Structural and Behaviour Optimization of Tubular Structures Made of Tailor Welded Blanks by Applying Taguchi and Genetic Algorithms Methods

Even though they initially appeared as a method of using waste from other production processes, tailored welded blanks (TWB) presented several advantages by combining materials with different characteristics. On the one hand, this study focuses on minimizing the adverse effects caused by the springback of TWB parts. The proposed method is based on the Taguchi technique using orthogonal type 23 networks. On the other hand, genetic algorithms were applied to obtain maximum performance parameters within the dynamic loadings of tubular structures made of TWB by advantageous positioning of the weld line. The obtained data were compared and evaluated through software platforms such as MATLAB, Design Expert, and Dynaform, and experimental validation. By generating an objective function, the construction of thin-walled tubular structures can be controlled for a predetermined deformation and maximum energy absorption. The data obtained has an error rate of less than 3%, thus considering that this method can be used successfully in the qualitative and quantitative estimation of dynamically loaded TWB tubular structures.