The welding process in aluminum is not a simple task to carry out. Problems such as weld bead discontinuity, cracks, and lack of penetration commonly occur in this kind of process. Thus, it is extremely necessary to have an accurate specification of the parameters in order to achieve optimal values for the investigated responses. In view of this, the present paper proposes the application of a multiobjective optimization approach considering multivariate constraints based on the simultaneous confidence intervals and the elliptical region of the correlated data. Structured experiments for the welding process of aluminum alloy (AA) 6063 TA tubes used in corona rings were performed according to a face centered composite design with 4 factors, wire feed rate (Wf), arc voltage (V), contact tip to the workpiece distance (Ct) and motor frequency (Fr), resulting in 31 experiments. Poisson regression was applied to model the values of yield (Y), dilution (D), reinforcement index (RI) and penetration index (PI), allowing to estimate the optimal individual values with regards to the multivariate constraints. Rotated factor scores were obtained in order to replace the original data and therefore the factor multivariate square error was used as objective functions to be minimized through normal boundary intersection method. It was possible to observe that a satisfactory weld bead with large values of PI, D and Y and a small value of RI, was reached as pre specified by the manager of the process.