Multi-objective optimization of loading path design in multi-stage tube forming using MOGA

• Published in: International journal of material forming 2013-03, Vol.6 (1), p.125-135
• Main Authors: An, Honggang, Green, Daniel, Johrendt, Jennifer, Smith, Lorenzo
• Format: Article
• Language: English
• Subjects: CAE) and Design; Computational Intelligence; Computer-Aided Engineering (CAD; Engineering; Machines; Manufacturing; Materials Science; Mechanical Engineering; Original Research; Processes
• ISSN: 1960-6206; 1960-6214
• DOI: 10.1007/s12289-011-1079-y

Pre-bending is a critical process required prior to hydroforming. The bending has an effect on the tube thickness and strain which will use up a portion of the formability of the as-received tube. To compensate for this loss of formability, a multi-objective optimization method was applied to improve the hydroforming process after pre-bending. A multi-objective genetic algorithm (MOGA) and Kriging surrogate model were used to optimize the loading path. The Kriging model was used to replace the finite element simulation in constraint handling. The optimal loading parameters in the hydroforming process were obtained for a tube that was previously bent 90°, and showed an improvement in reducing the corner radii of the part at the extrados and intrados of the bend (8.73 mm and 11.24 mm for the extrados and intrados of the bend, respectively). The corresponding corner fill expansion (CFE) was improved by 16.7% (or 1.79 mm) compared to the maximum expansion of 10.73 mm obtained experimentally.