Genetic algorithm for optimisation of A-TIG welding process for modified 9Cr–1Mo steel

Abstract

It is essential to set up the activated tungsten inert gas (A-TIG) welding process parameters to produce the desired weld bead geometry and heat affected zone (HAZ) width in modified 9Cr–1Mo steel weld joints. Therefore, it becomes necessary to develop a tool for optimisation of A-TIG welding process. Genetic algorithm (GA) based model has been developed to determine the optimum process parameters. In this methodology, first independent ANN models correlating depth of penetration, weld bead width and HAZ width with current, voltage and torch speed respectively were developed. Then, GA code was developed in which the objective function was evaluated using the ANN models. There was good agreement between the target and actual values of bead geometry and HAZ width obtained using the GA optimised process parameters. Thus, a methodology using GA has been developed for optimising the A-TIG process parameters for modified 9Cr–1Mo steel.