Springback prediction and reduction in deep drawing under influence of unloading modulus degradation

Research output: Journal contributionsJournal articlesResearchpeer-review

Standard

Springback prediction and reduction in deep drawing under influence of unloading modulus degradation. / ul Hassan, Hamad; Maqbool, Fawad; Güner, Alper et al.
In: International Journal of Material Forming, Vol. 9, No. 5, 01.11.2016, p. 619-633.

Research output: Journal contributionsJournal articlesResearchpeer-review

Harvard

APA

Vancouver

ul Hassan H, Maqbool F, Güner A, Hartmaier A, Ben Khalifa N, Tekkaya AE. Springback prediction and reduction in deep drawing under influence of unloading modulus degradation. International Journal of Material Forming. 2016 Nov 1;9(5):619-633. doi: 10.1007/s12289-015-1248-5

Bibtex

@article{ddfca4cf37cf41e5a19438c99cd13f87,
title = "Springback prediction and reduction in deep drawing under influence of unloading modulus degradation",
abstract = "Springback is considered as one of the major problems in deep drawing of high-strength steels (HSS) and advanced high-strength steels (AHSS) which occurs during the unloading of part from the tools. With an ever increasing demand on the automotive manufactures for the production of lightweight automobile structures and increased crash performance, the use of HSS and AHSS is becoming extensive. For the accurate prediction of springback, unloading behavior of dual phase steels DP600, DP1000 and cold rolled steel DC04 for the deep drawing process is investigated and a strategy for the reduction of springback based on variable blankholder force is also presented. Cyclic tension compression tests and LS-Opt software are used for the identification of material parameters for Yoshida-Uemori (YU) model. Degradation of the Young{\textquoteright}s modulus is found to be 28 and 26 and 14 % from the initial Young{\textquoteright}s modulus for DP600, DP1000 and for the DC04 respectively for the saturated value. A finite element model is generated in LS-DYNA based on the kinematic hardening material model, namely Yoshida-Uemori (YU) model. The validation of numerical simulations is also carried out by the real deep drawing experiments. The springback could be predicted with the maximum deviation of 1.1 mm for these materials. For DP1000, the maximum springback is reduced by 24.5 %, for DP600 33.3 and 48.7 % for DC04 by the application of monotonic blankholder force instead of a constant blankholder force of 80 kN. It is concluded that despite the reduction of Young{\textquoteright}s modulus, the springback can be reduced for these materials by increasing the blankholder force only in last 13 % of the punch travel.",
keywords = "Deep drawing, Springback, Variable blankholder force, Young{\textquoteright}s modulus degradation, Engineering",
author = "{ul Hassan}, Hamad and Fawad Maqbool and Alper G{\"u}ner and Alexander Hartmaier and {Ben Khalifa}, Noomane and Tekkaya, {A. Erman}",
year = "2016",
month = nov,
day = "1",
doi = "10.1007/s12289-015-1248-5",
language = "English",
volume = "9",
pages = "619--633",
journal = "International Journal of Material Forming",
issn = "1960-6206",
publisher = "Springer Paris",
number = "5",

}

RIS

TY - JOUR

T1 - Springback prediction and reduction in deep drawing under influence of unloading modulus degradation

AU - ul Hassan, Hamad

AU - Maqbool, Fawad

AU - Güner, Alper

AU - Hartmaier, Alexander

AU - Ben Khalifa, Noomane

AU - Tekkaya, A. Erman

PY - 2016/11/1

Y1 - 2016/11/1

N2 - Springback is considered as one of the major problems in deep drawing of high-strength steels (HSS) and advanced high-strength steels (AHSS) which occurs during the unloading of part from the tools. With an ever increasing demand on the automotive manufactures for the production of lightweight automobile structures and increased crash performance, the use of HSS and AHSS is becoming extensive. For the accurate prediction of springback, unloading behavior of dual phase steels DP600, DP1000 and cold rolled steel DC04 for the deep drawing process is investigated and a strategy for the reduction of springback based on variable blankholder force is also presented. Cyclic tension compression tests and LS-Opt software are used for the identification of material parameters for Yoshida-Uemori (YU) model. Degradation of the Young’s modulus is found to be 28 and 26 and 14 % from the initial Young’s modulus for DP600, DP1000 and for the DC04 respectively for the saturated value. A finite element model is generated in LS-DYNA based on the kinematic hardening material model, namely Yoshida-Uemori (YU) model. The validation of numerical simulations is also carried out by the real deep drawing experiments. The springback could be predicted with the maximum deviation of 1.1 mm for these materials. For DP1000, the maximum springback is reduced by 24.5 %, for DP600 33.3 and 48.7 % for DC04 by the application of monotonic blankholder force instead of a constant blankholder force of 80 kN. It is concluded that despite the reduction of Young’s modulus, the springback can be reduced for these materials by increasing the blankholder force only in last 13 % of the punch travel.

AB - Springback is considered as one of the major problems in deep drawing of high-strength steels (HSS) and advanced high-strength steels (AHSS) which occurs during the unloading of part from the tools. With an ever increasing demand on the automotive manufactures for the production of lightweight automobile structures and increased crash performance, the use of HSS and AHSS is becoming extensive. For the accurate prediction of springback, unloading behavior of dual phase steels DP600, DP1000 and cold rolled steel DC04 for the deep drawing process is investigated and a strategy for the reduction of springback based on variable blankholder force is also presented. Cyclic tension compression tests and LS-Opt software are used for the identification of material parameters for Yoshida-Uemori (YU) model. Degradation of the Young’s modulus is found to be 28 and 26 and 14 % from the initial Young’s modulus for DP600, DP1000 and for the DC04 respectively for the saturated value. A finite element model is generated in LS-DYNA based on the kinematic hardening material model, namely Yoshida-Uemori (YU) model. The validation of numerical simulations is also carried out by the real deep drawing experiments. The springback could be predicted with the maximum deviation of 1.1 mm for these materials. For DP1000, the maximum springback is reduced by 24.5 %, for DP600 33.3 and 48.7 % for DC04 by the application of monotonic blankholder force instead of a constant blankholder force of 80 kN. It is concluded that despite the reduction of Young’s modulus, the springback can be reduced for these materials by increasing the blankholder force only in last 13 % of the punch travel.

KW - Deep drawing

KW - Springback

KW - Variable blankholder force

KW - Young’s modulus degradation

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=84936806090&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/c3304298-7024-3a37-9817-3c2ec93dfc20/

U2 - 10.1007/s12289-015-1248-5

DO - 10.1007/s12289-015-1248-5

M3 - Journal articles

AN - SCOPUS:84936806090

VL - 9

SP - 619

EP - 633

JO - International Journal of Material Forming

JF - International Journal of Material Forming

SN - 1960-6206

IS - 5

ER -

Recently viewed

Publications

  1. Hypertext
  2. Control of the inverse pendulum based on sliding mode and model predictive control
  3. Continuous 3D scanning mode using servomotors instead of stepping motors in dynamic laser triangulation
  4. A decoupled MPC using a geometric approach and feedforward action for motion control in robotino
  5. Model predictive control for switching gain adaptation in a sliding mode controller of a DC drive with nonlinear friction
  6. Loss systems in a random environment: steady state analysis
  7. Differences Between Classical and Bayesian Estimates for Mixed Logit Models
  8. A general structural property in wavelet packets for detecting oscillation and noise components in signal analysis
  9. A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations
  10. A simple fuzzy controller for robot manipulators with bounded inputs
  11. Perfect anti-windup in output tracking scheme with preaction
  12. Advantages and Disadvanteges of Different Text Coding Procedures for Research and Practice in a School Context
  13. Simulation based comparison of safety-stock calculation methods
  14. Semantic Parsing for Knowledge Graph Question Answering with Large Language Models
  15. Correlation between mechanical behaviour and microstructure in the Mg-Ca-Si-Sr system for degradable biomaterials based on thermodynamic calculations
  16. Trajectory-based computational study of coherent behavior in flows
  17. Enhancing the Building Information Modeling Lifecycle of Complex Structures with IoT
  18. Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor
  19. A geometric approach for controlling an electromagnetic actuator with the help of a linear Model Predictive Control