Optimization of GMA welding process using the dual response approach

Disturbances and changes in the welding working environment lead to possible variations in the output variables associated with weld quality. In order to enhance weld quality, it is essential to optimize the welding process by taking the variance as well as the average value of the output variables into consideration. In this study, the dual response approach is adopted to determine the welding process parameters, which produce the target value with minimal variance. The dual response approach optimizes the penetration in gas metal arc (GMA) welding through the procedures as follows. First, the regression models of the mean value and standard deviation of the penetration are induced through regression analysis. Subsequently, an optimization algorithm based on the regression models and constraints is applied to determine the welding process parameters, which generate the desired penetration with minimized variance. In particular, the genetic algorithm, a global optimization algorithm, is adopted in this study to determine the optimal solution.

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