Optimization of Welding Input Parameters Using PSO Technique for Minimizing HAZ Width in GMAW

Abstract

In order to conceive command systems for welding equipment based on intelligence techniques similar to human thinking; it is better to use artificial intelligence methods, for example: Genetic algorithms and particle swarm optimization. Freshly, this latter has received increased attention in many research fields. This paper discuss the application of particle swarm optimization algorithm to optimize the welding process parameters and obtain a better Width of Head Affected Zone (WHAZ) in the welding machine which is gas metal arc welding. The effect of four main welding variables in the gas metal arc welding process, namely welding speed, welding voltage, nozzle-to-plate distance and wire feed speed on the WHAZ are studied. A source code is developed in MATLAB 8.3 to perform the optimization.

Generating a Matlab Code with Parameter Optimization in Gearbox

“…It is possible to optimize production with software codes made in different versions of the Matlab commercial package program (Eremochkin and Dorokhov, 2021). In design applications where, multiple independent parameters are involved, such applications provide an advantage to the manufacturer (Mezaache et al, 2022).…”