A new method for automatic optimization of drawbead geometry in the sheet metal forming process based on an iterative learning control model.

In this paper, an iterative learning control (ILC) model is constructed with the state function, forming quality function, and learning updating law to optimize the sheet forming process. The state function, which is hardly calculated explicitly, is replaced by finite element simulation to predict the workpiece state with a specific drawbead geometry scheme. Then, the forming quality function is defined by accumulating the elements' thinning strain deviation with different weights. Afterwards, the learning updating law is designed to provide a new scheme of drawbead geometry based on the forming quality function multiplied by a learning gain. The ILC model guarantees a quick convergence and greatly improves the optimization efficiency for industrial application. To apply the ILC model to optimizing the drawbead geometry automatically, schemes of seamless integration of computer-aided engineering system into the CATIA platform and the drawbead geometry parameterization are adopted. Lastly, the rapidity and practicability of the optimization method for drawbead geometry are verified by the numerical experiment of the engine hood inner panel. [ABSTRACT FROM AUTHOR]