Abstract Scope |
Dissimilar welding process finds niche application in automobile, aerospace, marine industries. It superseded the traditional welding technique and eases the complexity in the state of the art. Interestingly, dissimilar welding process is cost effective comparative to its cousins techniques such laser welding, electron beam welding, etc. and is a blessing for the industries having welding associated to mild steel and stainless steel 304 (SS304). We investigated and analyzed the optimum conditions for Taguchi based optimization and grey relational analysis of the welding parameter. An Automated Gas Metal Arc Welding (GMAW) technique was implemented to study the dissimilar metal welding of Low carbon steel to SS 304 using ER70S-6/AWS A5.18 filler wire. A customized state of the art table CNC machine was used to automate the welding process. The Finite Element Analysis software such as ANSYS and MSC SIMUFACT WELDING are used to design, simulate and analyze the distortion pattern as well as thermal distribution along the welded joints. The obtained simulated results were corroborated with the experimental results. Moreover, the optimized parameters for the validation of distortion pattern were found to be within error tolerance limit of 10%. The present study will be filler in the dent created during dis-similar metal welding processes and opens up the scope for upcoming research based on the Taguchi optimization and reduction of the distortion pattern. Our results exemplify the role of the filler metal consumption, and improved efficiency of weldment for tensile strength. |