baharudin, B. T. Hang Tuah and Paslar, Shahla and Matori, Khamirul Amin and Sulaiman, Shamsuddin and Fadaeifard, Firouz (2017) Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm. Materials, 10 (5). art. no. 533. pp. 1-19. ISSN 1996-1944 http://www.mdpi.com/1996-1944/10/5/533 10.3390/ma10050533 |
| spellingShingle | Tamjidy, Mehran Baharudin, B. T. Hang Tuah Paslar, Shahla Matori, Khamirul Amin Sulaiman, Shamsuddin Fadaeifard, Firouz Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm |
| title | Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm |
| title_full | Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm |
| title_fullStr | Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm |
| title_full_unstemmed | Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm |
| title_short | Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm |
| title_sort | multi-objective optimization of friction stir welding process parameters of aa6061-t6 and aa7075-t6 using a biogeography based optimization algorithm |
| url | http://psasir.upm.edu.my/id/eprint/43947/ http://psasir.upm.edu.my/id/eprint/43947/ http://psasir.upm.edu.my/id/eprint/43947/ http://psasir.upm.edu.my/id/eprint/43947/1/materials-10-00533.pdf |