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<p>In this research, friction stir welding of AA 6082-T6 to AA 6061-T6 was conducted, and an integrated methodology of both destructive and non-destructive testing was established to characterize the weld defects in the dissimilar alloy joints. An experimental design matrix was established to conduct a series of nine experiments, and it was evaluated by grey relational analysis to determine the most influential combinations of tool rotation and welding speeds. A multiple linear regression model was then developed to relate process settings to joint performance characteristics. These characteristics included yield strength, tensile strength, percentage elongation, microhardness, modulus of toughness, and modulus of resilience. The model demonstrated only moderate predictive accuracy under extreme thermal conditions. Specimens corresponding to top-ranked conditions from the grey relational analysis underwent high-resolution Micro-CT scans to detect and measure subsurface tunnel defects, reporting their height, width, and porosity volume. Subsequently, to reduce such weld defects, controlled variation experiments were performed by varying the tool shoulder diameter with 3&#xa0;mm increments to optimize heat generation and material flow, resulting in the complete mitigation of the tunnel defects. These experimental results provide precise parameter guidelines and confirm that combining statistical optimization, regression modelling, and advanced non-destructive imaging significantly improves the integrity and reproducibility of dissimilar alloy welds.</p>

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Identification and Mitigation of Tunnel Defects in Friction Stir Welding of Dissimilar Aluminum Alloys - AA 6082-T6 and AA 6061-T6

  • 期刊论文

  • 发表日期：

    2025年9月10日

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  • Ramprasad Ganesan,
  • Hema Pothur

摘要

In this research, friction stir welding of AA 6082-T6 to AA 6061-T6 was conducted, and an integrated methodology of both destructive and non-destructive testing was established to characterize the weld defects in the dissimilar alloy joints. An experimental design matrix was established to conduct a series of nine experiments, and it was evaluated by grey relational analysis to determine the most influential combinations of tool rotation and welding speeds. A multiple linear regression model was then developed to relate process settings to joint performance characteristics. These characteristics included yield strength, tensile strength, percentage elongation, microhardness, modulus of toughness, and modulus of resilience. The model demonstrated only moderate predictive accuracy under extreme thermal conditions. Specimens corresponding to top-ranked conditions from the grey relational analysis underwent high-resolution Micro-CT scans to detect and measure subsurface tunnel defects, reporting their height, width, and porosity volume. Subsequently, to reduce such weld defects, controlled variation experiments were performed by varying the tool shoulder diameter with 3 mm increments to optimize heat generation and material flow, resulting in the complete mitigation of the tunnel defects. These experimental results provide precise parameter guidelines and confirm that combining statistical optimization, regression modelling, and advanced non-destructive imaging significantly improves the integrity and reproducibility of dissimilar alloy welds.