LAUSR

Aluminum is widely used in fields that require lightweight technology, such as in the aerospace and automobile industries. The welding of aluminum alloys, however, tends to generate large deformations in the welded structures due to its large heat conductivity and thermal expansion. Therefore, this study aims to reduce welding deformations that occur in the welding process by obtaining an optimal welding sequence. The welding sequence optimization process consists of two main stages. The first involves the prediction of the welding deformation behavior by using thermo-elastic-plastic finite element analysis. The second stage optimizes the welding sequence by using a genetic algorithm (GA), which can efficiently optimize very large solution spaces considering not only the welding sequence, but also the welding direction. In addition, this study proposed an appropriate and efficient GA for the present optimization problem. The optimization results showed that the developed finite element analysis model were in good agreement with the experimental results, and the proposed optimization tool can reduce the welding deformation considerably.