Exploring Recent Metaphor-Based Algorithms for Optimizing TIG Welding Parameters

Welding processes are characterized by multiple input parameters. Selecting the optimal combination of these parameters is a critical task to ensure high-quality welds and productivity. This study focuses on identifying the most suitable input parameter combination for Tungsten Inert Gas (TIG) welding of martensitic stainless steel AISI 420. The chosen input parameters include welding current, gas flow rate, and welding speed. The response parameters considered are the Ultimate Tensile Strength (UTS) and Ductility or Elongation (E) of the welded joint, determined through tensile testing. To optimize the welding process, we applied three recently proposed metaheuristic algorithms, collectively referred to as the Rao optimization algorithms. The primary objective of this optimization is to maximize the desired performance metrics of the welding process. Simulated results allowed us to identify a critical operating region for efficient TIG welding, focusing on achieving maximum UTS and Ductility. A thorough investigation was conducted to determine the most effective algorithms based on criteria such as maximum iteration, population size, and convergence speed.