Accurate prediction of springback in forming of BIW parts

Nagur Aziz Kamal Bashah, Ahmad Zakaria, Khairul Za im Kamarulzaman, Achmed Mobin, Mohd Safuan Mohd Abdul Lazat, Norhamidi Muhamad, Baba Md Deros

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The use of High Strength Steels (HSS) for automotive parts improves car performance in terms of structural strength and weight reduction. However it poses major challenges to manufacturing since HSS is prone to springback. Springback causes deviation in part geometry from its intended design thus giving problem to its subsequent assembly process. In this paper, three models for predicting springback were evaluated. First model is based on the Multiple Regression (MR) technique. Second model utilized Hill Orthotropic constitutive material model and the last model employed a neural network predictive model. All the models were evaluated by using tool surface and stamped part historical data that are obtained from three selected springback prone automotive BIW parts representing three different levels of springback severity namely high, medium and small. The results on the low springback part show that the neural network model outperforms the other approaches.

Original languageEnglish
Title of host publicationApplied Mechanics and Materials
Pages93-97
Number of pages5
Volume165
DOIs
Publication statusPublished - 2012
EventRegional Conference on Automotive Research, ReCAR 2011 - Kuala Lumpur
Duration: 14 Dec 201115 Dec 2011

Publication series

NameApplied Mechanics and Materials
Volume165
ISSN (Print)16609336
ISSN (Electronic)16627482

Other

OtherRegional Conference on Automotive Research, ReCAR 2011
CityKuala Lumpur
Period14/12/1115/12/11

Fingerprint

High strength steel
Neural networks
Railroad cars
Geometry

Keywords

  • Multiple regression
  • Neural network
  • Springback

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Bashah, N. A. K., Zakaria, A., Kamarulzaman, K. Z. I., Mobin, A., Lazat, M. S. M. A., Muhamad, N., & Md Deros, B. (2012). Accurate prediction of springback in forming of BIW parts. In Applied Mechanics and Materials (Vol. 165, pp. 93-97). (Applied Mechanics and Materials; Vol. 165). https://doi.org/10.4028/www.scientific.net/AMM.165.93

Accurate prediction of springback in forming of BIW parts. / Bashah, Nagur Aziz Kamal; Zakaria, Ahmad; Kamarulzaman, Khairul Za im; Mobin, Achmed; Lazat, Mohd Safuan Mohd Abdul; Muhamad, Norhamidi; Md Deros, Baba.

Applied Mechanics and Materials. Vol. 165 2012. p. 93-97 (Applied Mechanics and Materials; Vol. 165).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bashah, NAK, Zakaria, A, Kamarulzaman, KZI, Mobin, A, Lazat, MSMA, Muhamad, N & Md Deros, B 2012, Accurate prediction of springback in forming of BIW parts. in Applied Mechanics and Materials. vol. 165, Applied Mechanics and Materials, vol. 165, pp. 93-97, Regional Conference on Automotive Research, ReCAR 2011, Kuala Lumpur, 14/12/11. https://doi.org/10.4028/www.scientific.net/AMM.165.93
Bashah NAK, Zakaria A, Kamarulzaman KZI, Mobin A, Lazat MSMA, Muhamad N et al. Accurate prediction of springback in forming of BIW parts. In Applied Mechanics and Materials. Vol. 165. 2012. p. 93-97. (Applied Mechanics and Materials). https://doi.org/10.4028/www.scientific.net/AMM.165.93
Bashah, Nagur Aziz Kamal ; Zakaria, Ahmad ; Kamarulzaman, Khairul Za im ; Mobin, Achmed ; Lazat, Mohd Safuan Mohd Abdul ; Muhamad, Norhamidi ; Md Deros, Baba. / Accurate prediction of springback in forming of BIW parts. Applied Mechanics and Materials. Vol. 165 2012. pp. 93-97 (Applied Mechanics and Materials).
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