Use of Tungsten Inert Gas Welding on Mild Steel Weldment to Optimize Welding Process Variables on Electrode Melting Rate

Abstract

One of the most crucial factors taken into account when evaluating the performance of Tungsten Inert Gas (TIG) welding is the Electrode Melting Rate, which shows how much of the heat deposited by the welding operation is used to generate melting. A dense weld pool forms in the field of welding when there is a good melting rate. Therefore, this paper investigates the use of tungsten inert gas welding on mild steel weldment to optimize welding process variables on electrode melting rate employing Artificial Neural Networks and Response Surface Methodology in the analysis. The ideal electrode melting rate of 4.6539 mm/s can be achieved by combining the following parameters: wire diameter of 2.55 mm, welding speed of 3.02 mm/s, and welding current of 208.22A, according to the RSM results. R values of 0.9119 were displayed by the RSM for the electrode melting rate. A regression plot of the ANN results indicates that the total R value is 0.93807. Because the Artificial Neural Network's output fits the experimental data more closely than the Response Surface Methodology's, it is chosen as the superior predictive model.

Keywords

• Electrode melting rate; Weldment; tungsten inert gas welding; mild steel welds; r0esponse surface methodology; artificial neural network