Mathematical Modeling for Prediction and Optimization of Tig Welding Pool Geometry

TIG welding is an arc-welding process that produces coalescence of metals by heating them with an arc between a non-consumable tungsten electrode and the base metal 1 . Many delicate components in aircraft and nuclear reactors are TIG welded due to its reliability. Basically, TIG weld quality is strongly characterized by the weld pool geometry as shown in Figure 1. This is because the weld pool geometry plays an important role in determining the mechanical properties of the weld 2 . TIG welding is a highly non-linear, strongly coupled, multivariable process 3, 4, 5 . The weld pool geometry and, hence, the quality of TIG welded joints are greatly dependent on the selection of input control variables such as welding speed (V), welding current (I), shielding gas flow rate (F) and gap distance (G). Therefore, in the TIG welding, engineers often face with the problem of selecting appropriate and optimum combinations of input control variables for the required weld pool quality. In this work, nonlinear and multi-objective mathematical models are developed for the selection of the optimum processes parameters. First, the upper and lower limits of the input control variables are obtained and the effect of the input control variables on the weld pool quality parameters is determined. Then, the mathematical relationships between the input control variables and weld pool quality parameters are obtained. These relationships are considered as objective functions in the mathematical models. To the best of our knowledge the optimization problem of the TIG welding using nonlinear and multi-objective mathematical models has not been investigated previously and applied on real life case study like in this work.