WEAR MODEL OF SURFACE TREATED LOW CARBON STEEL-BASED ON TAGUCHI EXPERIMENT METHOD USING THE GMAW PROCESS

This article presents the results of optimizing semi-automatic welding process parameters using the Taguchi method and regression analysis. Experiments were designed with the semi-automatic welding process to identify the optimal parameters, which were validated through Analysis of Variance (ANOVA). Additionally, multiple regression analysis was conducted using the MINITAB software to develop a mathematical model predicting wear values under different welding conditions. The study experimentally investigated the effects of parameters such as particle size of the material, coating thickness, and current strength on wear. Results showed that the parameter with the most significant impact on wear was coating thickness, specifically the chromium content, followed by current and particle size of the material.