Abstract

Springback occurs at the end of sheet metal forming process where the geometric changes takes place in the part when the load is removed. It is an important factor to determine the quality of sheet metal forming. In this paper, the factors which affects the springback is determined and its influence over springback is studied analytically. The sheet metal forming process is performed using finite-element tool ABAQUS, so as to obtain the springback value for different process parameter. Punch radius and clearance gap along the horizontal axis between punch and die are the two process parameters considered for this study. For this study, 2D metal forming process has been performed and the springback angle is calculated at the corner area close to the holder. Kriging interpolation technique is used to build the surrogate model for the optimization process. Finite element method provides the data to build the metamodel which also helps in reducing the number of the real tests. Kriging or Gaussian process regression is an interpolation method which interpolates the values, modeled by a Gaussian process governed by prior covariance to optimize the smoothness of the fitted values. Kriging was applied to simulate the complex springback process. The sample data required to build the surrogate model was generated using MATLAB. Latin hypercube sampling technique has been utilized to generate the input sample points. The meta- model built with help of kriging interpolation for the sheet metal forming process is validated using RMSE method. With help of this approach we are able to predict the best process parameter which results in lower springback for the sheet metal forming is obtained, thereby reducing the spring back considerably. This paper gives a new approach that involves in reducing the springback phenomenon in sheet metal forming process with help of meta-model technique.