Experimental Design of Bio-Inspired Algorithms for Optimization Problems in Industry 5.0

Metaheuristics-based Parametric Optimization of Semi-automatic MIG Welded Austenitic AISI 304 Stainless Steel for Industry 5.0

Author(s): Abhishek Ghosh and Sudip Mandal *

Pp: 87-102 (16)

DOI: 10.2174/9798898814083126010011

* (Excluding Mailing and Handling)

Abstract

Austenitic stainless steels are readily weldable, but sensitization and solidification cracks are common defects in the welding of such steels. It is found that the problem of solidification cracking remains under control if the weld pool solidifies in FA mode. 6-8% delta ferrite in the fusion zone can promote the FA mode of solidification. The effects of different semi-automatic MIG welding parameters, like welding current, gas flow rate, and welding speed, on solidification behavior and microstructure of the weldment are not clear. In this present work, an attempt has been made to optimize MIG welding input parameters to achieve 7% delta ferrite in the fusion zone. Initially, ANOVA-based analysis and optimization was performed. A new metaheuristic, namely the Elephant Swarm Water Search Algorithm (ESWSA), was used for optimization purposes to get the optimal condition of grinding.


Keywords: AISI304 austenitic stainless steel, ANOVA, ESWSA, Industry 5.0, Metaheuristics optimization, Semi-automatic MIG welding.