Optimization of Submerged Arc Welding process Parameters Using PCA-Based Taguchi Approach.

Abstract

The present study highlights Optimization of submerged arc welding (SAW) process parameters in order to obtain optimal parametric combination to yield favourable weld bead geometry in mild steel plates IS 2062. Taguchi’s L₂₅ orthogonal array (OA) design and signal- to- noise ratio (S/N ratio) have been used in this study.Penetration (P), bead width (W), reinforcement (R) and Percentage dilution (D) are selected as objective functions. The principal component analysis coupled with Taguchi method has been applied to solve this multi response optimization problem. Carried out to meet basic assumption of Taguchi method, individual response correlations have been eliminated first by means of principal component analysis (PCA).The correlated responses then transformed into uncorrelated or independent quality indices called principal components. The principal components converted as single objective function called multiple performance index (MPI). The developed models have checked for adequacy and significance based on ANOVA test. Accuracy of optimization was confirmed by conducting confirmation tests. Results indicate feasibility of Taguchi analysis coupled with principal component analysis (PCA) in continuous improvement in welding industry.