PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Characterizing the formability of mild steel in the production of square components by deep drawing process

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The deep drawing process for square cups is commonly utilized in sheet metal forming, however, there are many associated defects, including fracture, earing, wrinkling. A problem that has more attention in this work is the studying of the influence of the different parameters such as blank diameter, drawing speed, and punch profile radius on the formability of the squared cups. Three circular blanks with diameter (80, 90, 100) mm, three punch profile radius of (4, 7, 10) mm, and three drawing speed of (100, 200, 300) mm/min have been chosen, while the other parameters kept constant. The formability indicators utilized in this study are thickness distribution, maximum thinning and maximum drawing force. The experiments were designed by L9 Taguchi method and analyzed by ANOVA and S/N ratios techniques. The results shown that square cup corners experience higher deformation than that of the side walls cup. Consequently, during plastic deformation, the metal flows along the side walls of the cup are easier and more uniform compared to those in the corners. The best results were obtained from the 80mm blank dimeter, with 100mm/min drawing speed and 7mm punch profile radius according to the uniform thickness distribution, maximum thinning and maximum drawing force.
Twórcy
  • Production Engineering and Metallurgy Department, University of Technology, Baghdad, Iraq
Bibliografia
  • 1. Behrens B.-A., Hübner S., Wehmeyer J., Müller P., and Yarcu S. Tribological investigations of water-based lubricants for application in the deep drawing process, IOP Conf. Ser. Mater. Sci. Eng., 2024, 1307(1), 012001, https://doi.org/10.1088/1757-899x/1307/1/012001
  • 2. Leng Y., Sanjon C. W., Tan Q., Groche P., Hauptmann M., and Majschak J. Study of Parameters Influencing Wrinkles in the Deep Drawing of Fiber-Based Materials Using Automatic Image Detection, 2024.
  • 3. Xie H., Lu Y., Li R., and Liu J. Multi-pass deep-drawing process and mould design for thin-walled hollow cylindrical parts, Appl. Comput. Eng., 2024, 709(1), 85–91, https://doi.org/10.54254/2755-2721/70/20240964
  • 4. Heinzel C., Thiery S., and Khalifa B.N. Study on the effects of tool design and process parameters on the robustness of deep drawing, Mater. Res. Proc., 2024, 41, 1488–1497, https://doi.org/10.21741/9781644903131-165
  • 5. Jaber A. S., Shukur J. J., and Khudhir W. S. Analysis of the process parameters effect on the thickness distribution and thinning ratio in single point incremental forming process, J. Mech. Eng. Res. Dev., 2020, 43(7), 374–382.
  • 6. Shukur J. J. and Jaber A. S. Experimental and finite element analysis study of die geometrical affect the forming load during extrusion process, IOP Conf. Ser. Mater. Sci. Eng., 2020, 881(1), https://doi.org/10.1088/1757-899X/881/1/012045
  • 7. Nizam M. Wrinkling Defect in Sheet Metal Process using Finite Element Analysis, Int. J. Res. Appl. Sci. Eng. Technol., 2022, 10(6), 4421–4429, https://doi.org/10.22214/ijraset.2022.44947
  • 8. Rajhi W. Numerical Simulation of Damage on Warm Deep Drawing of Al 6061-T6 Aluminium Alloy, Eng. Technol. Appl. Sci. Res., 2019, 9(5), 4830–4834, https://doi.org/10.48084/etasr.3148
  • 9. Jaber A., Mohammed A., and Younis K. Improvement of Formability of AISI 1006 Sheets by Hydroforming with Die in Square Deep Drawing, Eng. Technol. J., 2023, 0(0), 1–9, https://doi.org/10.30684/etj.2023.141104.1482
  • 10. Sevšek L., Vilkovský S., Majerníková J., and Pepelnjak T. Predicting the deep drawing process of TRIP steel grades using multilayer perceptron artificial neural networks, Adv. Prod. Eng. Manag., 2024, 19(1), 46–64, https://doi.org/10.14743/apem2024.1.492
  • 11. Miłek T. Experimental determination of material boundary conditions for computer simulation of sheet metal deep drawing processes, Adv. Sci. Technol. Res. J., 2023, 17(5), 360–373, https://doi.org/10.12913/22998624/172364
  • 12. ASTM, ASTM E8/E8M standard test methods for tension testing of metallic materials 1, Annu. B. ASTM Stand. 2010, 4,(I), C, 1–27, https://doi.org/10.1520/E0008
  • 13. Modi B. and Kumar D. R. Optimization of process parameters to enhance formability of AA 5182 alloy in deep drawing of square cups by hydroforming, J. Mech. Sci. Technol., 2019, 33(11), 5337–5346, https://doi.org/10.1007/s12206-019-1026-2
  • 14. Bedan, A.S., Mansor, K.K., Anwer, K.K., Kadhim, H.H. Design and Implementation of Asymmetric Extrusion Die Using Bezier Technique, IOP Conference Series: Materials Science and Engineering, 2020, 881(1), 012052.
  • 15. Bedan, A.S., Shabeeb, A.H., Hussein, E.A. Improve single point incremental forming process performance using primary stretching forming process. Advances in Science and Technology Research Journal, 2023, 17(5), 260–268.
  • 16. Abbas, E.A., Mansor, K.K. Numerical and Experimental Investigation of the Effect of Strength of Aluminum 6061 Alloy on Thickness Reduction in Single-Point Incremental Forming, Advances in Science and Technology Research Journal, 2023, 17(4), 271–281.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c66f7a54-b6cd-4012-9eec-55ccfa397d6f
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.