Improving Steel Industrial Processes Using Genetic Algorithms and Finite Element Method

  • Andrés Sanz-García
  • Rubén Lostado-Lorza
  • Alpha Pernía-Espinoza
  • Francisco J. Martínez-de-Pisón-Ascacíbar
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 87)

Abstract

Steel industrial engineers must estimate optimal operational parameters of industrial processes and the correct model for complex material behaviour. Common practice has been to base these determinations on classic techniques, such as tables and theoretical calculations. In this paper three successful experiences combining finite element modelling with genetic algorithms are reported. On the one hand, two cases of improvement in steel industrial processes are explained; on the other hand, the efficient determination of realistic material behaviour laws is presented. The proposed methodology optimizes and fully automates these determinations. The reliability and effectiveness of combining genetic algorithms and the finite element method is demonstrated in all cases.

Keywords

Genetic Algorithms optimization Finite Element Method Material Behaviour Model Straightening Process Tension Levelling Process 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Andrés Sanz-García
    • 1
  • Rubén Lostado-Lorza
    • 1
  • Alpha Pernía-Espinoza
    • 1
  • Francisco J. Martínez-de-Pisón-Ascacíbar
    • 1
  1. 1.Department of Mechanical EngineeringUniversity of La RiojaLogroñoSpain

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