Comparative experimental and statistical study of conventional and bobbin tool friction stir welding of AA6061-T6 aluminum alloy
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| Udgivet i: | Journal of Engineering and Applied Science vol. 72, no. 1 (Dec 2025), p. 255 |
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Springer Nature B.V.
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| 024 | 7 | |a 10.1186/s44147-025-00834-2 |2 doi | |
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| 100 | 1 | |a Yacout, George G. |u German University in Cairo, Engineering Design and Production Department, Faculty of Engineering and Materials Science, Cairo, Egypt (GRID:grid.187323.c) (ISNI:0000 0004 0625 8088) | |
| 245 | 1 | |a Comparative experimental and statistical study of conventional and bobbin tool friction stir welding of AA6061-T6 aluminum alloy | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This study provides a comprehensive comparative analysis of Conventional Friction Stir Welding (CFSW) and Bobbin Tool Friction Stir Welding (BTFSW) for AA6061-T6 aluminum alloy plates. A factorial experimental design was employed to systematically investigate the effects of rotational speed, feed rate, tilt angle or pinching gap, plunge depth, and tool pin profile on joint performance. Regression models for ultimate tensile strength (UTS) and Vickers micro-hardness (HV) were developed and validated through analysis of variance (ANOVA), with all models exhibiting excellent fit (R2 > 0.99) and strong predictive capability. The results demonstrate that both CFSW and BTFSW can achieve high-quality, defect-free welds, with CFSW yielding a maximum UTS of 241.52 MPa and BTFSW achieving comparable strength and superior hardness (up to 101.26 HV with a threaded pin). ANOVA revealed rotational speed and tool profile as the most significant factors for UTS, while feed rate and pin geometry predominantly governed hardness. Response surface analysis identified pronounced interaction and quadratic effects, highlighting the importance of simultaneous optimization of multiple process parameters. BTFSW outperformed CFSW in terms of process flexibility, hardness, and defect mitigation, attributed to its symmetrical heat input and elimination of the backing plate. The study delivers validated predictive equations and detailed process maps to guide industrial practitioners in optimizing Friction Stir Welding (FSW) parameters for AA6061-T6, ultimately enabling the tailored achievement of superior mechanical properties and weld integrity.Highlights• This study systematically compares the mechanical performance and process response of Conventional FSW and Bobbin Tool FSW configurations for AA6061-T6 aluminum alloy, using identical experimental protocols and advanced statistical modeling.• Regression models validated by ANOVA and diagnostic plots (R² > 0.99) accurately predict ultimate tensile strength and hardness based on key process variables, providing a reliable framework for process optimization.• Results reveal that BTFSW offers superior hardness, process flexibility, and defect mitigation over CFSW, while both methods achieve comparable peak tensile strengths when optimally configured.• Optimized process maps and validated models are provided as practical tools for industry practitioners to achieve tailored mechanical properties and high-quality welds in AA6061-T6, supporting flexible implementation in advanced manufacturing. | |
| 653 | |a Process variables | ||
| 653 | |a Design of experiments | ||
| 653 | |a Spools | ||
| 653 | |a Friction stir welding | ||
| 653 | |a Regression models | ||
| 653 | |a Optimization | ||
| 653 | |a Mechanical properties | ||
| 653 | |a Response surface methodology | ||
| 653 | |a Surface analysis (chemical) | ||
| 653 | |a Variance analysis | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Pareto optimum | ||
| 653 | |a Defects | ||
| 653 | |a Shear tests | ||
| 653 | |a Tensile strength | ||
| 653 | |a Metal plates | ||
| 653 | |a Welding parameters | ||
| 653 | |a Ultimate tensile strength | ||
| 653 | |a Metal fatigue | ||
| 653 | |a Aluminum alloys | ||
| 653 | |a Welded joints | ||
| 653 | |a Process mapping | ||
| 653 | |a Flexibility | ||
| 653 | |a Feed rate | ||
| 653 | |a Alloys | ||
| 653 | |a Statistical models | ||
| 653 | |a Aluminum base alloys | ||
| 653 | |a Process parameters | ||
| 700 | 1 | |a Shash, A. Y. |u German University in Cairo, Engineering Design and Production Department, Faculty of Engineering and Materials Science, Cairo, Egypt (GRID:grid.187323.c) (ISNI:0000 0004 0625 8088); Cairo University, Mechanical Design and Production Engineering Department, Faculty of Engineering, Giza, Egypt (GRID:grid.7776.1) (ISNI:0000 0004 0639 9286) | |
| 700 | 1 | |a Hegazi, Hesham A. |u German University in Cairo, Engineering Design and Production Department, Faculty of Engineering and Materials Science, Cairo, Egypt (GRID:grid.187323.c) (ISNI:0000 0004 0625 8088); Cairo University, Mechanical Design and Production Engineering Department, Faculty of Engineering, Giza, Egypt (GRID:grid.7776.1) (ISNI:0000 0004 0639 9286) | |
| 700 | 1 | |a El-Sherbiny, Mahmoud G. |u Cairo University, Mechanical Design and Production Engineering Department, Faculty of Engineering, Giza, Egypt (GRID:grid.7776.1) (ISNI:0000 0004 0639 9286) | |
| 773 | 0 | |t Journal of Engineering and Applied Science |g vol. 72, no. 1 (Dec 2025), p. 255 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3284826523/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3284826523/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3284826523/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |