Optimization of Process Parameters Affecting on Spring-Back in V-Bending Process for High Strength Low Alloy Steel HSLA 420 Using FEA (HyperForm) and Taguchi Technique

Authors: Navajyoti Panda, R. S. Pawar

Abstract:

In this study, process parameters like punch angle, die opening, grain direction, and pre-bend condition of the strip for deep draw of high strength low alloy steel HSLA 420 are investigated. The finite element method (FEM) in association with the Taguchi and the analysis of variance (ANOVA) techniques are carried out to investigate the degree of importance of process parameters in V-bending process for HSLA 420&ST12 grade material. From results, it is observed that punch angle had a major influence on the spring-back. Die opening also showed very significant role on spring back. On the other hand, it is revealed that grain direction had the least impact on spring back; however, if strip from flat sheet is taken, then it is less prone to spring back as compared to the strip from sheet metal coil. HyperForm software is used for FEM simulation and experiments are designed using Taguchi method. Percentage contribution of the parameters is obtained through the ANOVA techniques.

Keywords: Bending, V-bending, FEM, spring-back, Taguchi, HyperForm, profile projector, HSLA 420 & St12 materials.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1315671

References:

[1] H. K. Yi, D. W. Kim, C. J. Van Tyne, and Y. H. Moon, Analytical prediction of springback based on residual differential strain during sheet metal bending. Int. J. Mech. Sci., 2008, 117- 129.
[2] Thaweepat Buranathiti and Jian Cao, An effective analytical model for spring back predictionin straight flanging processes, Int. J. Materials and Product Technology,2004,137-153.
[3] Sutasn Thipprakmas, Finite element analysis of punch height effect on V-bending angle, Materials and Design 31 (2010) 1593– 1598.
[4] You-Min Huang and Daw-KweiLeu, effects of process variables on v-die bendingprocess of steel sheet, Int. J. Mech. Sci. Vol. 40, No. 7, 631 - 650, 1998.
[5] Ján SLOTA and Miroslav JURČIŠIN, Experimental and Numerical Prediction of Springback in V-Bending of Anisotropic sheet metals for automotive industry, Mechanika z. 84 (3/12) 2012, 55-68.
[6] Himanshu V. Gajjar, Anish H. Gandhi, and Harit K. Raval, Finite Element Analysis of Sheet Metal Airbending Using Hyperform LS-DYNA, World Academy of Science, Engineering and Technology 8 2007, 92-97.
[7] Wang J, Verma S, Alexander R, Gauc J. Spring-back control of sheet metal air bending process. J Manuf Process 2008;10:21– 7.
[8] W. M. Chan, H. I. Chew, H. P. Lee, B. T. Cheok, Finite element analysis of springback of V bending sheet metal forming processes, Journal of Materials Processing Technology 148 (2004) 15-24.
[9] KazunariImaia, Junichi Koyama, Yingjun Jin, High-accuracy V-bending system by realtime identifying material property, journal of materials processing technology 2 0 1 (2008) 193– 197.
[10] Leu DK, Hsieh CM. The influence of coining force on spring-back reduction in V-die bending process. J Mater Process Technol 2008; 196:230–5.
[11] Florica Mioara Groze Gheorghe Achimaş, Springback Prediction of the V Bending Process using Finite Element Simulation, 7th International Multidisciplinary Conference, Baia Mare, Romania, May 17-18, 2007, ISSN-1224-3264.
[12] Sutasn Thipprakmas, Wiriyakorn Phanitwong, Process parameter Design of springback and spring-go in V bending process using Taguchi technique, Materials and Design 32 (2011) 4430-4436.
[13] Peng Chen, Muammer Koc¸ Simulation of springback variation in forming of advanced high strength steels, Journal of Materials Processing Technology 190 (2007) 189–198.
[14] Vijay Gautam, Parveen Kumar, Aadityeshwar Singh Deo, Effect of Punch Profile Radius and Localised Compression on Springback in V-Bending of High Strength Steel and its FEA Simulation, International Journal Of Mechanical Engineering And Technology (Ijmet), Volume 3, Issue 3, (2012), 517-530.
[15] M. V. Inamdar, P. P. Date, U. B. Desai, Studies on the prediction of springback in air vee bending of metallic sheets using an arti®cial neural network, Journal of Materials Processing Technology 108 (2000) 45 –54.
[16] A. Gisario, M. Barletta, C. Conti, S. Guarino, Springback control in sheet metal bending by laser-assisted bending: Experimental analysis, empirical and neural network modeling, Optics and Lasersin Engineering49(2011)1372– 1383.
[17] Kazan R, Firat M, Tiryaki AE. Prediction of spring back in wipe-bending process of sheet metal using neural network. J Mater Des 2009;30:418–23.