Multi attribute decision making parametric optimization in weld bead by gas metal arc welding through grey relation analysis: A case study

Abstract

The basic purpose of this study was to identify the effect of gas metal arc (GMA) welding process parameters on the weld bead geometry of IS2062 structural steel of A grade. L16 Taguchi orthogonal array (OA) design with the idea of S/N (signal to noise) ratio was applied to obtain objective function to be optimized within the experimental field. In this research work the Taguchi technique was joined with grey relational analysis to solve the multi-response optimization problem. ANOVA (Analysis of Variance) was applied to estimate the most significant input parameters which contribute toward the output parameters. Arc voltage, gas flow rate, and wire feed speed were carefully selected as input parameters, whereas weld bead, depth of penetration, and reinforcement were output respectively. The optimal GMA welding process parameters were identified in order to enhance the productivity and curtail the overall functional cost of weld.

Keywords: grey-relational analysis (GRA), Taguchi technique, optimization, GMAW, ANOVA.