Optimization of tensile strength in TIG welding using the Taguchi method and analysis of variance (ANOVA)

The main criteria discussed in this paper concern the welding optimization parameters and tensile strength of duplex stainless steel 2205 by tungsten inert gas welding based on Taguchi method and analysis of variance. Taguchi method of orthogonal L9 design experiment is carried out using orthogonal array for defining the problem occur on welding process and to reduce the error occurred in the neural network for the prediction of output. The neural network is a mathematical prediction model for the optimization process using back propagation algorithm. Analysis of variance (ANOVA) is a decision tool for detecting the variation of process parameters, it is a statistical technique for find out the optimal level of factors for the verification of the optimal design parameters through confirmation experiments. The purpose of this paper to increase the tensile strength, hardness and depth of weld by varying the parameters such as current, time, speed, variation of oxide fluxes, electrode diameter and gas flow rate. The Mat lab software is used for analyzing results and it shows that neural network coupled with Taguchi method and Anova is an effective method for optimizing the weld quality of material.