An enhanced mean signal-to-noise ratio strategy for multi-parametric optimizations of friction stir welding (FSW) of dissimilar AA6061/AA7075 thick Al-alloy joints by using Taguchi’s–Grey relational analysis method: unveiling the microstructural morphological characterizations
Аннотация
Abstract The lightweight materials are highly suitable in the automotive, transportation, marine, defense, rail and other industrial sectors, due to their excellent strength-to-weight ratio. The environmentally friendly Friction Stir Welding (FSW) method was used in this work to produce solid-state joints with polygonal pin profiles. Weld trails were designed using an orthogonal array of L27 runs with five parameters each at three levels. AA6061/AA7075 Al-alloys in a dissimilar combination were processed using the polygonal pin profiles. The regression Eq. helps in developed the mathematical model to frame the relationship between input parameters to responses. In order to obtain precise F and P values the current work concentrated on determining the optimal condition by using predicted mean values of the outcomes. The experimental test results proved that, the highest values of Ultimate Tensile Strength, Yield Strength, Hardness and Flexural Strength of weld joint are measured as 237 MPa, 223 MPa, 122 HV, and 262 MPa respectively. The maximum joint efficiency of the sample 11, processed at a tool rotational speed of 900 rpm, weld speed of 20 mm/min, Tilt angle of 1o, offset of 1.5 mm and with a hybrid square profile is found as 87%, which is validated by American Welding Society (AWSD17) standards.
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