OPTIMIZING FSW PARAMETERS FOR AZ31B-AA6082 ALLOYS USING HYBRID MCDM AND MULTI-OBJECTIVE RSM MODELS: A NUMERICAL DECISION-MAKING APPROACH

This paper presents the development of an innovative numerical decision-making model aimed at identifying the optimal combination of process parameters during friction stir welding (FSW) of dissimilar AZ31B magnesium (Mg) and AA6082 aluminum (Al) alloy plates. The study considered not only the tool's traverse speed and rotational speed as input parameters but also the positioning of the AZ31B Mg alloy on either the advancing side (AS) or the retreating side (RS). A total of 21 experimental runs were conducted, with tensile strength, elongation percentage, impact energy, and hardness evaluated as performance outcomes. In the first phase, a multi-criterion decision-making (MCDM) methodology was employed to develop the numerical model and identify the ideal set of parameters. To ensure the model's reliability and accuracy, a sensitivity analysis was conducted. The results obtained from the MCDM model were validated by comparing them with those derived from a fuzzy logic-based decision-making approach. In the second phase, a response surface methodology (RSM) was applied to construct a numerical model using multivariate regression. A trade-off analysis, utilizing a multi-objective RSM approach, was performed to optimize the parameter combination. The optimal solution, computed through this approach, was further validated via a confirmation experiment. The ideal combination of process parameters - rotational speed of 841.42rpm, traverse speed of 0.5mm/s, and positioning of AZ31B Mg alloy on the advancing side - yielded a tensile strength of 214.65MPa, elongation of 10.76%, hardness of 74.89HV, and an impact energy of 6.01J. This research paper demonstrates the effectiveness of the proposed hybrid MCDM-RSM model in accurately determining the optimal FSW parameters and highlights its potential application in similar joining processes.