The 22MnB5-galvannealed steel is extensively used in the hot stamping process to produce car anti-collision structure parts. Furthermore, the resistance spot welding (RSW) is an important process in the automobile industry, especially in body construction, and the 22MnB5-galvannealed steels are a big challenge for the joining methods because their microstructure and mechanical properties are different from those of the conventional steels. In view of this, the present paper aims to optimize the parameters of the RSW process of the 22MnB5-galvannealed steel. Initially, the goal was to remove the galvannealed coating and in the next stage, the following responses were maximized: the nugget width, the nugget cross-sectional area, the penetration, the strength, the joint efficiency, and the energy absorption, whereas the indentation, heat affected zone and separation were used as constraints. The process parameters selected were the effective welding time, the effective welding current, the quenching time, and the upslope time. Response surface methodology (RSM) was applied jointly with the global criterion method based on principal components. The results of the multiobjective optimization are close to the individual targets for each response, highlighting the importance of considering the correlation structure presented in the responses.
A multiobjective optimization of the welding process in aluminum alloy (AA) 6063 T4 tubes used in corona rings through normal boundary intersection and multivariate techniques
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.
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