Abstract—The springback amount in the air bending process is influenced by a number of material’s geometrical parameters. To predict the springback a multidimensional function should be approximated. In this paper a response surface metamodel is utilized for this purpose. A verified nonlinear Finite Element (FE) algorithm is developed to generate the training data. Then, the generated training data will be used to train RSM. The FE algorithm is developed based on the updated Lagrangian formulation. To select the training data for the RSM, computer generated D-optimal designs are utilized.
Index Terms—Metamodels, springback, response surface, D-optimal designs.
Jaber E. Abu Qudeiri, Usama Umer, and Hussein M. A. Hussein are with the Advanced Manufacturing Institute, King Saud University, Riyadh, Saudi Arabia (e-mail: jqudeiri@ksu.edu.sa, uumer@ksu.edu.sa, hhussein@ksu.edu.sa).
Fayez Y. Abu Khadra is with the Mechanical Engineering Dept., King Abdulaziz University, Rabigh, Saudi Arabia (e-mail: f_Khadra@yahoo.com).
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Cite: Jaber E. Abu Qudeiri, Fayez Y. Abu Khadra, Usama Umer, and Hussein M. A. Hussein, "Response Surface Metamodel to Predict Springback in Sheet Metal Air Bending Process," International Journal of Materials, Mechanics and Manufacturing vol. 3, no. 4, pp. 266-269, 2015.