Development of a neural network model to predict distortion during the metal forming process by line heating

  • César Pinzón Specialized Research Center for Manufacturing and Joining Processes (LEPUM) – School of Mechanical Engineering – Technological University of Panama.
  • Carlos Plazaola Member of the National Researcher Systems (SNI) – SENACYT, Panama.
  • Ilka Banfield
  • Amaly Fong
  • Adán Vega

Abstract

In order to achieve automation of the plate forming process by line heating, it is necessary to know in advance the deformation to be obtained under specific heating conditions. Currently, different methods exist to predict deformation, but these are limited to specific applications and most of them depend on the computational capacity so that only simple structures can be analyzed. In this paper, a neural network model that can accurately predict distortions produced during the plate forming process by line heating, for a wide range of initial conditions including large structures, is presented. Results were compared with data existing in the literature showing excellent performance. Excellent results were obtained for those cases out of the range of the training data.

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References

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Published
2013-01-23
How to Cite
Pinzón, C., Plazaola, C., Banfield, I., Fong, A., & Vega, A. (2013). Development of a neural network model to predict distortion during the metal forming process by line heating. Ciencia Y tecnología De Buques, 6(12), 41-49. https://doi.org/10.25043/19098642.77
Section
Scientific and Technological Research Articles