Tailoring weld geometry during keyhole mode laser welding using a genetic algorithm and a heat transfer model

Abstract

Tailoring of weld attributes based on scientific principles remains an important goal in welding research. The current generation of unidirectional laser keyhole models cannot determine sets of welding variables that can lead to a particular weld attribute such as specific weld geometry. Here we show how a computational heat transfer model of keyhole mode laser welding can be restructured for systematic tailoring of weld attributes based on scientific principles. Furthermore, the model presented here can calculate multiple sets of laser welding variables, i.e. laser power, welding speed and beam defocus, with each set leading to the same weld pool geometry. Many sets of welding variables were obtained via a global search using a real number-based genetic algorithm, which was combined with a numerical heat transfer model of keyhole laser welding. The reliability of the numerical heat transfer calculations was significantly improved by optimizing values of the uncertain input parameters from a limited volume of experimental data. The computational procedure was applied to the keyhole mode laser welding of the 5182 Al–Mg alloy to calculate various sets of welding variables to achieve a specified weld geometry. The calculated welding parameter sets showed wide variations of the values of welding parameters, but each set resulted in a similar fusion zone geometry. The effectiveness of the computational procedure was examined by comparing the computed weld geometry for each set of welding parameters with the corresponding experimental geometry. The results provide hope that systematic tailoring of weld attributes via multiple pathways, each representing alternative welding parameter sets, is attainable based on scientific principles.