Hybrid technique of MARCOS-Taguchi approach for multi-purpose optimization of friction stir spot welded AA6063 alloy integrated with silicon carbide and graphite

Friction stir spot welding (FSSW) is a popular technique for solid-state welding of both weldable and non-weldable materials. As part of this investigation, Al6063-T6 weld specimens were strengthened with silicon carbide (SiC, ∼2 wt.%, average particle size ≈ 10 μm) and graphite (Gr, ∼1 wt.%, average particle size ≈ 8 μm) particles. The current study focused on optimizing the multi-objective FSSW process to achieve the optimal combination of process parameters for stronger welds. The Taguchi L16 orthogonal array was used to design experiments on process factors, including the dwell time, tool shoulder diameter, and tool pin length. Tensile-shear strength and flash height were the two output quality characteristics measured. Multi-objective optimization was performed using a hybrid measurement of alternatives and ranking based on the Compromise Solution (MARCOS)-Taguchi technique. The significance of parameters was determined utilizing the analysis of variance technique, and a confirmatory test verified the optimality of the results. The optimal combination of parameters achieved by Taguchi was also confirmed by the MARCOS method, indicating that both approaches can be used with high reliability to optimize weld quality characteristics. It was observed that the maximum weld strength was achieved with a 2 mm pin length, a 15 mm shoulder diameter, a 1000 rpm rotation speed, and a 9 s dwell time. Pin length had a significant impact on weld quality, followed by rotation speed, shoulder diameter, and dwell time. The presence of SiC and Gr reinforcement improved microhardness and tensile-shear strength. The MARCOS-Taguchi approach effectively optimized FSSW process parameters, with confirmatory testing validating the results. MARCOS reduced the prediction error to 0.3% compared to 4.1% in Grey Relational Analysis (GRA) and 3.9% in Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).