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Structural Engineering and Mechanics
  Volume 65, Number 4, February25 2018 , pages 447-452

Optimization of spring back in U-die bending process of sheet metal using ANN and ICA
Mojtaba Sheikhi Azqandi, Navid Nooredin and Ali Ghoddosian

    The controlling and prediction of spring back is one of the most important factors in sheet metal forming processes which require high dimensional precision. The relationship between effective parameters and spring back phenomenon is highly nonlinear and complicated. Moreover, the objective function is implicit with regard to the design variables. In this paper, first the influence of some effective factors on spring back in U-die bending process was studied through some experiments and then regarding the robustness of artificial neural network (ANN) approach in predicting objectives in mentioned kind of problems, ANN was used to estimate a prediction model of spring back. Eventually, the spring back angle was optimized using the Imperialist Competitive Algorithm (ICA). The results showed that the employment of ANN provides us with less complicated and time-consuming analytical calculations as well as good results with reasonable accuracy.
Key Words
    U-die bending process; spring back angle; artificial neural network; imperialist competitive algorithm
Mojtaba Sheikhi Azqandi: Department of Mechanical Engineering, Bozorgmehr University of Qaenat, Qaen, Iran
Navid Nooredin: Khorasan Steel Complex Co., Neishabour, Iran
Ali Ghoddosian: Faculty of Mechanical Engineering, Semnan University, Semnan, Iran

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