Multiple objective optimisation of submerged arc weld process parameters using grey-based Taguchi method

Welding is the most common manufacturing process. The quality of weld is a very important working aspect for the manufacturing and construction industries. Because of high quality and reliability, submerged arc welding (SAW) is one of the chief metal joining processes employed in industry. Quality of weld mainly depends on the mechanical properties of the weld, which in turn relays on the interaction of the weld parameters. This paper discusses the multi-response optimisation of weld parameters using grey-based Taguchi method. Experiments are conducted using Taguchi's L9 orthogonal array. The weld parameters are welding current, welding speed and arc voltage with bead hardness and material deposition rate as responses. Taguchi's signal-to-noise (S/N) ratio is computed based on their performance characteristics. Grey relation grade is obtained using S/N ratio values of responses. Based on grey relational grade, optimum levels of parameters have been identified. The significant contributions are estimated using analysis of variance. Confirmation test is conducted to validate the proposed method. This evaluation procedure can be used in decision-making to select process parameters for a welding operator. The proposed and developed method has good accuracy and competency enhancing automation and robotisation.