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Comparison of regression and artificial neural network model for the prediction of springback during air bending process of interstitial free steel sheet

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Abstract

This paper compares the regression and neural network modeling for predicting springback of interstial free steel sheet during air bending process. In this investigation, punch travel, strain hardening exponent, punch radius, punch velocity and width of the sheet were considered as input variables and springback as response variable. It has been observed that the ANN modeling process has been able to predict the springback with higher accuracy when compared with regression model.

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Abbreviations

a :

Constant

S:

Springback in degrees

r p :

Punch radius in mm

d :

Punch travel in mm

n :

Strain hardening exponent

v p :

Punch velocity in mm/s

w :

Width of the sheet in mm

θ s :

Springback angle (θ 1 − θ 2) in degrees

θ 1 :

Bending angle before springback in degrees

θ 2 :

Desired bending angle after springback in degrees

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Authors and Affiliations

  1. Department of Production Engineering, National Institute of Technology, Tiruchirappalli, 620015, Tamilnadu, India

    R. Narayanasamy

  2. Department of Mechanical Engineering, R.V.S. College of Engineering and Technology, Dindigul, 624005, Tamilnadu, India

    P. Padmanabhan

Authors
  1. R. Narayanasamy
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  2. P. Padmanabhan
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Correspondence to P. Padmanabhan.

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Narayanasamy, R., Padmanabhan, P. 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, 357–364 (2012). https://doi.org/10.1007/s10845-009-0375-6

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  • DOI: https://doi.org/10.1007/s10845-009-0375-6

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