A Non-lineal Mathematical Model for Annealing Stainless Steel Coils

Raquel González Corral, J. Bonelo Sánchez, Carlos G. Spinola, C. Galvez-Fernández, M. Martín-Vázquez

Abstract

Stainless steel manufacturing has experienced a high growth. Nowadays the stainless steel manufacturing is an industry with many applications. Annealing process is an important process in the production of stainless steel coils. The aim of this research is to obtain the classification of defective annealed coils. So a nonlinear mathematical model has been developed for the annealing process. In this research the following techniques have been used: SOM neural networks and classifications methods. For testing, temperature signals were collected along the annealing furnace, also speed signal of the production line were collected. These signals are correlated with each one of the manufactured coils.

References

  1. Chapple Mike, “Data Mining: An Introduction”, 2002. http://databases.about.com/library/weekly/aa100700a. htm
  2. J. Kangas, T. Kohonen, (1997). Developments and applications of the self organizing map (SOM) and related algorithms. Mathematics and Computers in simulation, 41 (1-2); 3-12.
  3. Khan S. H., Ali F., Nusair Khan A., Iqbal M. A., (2008). Eddy current detection of changes in stainless steel after cold reduction. Computational Materials Science, vol.43, no.4, 2008, pp. 623-8.
  4. T. Kohonen (1997) The Self Organizinf Map. Springer. 2ª Ed.
  5. T. Kohonen, J. Hunniyen, J. Kangas, J. Laaksonen, (1992- 1997). The Self Organizing Map program package”. Helsinki University of Technology, Finland.
  6. Reed, R. J., (2003). North American Combustion Handbook. North American Manufacturing Company. Cleveland.
  7. C. Spinola, J. Bonelo, J. Vizoso et al., (2008). Supervision model for the annealing process in a stainless steel production line. IEEE International Conference on Industrial Technology. Pages 1-4.
  8. C. Spinola, J. Bonelo, J. Vizoso et al., (2004). An approach to the analysis of thickness deviations in stainless steel coils based on self-organising map neural networks. Springer London. Pages 309-315. DOI: 10.1007/s00521-004-0426-z.
  9. Ben Young, (2008). Experimental and numerical investigation of high strength stainless steel structures. Journal of Constructional Steel Research, vol.64, no.11, 2008, pp. 1225-30.
Download


Paper Citation


in Harvard Style

González Corral R., Bonelo Sánchez J., G. Spinola C., Galvez-Fernández C. and Martín-Vázquez M. (2012). A Non-lineal Mathematical Model for Annealing Stainless Steel Coils . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 607-610. DOI: 10.5220/0004112206070610


in Bibtex Style

@conference{ncta12,
author={Raquel González Corral and J. Bonelo Sánchez and Carlos G. Spinola and C. Galvez-Fernández and M. Martín-Vázquez},
title={A Non-lineal Mathematical Model for Annealing Stainless Steel Coils},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)},
year={2012},
pages={607-610},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004112206070610},
isbn={978-989-8565-33-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)
TI - A Non-lineal Mathematical Model for Annealing Stainless Steel Coils
SN - 978-989-8565-33-4
AU - González Corral R.
AU - Bonelo Sánchez J.
AU - G. Spinola C.
AU - Galvez-Fernández C.
AU - Martín-Vázquez M.
PY - 2012
SP - 607
EP - 610
DO - 10.5220/0004112206070610