Prediction of Springback in the Air Bending Process Using a Kriging Metamodel

F A Khadra,A W El-Morsy

doi:10.48084/etasr.925

Abstract

This paper addresses the use of the kriging‏ approach to predict the springback in the air bending process. The materials and the geometrical parameters, which significantly affect the springback, were considered as inputs, and the springback angle was considered as the response. A verified nonlinear finite element model was used to generate the training data required to create the kriging‏ metamodel. The training examples were selected based on computer-generated D-optimal designs. A comparison between the kriging approaches and the response surface methodology is conducted and discussed. The results showed that kriging accurately predicts the finite element springback results. Comparing the accuracy of kriging with a response surface methodology shows that kriging with a 2nd degree polynomial and exponential correlation function predicts the springback more accurately than the response surface methodology.

Highlights

Springback is a common phenomenon that occurs in sheet metal bending after unloading the static loads due to elastic recovery
A number of analytical models based on the geometry and the material characteristics have been conducted using the analytical methods for springback predictions
The model with examples selected based on the FQ model reached a significant level (0.0012 in the case of P2EXP), which is more reliable than the model based on the LI model b(0e.t0te2r6fiitnwthheencacsoemopfaPre2dEXtPo).thTehLerIemfoored,elt,haenFdQthme oRd2evlaslhuoews fsoar the full quadratic models are satisfactory

Summary

Introduction

Springback is a common phenomenon that occurs in sheet metal bending after unloading the static loads due to elastic recovery. Numerous investigations have been conducted on the springback phenomenon in sheet metal bending processes via experimental [1,2,3,4,5], analytical [6,7,8,9], and numerical [10,11,12] methods for different shapes, processes and material parameters. A number of analytical models based on the geometry and the material characteristics have been conducted using the analytical methods for springback predictions. Most of the analytical models assume a simplified process and material properties due to the complexity of the problem

Methods

Findings

Discussion

Conclusion