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

The present study highlights optimization of submerged arc welding (SAW) process parameters in order to obtain optimal parametric combination to yield favorable 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. Based on individual principal components a Multi-response Performance Index (MPI) has been introduced to derive an equivalent single objective function which has been optimized using Taguchi method. Developed model has been checked for adequacy and significance based on ANOVA test. Accuracy of optimization was confirmed by conducting confirmation tests. The study highlights effectiveness of the proposed method for solving multi-objective optimization of submerged arc weld.