Optimization of Process Parameters in Submerged Arc Welding Using Multi-objectives Taguchi Method

Abstract

Submerged arc welding (SAW) is one of the oldest automatic welding processes to provide high quality of weld. The quality of weld in SAW is mainly influenced by independent variables such as welding current, arc voltage, welding speed, and electrode stick out. The prediction of process parameters involved in SAW is very complex process. Researchers attempted to predict the process parameters of SAW to get smooth quality of weld. This paper presents an alternative method to optimize process parameters of SAW of IS: 2062, Gr B mild steel with multi-response characteristics using Taguchi’s robust design approach. Experimentation was planned as per Taguchi’s L8 orthogonal array. In this paper, experiments have been conducted using welding current, arc voltage, welding speed, and electrode stick out as input process parameters for evaluating multiple responses namely weld bead width and bead hardness. The optimum values were analyzed by means of multi-objective Taguchi’s method for the determination of total normalized quality loss (TNQL) and multi-response signal-to-noise ratio (MRSN). The optimum parameters for smaller bead width and higher bead hardness are weld current at low level (12.186 A), arc voltage at low level (12.51 V), welding speed at low level (12.25 mm/min), and electrode stick out at low level (12.29 mm). Finally, confirmation experiment was carried out to check the accuracy of the optimized results.