Forming defects prediction for sheet metal forming using Gaussian process regression

Forming defects like fracture and wrinkle are key factors to influence the forming quality of sheet metal. Accurate prediction of forming defects is essential for the sheet metal forming process. In this paper, an approximation model technique based on Gaussian process regression(GPR) is proposed to predict the forming defects in sheet metal forming process. Finite element analysis is applied to simulate the drawing process. Design variables include drawbead resistance coefficient and blank-holding force. Forming limit diagram is used to calculate the values of defects. A dash board drawing case demonstrates that the proposed approach is more accurate and effective than support vector machines method and conventional response surface method.