Enhancing accuracy in simulation of sheet metal forming by modelling elasticity of tools
Source abstract
Abstract
Abstract The first ESAFORM Benchmark was dedicated to the cylindrical cup drawing test and involved the participation of 11 laboratories worldwide. Despite the wide variety of computational models adopted, several experimental results were not accurately predicted, and no conclusive explanation for the observed discrepancies was identified, motivating further investigation. Using the same benchmark configuration, the present study examines the influence of modelling tools as rigid or elastic on the accuracy of sheet metal forming simulations. The effect of the elasticity of tools is quantified and related to discrepancies previously reported in the benchmark. Different process conditions, including variations in blank thickness and diameter were analysed for two materials: AA6016 aluminium alloy and DC06 steel. The results demonstrate that considering the elasticity of tools significantly improves the prediction of punch force evolution, cup wall thickness, and earing profile, particularly in processes involving ironing. Elastic deflection of the tools modifies the contact pressure distribution under the blank-holder and increases the effective punch–die gap, leading to more accurate predictions of ironing forces and wall thickness. These findings help explain discrepancies observed in the first ESAFORM Benchmark and highlight that incorporating the elasticity of tools is essential for high-fidelity sheet metal forming simulations, particularly when ironing occurs.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Metal Forming Simulation Techniques · Laser and Thermal Forming Techniques · Metallurgy and Material Forming
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (56)
Show source-provided references
1. Zhang W, Xu J (2022) Advanced lightweight materials for automobiles: a review. Mater Des 221:110994. https://doi.org/10.1016/J.MATDES.2022.11099410.1016/J.MATDES.2022.110994 ↗
2. Candela A, Sandrini G, Gadola M, Chindamo D, Magri P (2024) Lightweighting in the automotive industry as a measure for energy efficiency: review of the main materials and methods. Heliyon 10:e29728. https://doi.org/10.1016/J.HELIYON.2024.E2972810.1016/J.HELIYON.2024.E29728 ↗
3. Göltl F, Birkert A, Harst F, Stache NC (2024) Methodic Approach for the Simulation-Based, Elastic Die Surface Compensation by Creating a FE-model of the Car Body Press Predicated on Spotting Images via Neural Networks. IOP Conf Ser Mater Sci Eng 1307:012039. https://doi.org/10.1088/1757-899X/1307/1/01203910.1088/1757-899X/1307/1/012039 ↗
4. Hayashi H (2007) Elastic deformation of tools in stamping of large-scale autobody panels. Proc. IDDRG Conference. 2007
5. Tehel R, Päßler T, Bergmann M (2020) Effective FE models for simulating the elasto-mechanical characteristics of forming machines. Int J Adv Manuf Technol 106:3505–3514. https://doi.org/10.1007/S00170-019-04832-6/FIGURES/1210.1007/S00170-019-04832-6/FIGURES/12 ↗
6. Del Pozo D, López De Lacalle LN, López JM, Hernández A (2008) Prediction of press/die deformation for an accurate manufacturing of drawing dies. Int J Adv Manuf Technol 37:649–56. https://doi.org/10.1007/S00170-007-1012-110.1007/S00170-007-1012-1 ↗
7. Doege E, Elend L-E (2001) Design and application of pliable blank holder systems for the optimization of process conditions in sheet metal forming. J Mater Process Technol 111:182–187. https://doi.org/10.1016/S0924-0136(01)00506-410.1016/S0924-0136(01)00506-4 ↗
8. Zaragoza VG, Rane K, Strano M, Monno M (2021) Manufacturing and performance of 3D printed plastic tools for air bending applications. J Manuf Process 66:460–469. https://doi.org/10.1016/J.JMAPRO.2021.04.04510.1016/J.JMAPRO.2021.04.045 ↗
9. Kaleem MA, Steinheimer R, Frohn-Sörensen P, Gabsa S, Engel B (2024) Additive manufacturing of polymeric pressure die for rotary draw bending process. Int J Adv Manuf Technol 134:1789–804. https://doi.org/10.1007/S00170-024-14221-310.1007/S00170-024-14221-3 ↗
10. Athale M, Park T, Hahnlen R, Pourboghrat F (2023) Design, performance, and cost savings of using GF-PC additively manufactured tooling for stamping of HSS 590 sheet metal. J Manuf Process 101:1–14. https://doi.org/10.1016/J.JMAPRO.2023.05.07210.1016/J.JMAPRO.2023.05.072 ↗
11. Geueke M, Frohn-Sörensen P, Reuter J, Padavu N, Reinicke T, Engel B (2021) Structural optimization of additively manufactured polymer tools for flexible sheet metal forming. Procedia CIRP 104:1345–1350. https://doi.org/10.1016/j.procir.2021.11.22610.1016/j.procir.2021.11.226 ↗
12. Giorleo L, Ceretti E (2022) Deep drawing punches produced using fused filament fabrication technology: performance evaluation. J Manuf Process 84:1–9. https://doi.org/10.1016/J.JMAPRO.2022.09.05410.1016/J.JMAPRO.2022.09.054 ↗
13. Fromentin S, Martiny M, Ferron G, Tourki Z, Moreira LP, Ferran G (2001) Finite element simulations of sheet-metal forming processes for planar-anisotropic materials. Int J Mech Sci 43:1833–1852. https://doi.org/10.1016/S0020-7403(01)00011-X10.1016/S0020-7403(01)00011-X ↗
14. Pilthammar J, Sigvant M, Islam MS, Schill M, Sjöblom S, Sjöblom V et al (2023) Three Industrial Cases of Sheet Metal Forming Simulations with Elastic Dies. IOP Conf Ser Mater Sci Eng 1284:012055. https://doi.org/10.1088/1757-899X/1284/1/01205510.1088/1757-899X/1284/1/012055 ↗
15. Großmann K, Wiemer H, Hardtmann A, Penter L (2008) The advanced forming process model including the elastic effects of the forming press and tool. Arch Civil Mech Eng 8:41–54. https://doi.org/10.1016/S1644-9665(12)60162-910.1016/S1644-9665(12)60162-9 ↗
16. Choi KY, Lee MG, Kim HY (2013) Sheet metal forming simulation considering die deformation. Int J Automot Technol 14:935–40. https://doi.org/10.1007/S12239-013-0103-210.1007/S12239-013-0103-2 ↗
17. Keum YT, Ahn IH, Lee IK, Song MH, Kwon SO, Park JS (2005) Simulation of Stamping Process of Automotive Panel Considering Die Deformation. AIP Conf Proc, 778:90–5. https://doi.org/10.1063/1.201119910.1063/1.2011199 ↗
18. Neto DM, Coër J, Oliveira MC, Alves JL, Manach PY, Menezes LF (2016) Numerical analysis on the elastic deformation of the tools in sheet metal forming processes. Int J Solids Struct 100:270–285. https://doi.org/10.1016/j.ijsolstr.2016.08.02310.1016/j.ijsolstr.2016.08.023 ↗
19. Pilthammar J, Sigvant M, Islam MS, Schill M, Sjöblom S, Sjöblom V et al (2023) An overview of Methods for Simulating Sheet Metal Forming with Elastic Dies. IOP Conf Ser Mater Sci Eng 1284:012054. https://doi.org/10.1088/1757-899X/1284/1/01205410.1088/1757-899X/1284/1/012054 ↗
20. Pilthammar J, Sigvant M, Kao-Walter S (2018) Introduction of elastic die deformations in sheet metal forming simulations. Int J Solids Struct 151:76–90. https://doi.org/10.1016/J.IJSOLSTR.2017.05.00910.1016/J.IJSOLSTR.2017.05.009 ↗
21. Song YJ, Oh IS, Hwang SH, Choi H, Lee MG, Kim HJ (2021) Numerically efficient sheet metal forming simulations in consideration of tool deformation. Int J Automot Technol 22:69–79. https://doi.org/10.1007/S12239-021-0008-4/METRICS10.1007/S12239-021-0008-4/METRICS ↗
22. Haufe A, Roll K, Bogon P (2008) Sheet metal forming simulation with elastic tools in LS-DYNA. Proceedings of the 7th International Conference, NUMISHEET
23. Habraken AM, Aksen TA, Alves JL, Amaral RL, Betaieb E, Chandola N et al (2022) Analysis of ESAFORM 2021 cup drawing benchmark of an Al alloy, critical factors for accuracy and efficiency of FE simulations. IntJ Mater Form 15:1–96. https://doi.org/10.1007/S12289-022-01672-W/FIGURES/610.1007/S12289-022-01672-W/FIGURES/6 ↗
24. Oliveira MC, Cazacu O, Revil-Baudard B, Neto DM, Frohn-Sörensen P, Ma J (2023) Esaform 2021 cup drawing benchmark of an Al alloy: critical follow up analysis of its potentials. Mater Res Proc 28:1491–502. https://doi.org/10.21741/9781644902479-16110.21741/9781644902479-161 ↗
25. TC I (2009) Metallic Materials–Tensile Testing–Part 1: Method of Test at Room Temperature
26. Duarte JF, Santos A, Barata da Rocha A (1994) Development of testing equipment for sheet metal forming analysis. IDDRG’94-International Deep Drawing Research Group 18th Biennial Congress, pp. 259–72
27. de Sousa JPM (2019) Desenvolvimento de um Sistema de Controlo e Aquisição de Dados para Máquina Universal de Ensaios de Chapas Metálicas. Master thesis. University of Porto
28. Lin X, Wang J, Zhou Y, Lin C (2018) A Rapid 3D Vision Inspection System for Sheet Metal Parts Based on Feature Extraction and Partial Point Clouds. IOP Conf Ser Mater Sci Eng 452:022137. https://doi.org/10.1088/1757-899X/452/2/02213710.1088/1757-899X/452/2/022137 ↗
29. Rieke-Zapp D, Royo S (2017) Structured light 3D scanning. Digit Techniques Documenting Preserving Cult Herit pp. 247–25110.5040/9781641899444.019 ↗
30. Zeiss I (2023)
31. Menezes LF, Teodosiu C (2000) Three-dimensional numerical simulation of the deep-drawing process using solid finite elements. J Mater Process Technol 97:100–106. https://doi.org/10.1016/S0924-0136(99)00345-310.1016/S0924-0136(99)00345-3 ↗
32. Oliveira MC, Alves JL, Chaparro B, Menezes LF (2007) Study on the influence of work-hardening modeling in springback prediction. Int J Plast 23:516–43. https://doi.org/10.1016/j.ijplas.2006.07.00310.1016/j.ijplas.2006.07.003 ↗
33. Chen Z, Bong HJ, Li D, Wagoner RH (2016) The elastic–plastic transition of metals. Int J Plast 83:178–201. https://doi.org/10.1016/j.ijplas.2016.04.00910.1016/j.ijplas.2016.04.009 ↗
34. Sumikawa S, Ishiwatari A, Hiramoto J, Urabe T (2016) Improvement of springback prediction accuracy using material model considering elastoplastic anisotropy and Bauschinger effect. J Mater Process Technol 230:1–7. https://doi.org/10.1016/j.jmatprotec.2015.11.00410.1016/j.jmatprotec.2015.11.004 ↗
35. Zhang C, Zhang S, Lou Y (2022) Characterization of kinematic and distortional hardening by cyclic twin-bridge shear tests for sheet metal with inverse engineering approach. Mech Mater 172:104387. https://doi.org/10.1016/J.MECHMAT.2022.10438710.1016/J.MECHMAT.2022.104387 ↗
36. Voce E (1948) The relationship between stress and strain for homogeneous deformations. J Inst Metals 74:537–562
37. Swift HW (1952) Plastic instability under plane stress. J Mech Phys Solids 1:1–18. https://doi.org/10.1016/0022-5096(52)90002-110.1016/0022-5096(52)90002-1 ↗
38. Hill R (1948) A theory of the yielding and plastic flow of anisotropic metals. Proc Royal Soc A: Math Phys Eng Sci 193:281–297. https://doi.org/10.1098/rspa.1948.004510.1098/rspa.1948.0045 ↗
39. Kim S, Lee J, Barlat F, Lee M-G (2013) Formability prediction of advanced high strength steels using constitutive models characterized by uniaxial and biaxial experiments. J Mater Process Technol 213:1929–1942. https://doi.org/10.1016/j.jmatprotec.2013.05.01510.1016/j.jmatprotec.2013.05.015 ↗
40. Mu Z, Liu J, Wang W, Dai X, Ma S, Hou Y (2024) Characterization and modeling of biaxial plastic anisotropy in metallic sheets. Int J Mech Sci 282:109640. https://doi.org/10.1016/J.IJMECSCI.2024.10964010.1016/J.IJMECSCI.2024.109640 ↗
41. Barlat F, Maeda Y, Chung K, Yanagawa M, Brem JC, Hayashida Y et al (1997) Yield function development for aluminum alloy sheets. J Mech Phys Solids 45:1727–63. https://doi.org/10.1016/S0022-5096(97)00034-310.1016/S0022-5096(97)00034-3 ↗
42. Hughes TJR (1980) Generalization of selective integration procedures to anisotropic and nonlinear media. Int J Numer Methods Eng 15:1413–1418. https://doi.org/10.1002/nme.162015091410.1002/nme.1620150914 ↗
43. Coër J, Laurent H, Oliveira MC, Manach PY, Menezes LF (2018) Detailed experimental and numerical analysis of a cylindrical cup deep drawing: pros and cons of using solid-shell elements. Int J Mater Form 11:357–73. https://doi.org/10.1007/S12289-017-1357-4/FIGURES/2110.1007/S12289-017-1357-4/FIGURES/21 ↗
44. Tisza M (2004) Numerical modelling and simulation in sheet metal forming. J Mater Process Technol 151:58–62. https://doi.org/10.1016/J.JMATPROTEC.2004.04.00910.1016/J.JMATPROTEC.2004.04.009 ↗
45. Neto DM, Oliveira MC, Menezes LF, Alves JL (2014) Applying Nagata patches to smooth discretized surfaces used in 3D frictional contact problems. Comput Methods Appl Mech Eng 271:296–320. https://doi.org/10.1016/j.cma.2013.12.00810.1016/j.cma.2013.12.008 ↗
46. Lee K, Park J, Lee J, Kwon SW, Choi I, Lee MG (2023) An enhanced boundary lubrication friction model for sheet metal forming. Int J Mech Sci 260:108652. https://doi.org/10.1016/J.IJMECSCI.2023.10865210.1016/J.IJMECSCI.2023.108652 ↗
47. Trzepieciński T, Szwajka K, Szewczyk M (2023) An Investigation into the Friction of Cold-Rolled Low-Carbon DC06 Steel Sheets in Sheet Metal Forming Using Radial Basis Function Neural Networks. Appl Sci 13:9572. https://doi.org/10.3390/APP1317957210.3390/APP13179572 ↗
48. Sedighiani K, Diehl M, Traka K, Roters F, Sietsma J, Raabe D (2020) An efficient and robust approach to determine material parameters of crystal plasticity constitutive laws from macro-scale stress–strain curves. Int J Plast 134:102779. https://doi.org/10.1016/J.IJPLAS.2020.10277910.1016/J.IJPLAS.2020.102779 ↗
49. Mamros EM, Mayer SM, Banerjee DK, Iadicola MA, Kinsey BL, Ha J (2022) Plastic anisotropy evolution of SS316L and modeling for novel cruciform specimen. Int J Mech Sci 234:107663. https://doi.org/10.1016/J.IJMECSCI.2022.10766310.1016/J.IJMECSCI.2022.107663 ↗
50. Du K, Huang S, Hou Y, Wang H, Wang Y, Zheng W et al (2023) Characterization of the asymmetric evolving yield and flow of 6016-T4 aluminum alloy and DP490 steel. J Mater Sci Technol 133:209–29. https://doi.org/10.1016/J.JMST.2022.05.04010.1016/J.JMST.2022.05.040 ↗
51. Lenzen M, Merklein M (2024) Analysis of the evolution of the Lankford coefficient in uniaxial tensile tests and validation with grain structure analysis. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 238:364–72. https://doi.org/10.1177/0954405422112191410.1177/09544054221121914 ↗
52. Yang X, Liu H, Zhang L, Hu Y, Politis DJ, Gharbi MM et al (2024) Interactive mechanism and friction modelling of transient tribological phenomena in metal forming processes: A review. Friction 12:375–395. https://doi.org/10.1007/S40544-023-0751-9/METRICS10.1007/S40544-023-0751-9/METRICS ↗
53. Kraus M, Lenzen M, Merklein M (2021) Contact pressure-dependent friction characterization by using a single sheet metal compression test. Wear 476:203679. https://doi.org/10.1016/J.WEAR.2021.20367910.1016/J.WEAR.2021.203679 ↗
54. Soare SC, Diehl M (2024) Calibration and fast evaluation algorithms for homogeneous orthotropic polynomial yield functions. Comput Mech 73:1219–39. https://doi.org/10.1007/S00466-023-02408-6/FIGURES/1910.1007/S00466-023-02408-6/FIGURES/19 ↗
55. Liu W, Huang J, Pang Y, Zhu K, Li S, Ma J (2023) Multi-scale modelling of evolving plastic anisotropy during Al-alloy sheet forming. Int J Mech Sci 247:108168. https://doi.org/10.1016/J.IJMECSCI.2023.10816810.1016/J.IJMECSCI.2023.108168 ↗
56. Zhang S, Lou Y, Yoon JW (2023) Earing prediction with a stress invariant-based anisotropic yield function under non-associated flow rule. Int J Mater Form 16:1–11. https://doi.org/10.1007/S12289-023-01749-0/FIGURES/1110.1007/S12289-023-01749-0/FIGURES/11 ↗