journal article·2019-05Open access

Two regression approaches for prediction of large radius air bending

Vitalii Vorkov, Richard Aerens, Dirk Vandepitte, Joost R. Duflou

Abstract

The industrial importance of air bending applications with high-strength steels has increased in recent years. However, the limited cold formability of high-strength steels requires the application of punches with large radii. The usage of large radii tooling leads to a change of the loading scheme from traditional 3-point to 4-point bending. Therefore, the conventional formulas used for the prediction of 3-point bending operations fail to deliver accurate results. In the current work, two regression approaches are proposed to achieve an accurate prediction of industrially important bending parameters. The first model is based on phenomenological observations and fitting of well-established formulas. The second model utilizes the circular approximation model as base for the regression prediction. Large radius bending is used mostly for high-strength steels. Therefore, Strenx 700 MC and Strenx 1300 with thicknesses of 4 and 6 mm were used for the investigation. The following bending characteristics have been studied: position of contact points, bend allowance, bending force and springback. The predicted values are compared with the experimental results to assess the prediction accuracy of the proposed methods. Neither the phenomenological, nor the circular model delivers superior overall prediction quality for all output parameters, thus a combination of the two regression models is an attractive option for a better prediction of large radius air bending.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Metal Forming Simulation Techniques · Structural Load-Bearing Analysis · Laser and Thermal Forming Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (22)

Show source-provided references
1. Narayanasamy R, Padmanabhan P (2009) Modeling of springback on air bending process of interstitial free steel sheet using multiple regression analysis. Int J Interact Des Manuf 3(1):25–3310.1007/s12008-009-0059-7 ↗
2. Narayanasamy R, Padmanabhan P (2012) Comparison of regression and artificial neural network model for the prediction of springback during air bending process of interstitial free steel sheet. J Intell Manuf 23(3):357–36410.1007/s10845-009-0375-6 ↗
3. Li GY, Tan MJ, Liew KM (1999) Springback analysis for sheet forming processes by explicit finite element method in conjunction with the orthogonal regression analysis. Int J Solids Struct 36(30):4653–466810.1016/S0020-7683(98)00227-3 ↗
4. Yoshida M, Yoshida F, Konishi H, Fukumoto K (2005) Fracture limits of sheet metals under stretch bending. Int J Mech Sci 47(12):1885–189610.1016/j.ijmecsci.2005.07.006 ↗
5. Teimouri R, Baseri H, Rahmani B, Bakhshi-Jooybari M (2014) Modeling and optimization of spring-back in bending process using multiple regression analysis and neural computation. Int J Mater Form 7(2):167–17810.1007/s12289-012-1117-4 ↗
6. Bashah NAK, Muhamad N, Deros BM, Zakaria A, Ashari S, Mobin A, Lazat MSMA (2013) Multi-regression modeling for springback effect on automotive body in white stamped parts. Mater Des 46:175–19010.1016/j.matdes.2012.10.006 ↗
7. Zhan M, Yang H, Huang L, Gu R (2006) Springback analysis of numerical control bending of thin-walled tube using numerical-analytic method. J Mater Process Technol 177(1):197–20110.1016/j.jmatprotec.2006.03.183 ↗
8. Vorkov V, Aerens R, Vandepitte D, Duflou JR (2017) Accurate prediction of large radius air bending using regression. Procedia Eng 207:1623–162810.1016/j.proeng.2017.10.1089 ↗
9. Kurtaran H (2008) A novel approach for the prediction of bend allowance in air bending and comparison with other methods. Int J Adv Manuf Technol 37(5–6):486–49510.1007/s00170-007-0987-y ↗
10. Kim H, Nargundkar N, Altan T (2007) Prediction of bend allowance and springback in air bending. J Manuf Sci E-T ASME 129(2):342–35110.1115/1.2673527 ↗
11. Yang X, Choi C, Sever NK, Altan T (2016) 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 105:266–27210.1016/j.ijmecsci.2015.11.028 ↗
12. De Vin LJ (2000) Curvature prediction in air bending of metal sheet. J Mater Process Technol 100(1):257–26110.1016/S0924-0136(99)00489-6 ↗
13. Strano M, Iorio L, Semeraro Q, Sofia R (2017) Fusion metamodeling of the bend deduction in air bending. AIP Conference Proceedings 1896:10000310.1063/1.5008121 ↗
14. Vorkov V, Aerens R, Vandepitte D, Duflou JR (2015) On the identification of a loading scheme in large radius air bending. Key Eng Mater 639:155–16210.4028/www.scientific.net/KEM.639.155 ↗
15. Vorkov V, Aerens R, Vandepitte D, Duflou JR (2014) The multi-breakage phenomenon in air bending process. Key Eng Mater 611:1047–105310.4028/www.scientific.net/KEM.611-612.1047 ↗
16. Vorkov V, Aerens R, Vandepitte D, Duflou JR (2017) Experimental investigation of large radius air bending. Int J Adv Manuf Technol 92(9):3553–356910.1007/s00170-017-0346-6 ↗
17. Vorkov V (2017) Complete experimental data for large radius bending. https://doi.org/10.7910/DVN/P7XKVV , The Dataverse project10.7910/DVN/P7XKVV ↗
18. Vorkov V (2017) Variability data for large radius bending. https://doi.org/10.7910/DVN/WJGDUR , The Dataverse project10.7910/DVN/WJGDUR ↗
19. Chatti S, Fathallah R (2012) A study of the variations in elastic modulus and its effect on springback prediction. Int J Mater Form:1–11
20. Aerens R, Masselis S (2000) Air bending. Scientific and Technical Research Center of the Metal Fabrication Industry (CRIF/WTCM/SIRRIS) MC 110, Leuven, Belgium
21. Lange K (1985) Handbook of metal forming. McGraw-Hill Book Company, New York
22. Vorkov V (2017) Regression data for large radius bending. https://doi.org/10.7910/DVN/V7IB2Y , The Dataverse project10.7910/DVN/V7IB2Y ↗