Influence of the welding parameters on the heat affected zone for aluminium welding

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

“…Some factors that possibly have great influence on the welding process were stated in Table 3 after some research in the literature [5,8,46,47]. Their levels were also established not only according to the values found in literature, but mainly according to some experiments performed by the authors.…”

“…The use of aluminum is due to its weight, since it is lighter when compared with other metals, and because AA 6063 presents an electrical conductivity that satisfies the projects of companies such as the electric energy segment, consumers of this kind of product. Among studies such as [4][5][6][7], special attention has been given to the welding of different aluminum alloys, whose usage by the energy industry is extremely intense due to good corrosion resistance, good mechanical properties and excellent electrical conductivity. Aluminum welding is a really complex task and requires well defined parameters to present a satisfactory result, with no defects such as porosity, cracks, lack of penetration, lack of fusion, filling failures, etc.…”

“…In [5], whose main objective was the optimization of the HAZ, RSM was exploited. This method allowed the optimization of the response function, subjected to different independent variables after modelling the influence of these variables with a minimum number of experiments.…”

“…Furthermore, in [9], an experimental design is presented for a GMAW welding process to maximize the amount of information with the following characteristics: response surface-based modelling (RSM) to quantify response variables of interest; statistical model selection to obtain the most informative models; statistical model checking for definitive models to ensure inference capabilities; and multiobjective optimization to identify the Pareto front of optimal solutions. Several papers found in literature [5,6,[9][10][11][12] use techniques such as factor analysis, normal boundary intersection (NBI) and RSM for multiobjective optimization. However, they combine NBI and multivariate mean square error (MMSE), disregarding multivariate constraints.…”

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

“…Among studies such as [4][5][6][7], special attention has been given to the welding of different aluminum alloys, whose usage by the energy industry is extremely intense due to good corrosion resistance, good mechanical properties and excellent electrical conductivity. Aluminum welding is a really complex task and requires well defined parameters to present a satisfactory result, with no defects such as porosity, cracks, lack of penetration, lack of fusion, filling failures, etc.…”