OPTIMIZATION AND PREDICTION OF THE PERCENTAGE ELONGATION OF MILD STEEL WELD METAL USING RSM AND ANN

Abstract

This research study is centered on the optimization and prediction of Percentage Elongation of Mild steel weld metal using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) from Tungsten Inert Gas (TIG) welding process. Welding Current, Welding Voltage and Gas Flow Rate are the process input parameters and the response variable is Percentage Elongation. The final solution of the optimization process is to determine the most appropriate percentage combination of the Percentage Elongation with the optimum values of Current, Voltage and the Gas Flow Rate that will adequately optimize (maximize) the Percentage Elongation of the Mild Steel weld metal. Percent elongation is a mechanical property of a metal that indicates the degree to which a metal may be bent, stretched or compressed before it ruptures. It’s an important quality for metals used in welding, as they need to be able to withstand the high temperatures and stresses involved in the welding process. Optimizing this process is one sure way of producing a quality weld.

The RSM model produced the numerical optimal solution for the weldment of Mid Steel (MS). The model Coefficient of Determination (R²) and Adjusted R² for Percentage Elongation are 93.48% and 87.61% respectively. The Optimal Solutions for the input parameters are; Welding Current, 180.00Amps, Welding Voltage, 21.672Volts and Gas Flow Rate, 15.504L/min. The Optimal Solution for the response variable, Percentage Elongation is 22.111%. From the analysis of variance (ANOVA), it was observed that Gas Flow Rate (GFR) input parameter has more significant effect on the Percentage Elongation response variable. The ANN analysis predicted an optimal solution for the Percentage Elongation response variable to be 18.5044%, with an overall strong correlation (R) between the input factors and the response variable to be 99.89%. Therefore, it is advised that the models be used to navigate the design space.

KEYWORDS:  TIG, Mild Steel, Percentage Elongation, RSM, ANN