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Finite Element Analysis of Springback Process in Sheet Metal Forming

M.R. Jamli


Springback prediction is essential to ensure the economics of sheet metal forming operations. To achieve accurate results, current nonlinear recovery applications in finite element (FE) analysis have become more complicated and therefore require complex computational programming work to develop a constitutive model. At the end of a plastic deformation and after the load is released from the sheet metal, the change of stress in the elastic area becomes nonlinear. The change of elastic modulus is influenced by the amount of plastic strain, yield locus size, and stress normalization point. The effects of nonlinear recovery on the residual stress distribution and the sheet metal final shape after springback were investigated. The analysis results show that the formed hysteresis loops due to the unloading and reloading process were able to be simulated successfully by the proposed method. It was found that the distribution of non-zero residual stresses at the end of springback process was highly related to the nonlinear recovery curve.

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T. Meinders, I. A. Burchitz, M. H. A. Bonte, and R. A. Lingbeek, “Numerical product design: Springback prediction, compensation and optimization,” Int. J. Mach. Tools Manuf., Vol. 48, No. 5, pp. 499–514, 2008.

H. Dai, H. Jiang, T. Dai, W. Xu, and A. Luo, “Investigation on the influence of damage to springback of U-shape HSLA steel plates,” Vol. 708, 2017.

S. Sumikawa, A. Ishiwatari, and J. Hiramoto, “Journal of Materials Processing Technology Improvement of springback prediction accuracy by considering nonlinear elastoplastic behavior after stress reversal,” Vol. 241, pp. 46 53, 2017.

J. Lee and M. Lee, “Piecewise linear approximation of nonlinear

unloading-reloading behaviors using a multi-surface approach d e,” Vol. 93, pp. 112–136, 2017.

X. Yang, C. Choi, N. K. Sever, and T. Altan, “International Journal of Mechanical Sciences Prediction of springback in air-bending of Advanced High Strength steel ( DP780 ) considering Young ’ s modulus variation and with a piecewise hardening function,” Int. J. Mech. Sci., Vol. 105, pp. 266–272, 2016.

J. Lee, J.-Y. Lee, F. Barlat, R. H. Wagoner, K. Chung, and M.-G. Lee, “Extension of quasi-plastic–elastic approach to incorporate complex

plastic flow behavior – application to springback of advanced high strength steels,” Int. J. Plast., Vol. 45, pp. 140–159, Jun. 2013.

A. Govik, R. Rentmeester, and L. Nilsson, “A study of the unloading behaviour of dual phase steel,” Mater. Sci. Eng. A, Vol. 602, pp. 119–126, Apr. 2014.

J. Choi, J. Lee, G. Bae, F. Barlat, and M. Lee, “Evaluation of Springback for DP980 S Rail Using Anisotropic Hardening Models,” Vol. 68, No. 7, pp. 1850–1857, 2016.

Y. X. Zhu, Y. L. Liu, H. Yang, and H. P. Li, “Development and application of the material constitutive model in springback prediction of coldbending,” Mater. & Des., Vol. 42, No. 0, pp. 245–258, 2012.

M. R. Jamli, A. K. Ariffin, and D. A. Wahab, “Neural Network Prediction of Nonlinear Elastic Unloading for High Strength Steel,” Proc. APCOM & ISCM, Singapore, pp. 1–6, 2013.

L. Sun and R. H. Wagoner, “Complex unloading behavior: Nature of the deformation and its consistent constitutive representation,” Int. J. Plast., Vol. 27, No. 7, pp. 1126–1144, 2011.

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