Comprehensive exploration, modeling, and optimization of end milling parameters for magnesium AZ41 using multicriteria decision-making approach

This work is planned to comprehend the selection of desirable end milling parameters on magnesium AZ41. During machining, spindle speed (SS), feed rate (FR), and depth of cut (DoC) were systematically varied to assess their influence on the efficiency of the machining process. The surface characteristic of the current study was done by scanning electron microscope (SEM) and surface roughens tester. These SEM images explain the texture together with the morphology and composition in association, with the intermetallic phase found on the surface with presence of zinc and aluminum percentage more than Mg. It ensures that, the presence of aluminum content improves surface quality. Selecting optimal parameters in machining requires balancing cost minimization and quality maximization, posing a multiple criteria decision-making challenge. This study addresses the stated issue by employing the evaluation based on distance from average solution (EDAS) method. Further, the response surface methodology (RSM) is applied to build the empirical model through Taguchi design. The empirical model is proposed with a higher correlation coefficient of 0.9806, 0.9961, and 0.9629 for machining time, surface roughness, and material removal rate, respectively. Following the successful development of the model, optimization was performed using the desirability function approach (DFA), which allowed us to balance multiple objectives and achieve the desired outcomes. Optimization studies reveal varying surface roughness levels, with controlled shearing action, FR, and DoC influencing the results. The optimized input parameters concerning multiobjective criteria were found with the SS of 3443.7 rpm and FR of 500 m/min, and DoC of 0.65 mm. The optimized results of EDAS and DFA were found concurrently.