modeling and optimization of flux assisted tungsten inert gas welding process using taguchi method and statistical analysis

Flux assisted tungsten inert gas welding process known as activated tungsten inert gas welding process is being extensively used in order to improve the performance of tungsten inert gas  welding process. in this paper, welding current, welding speed and welding gap have been considered as process input variables in fabricating of aisi316l austenitic stainless steel parts. depth of penetration and weld bead width have been taken in to account as process response parameters. in this paper sio2, nanoparticles have been considered as an activating flux. to gather required data for modeling and optimization purposes, taguchi method has been employed. then, process response parameters have been measured and their corresponding signal to noise ratios have been calculated. next, different regression equations have been applied on signal to noise ratio values and the most fitted ones have been selected. furthermore, welding current has been determined as the most important parameter affects depth of penetration and weld bead width with 68% and 88% percent contribution respectively. next, signal to noise analysis, in such a way that weld bead width minimized and depth of penetration is maximized has been used. finally, experimental performance evaluation tests have been carried out, based on which it can be concluded that the proposed procedure is quite efficient (with less than 7% error) in modeling and optimization of the process.