Skip to main content
Log in

Design of a digital management system for the sintering material ground

  • Regular Paper
  • Published:
International Journal of Automation and Computing Aims and scope Submit manuscript

Abstract

There are many kinds and a large number of raw materials in the sintering material ground to be managed, while it is difficult to obtain the precise inventory values, which often leads to high cost. Furthermore, the external factors of material ground are difficult to handle, such as weather variation, order fluctuation, measurement failure and so on. To solve such raw material management problems, a digital management system has been developed. First, the practical requirements and the raw material management processes are analyzed. Then, optimization and prediction methods are used to calculate the inventory according to the practical situation. With the help of practical technologies and production conditions, the developed system has been applied to a large-scale sintering material ground. The practical running results of the application demonstrate the validity of the proposed digital management system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. B. Kim, J. Koo, B. S. Park. A raw material storage yard allocation problem for a large-scale steelworks. International Journal of Advanced Manufacturing Technology, vol. 41, no. 9–10, pp. 880–884, 2009.

    Article  Google Scholar 

  2. S. H. Li, L. X. Tang. Storage space allocation in material yards of integrated iron and steel plants. Control and Decision, vol. 21, no. 6, pp. 656–660, 665, 2006. (in Chinese)

    Google Scholar 

  3. R. J. Goelho, J. Guzzoul, M. M. Fioroni, E. L. M Harano, J. S. Lima, J. B. Mendes, R. B. Santos. Simulation of raw material yard at CST. Revue de Metallurgie. Cahiers D Informations Techniques, vol. 103, no. 3, pp. 117–120, 2006.

    Google Scholar 

  4. R. J. Coelho, P. F. Lana, A. C. Silva, T. F. Santos, M. M. Fioroni, L. Franzese, D. de Oliveira Mota, L. B. da Silva. Operational simulation model of the raw material handling in an integrated steel making plant. In Proceedings of 2009 Winter Simulation Conference, IEEE, Austin, TX, USA, pp. 3055–3065, 2009.

    Chapter  Google Scholar 

  5. T. G. Lim, K. W. Jeong. Evaluation of operation load in automatic raw material inspection system. In Proceedings of 2003 IEEE Conference on Control Applications, IEEE, Turkey, Japan, pp. 870–875, 2003.

    Google Scholar 

  6. P. George, T. D. Banerjee. Simulation model for a raw material unloading system in a steel plant. Bulk Solids Handling, vol. 15, no. 4, pp. 55–58, 1995.

    Google Scholar 

  7. Y. Goldblatt. Optimization tool helps to reduce raw material costs at Arcelormittal Dunkerque. MPI Metallurgical Plant and Technology International, vol. 32, no. 3, pp. 26–29, 2009.

    Google Scholar 

  8. J. S. Lamba. Importance of raw material preparations for iron and steel industry in India with reference to Durgapur Steel Plant. Journal of Mines, Metals and Fuels, vol. 40, no. 3, 1992.

  9. Y. Cai, M. Wu, S. L. Wang, C. S. Wang. Prediction method based on multi-model integration for iron mine powders inventories. Journal of Central South University (Science and Technology), vol. 42, no. 11, pp. 3399–3407, 2011. (in Chinese)

    Google Scholar 

  10. Q. Lu, P. Luo. A learning particle swarm optimization algorithm for odor source localization. International Journal of Automation and Computing, vol. 8, no. 3, pp. 371–380, 2011.

    Article  Google Scholar 

  11. M. Yoshida, M. Kimura. Depository planning expert system for raw material yard. Hitachi Review, vol. 14, no. 1, pp. 39–14, 1992.

    Google Scholar 

  12. Y. Cai, S. L. Wang, M. Wu, C. S. Wang, X. Z. Lai. Design and application of digital management system for the sinter raw material plant. In Proceedings of 2011 International Symposium on Advanced Control of Industrial Processes, Hangzhou, China, pp. 565–570, 2011.

  13. N. Kanagarajl, P. Sivashanmugaml, S. Paramasivam. A fuzzy logic based supervisory hierarchical control scheme for real time pressure control. International Journal of Automation and Computing, vol. 6, no. 1, pp. 88–96, 2009.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Min Wu.

Additional information

This work was supported by National High Technology Research and Development Program of China (863 Program) (No. 2012AA040307).

Yan Cai received her B. Sc. and M. Sc. degrees in engineering from Central South University, China in 2000 and 2007, respectively. Currently, she is a Ph. D. candidate in the Department of Control Engineering at the School of Information Science and Engineering, Central South University, China.

Her research interests include process control and intelligent optimization.

Min Wu received his B. Sc. and M. Sc. degrees in engineering from Central South University, China in 1983 and 1986, respectively. He received the Ph.D. degree in engineering from Tokyo Institute of Technology, Japan in 1999. Since 1986, he has been with Central South University, where he is currently a professor of automatic control engineering at the School of Information Science and Engineering. He was a visiting scholar in the Department of Electrical Engineering, Tohoku University, Japan from 1989 to 1990, a visiting research scholar in the Department of Control and Systems Engineering, Tokyo Institute of Technology, Tokyo from 1996 to 1999, and a visiting professor at the School of Mechanical, Materials, Manufacturing and Management, University of Nottingham, England from 2001 to 2002. He is an IEEE senior member. He received the Best Paper Award at the International Federation of Automatic Control in 1999 (jointly with M. Nakano and J. H. She).

His research interests include robust control and its application, process control and intelligent control.

Jin-Ni Zhou received her B. Sc. degree in engineering from Central South University, China in 2010. Currently, she is a master student in the Department of Control Engineering at the School of Information Science and Engineering, Central South University, China.

Her research interests include process control and intelligent Optimization.

Xin Chen received his B. Sc. degree in Industrial Automation, and the M. Sc. degree in control theory and control engineering from Central South University, China in 1999 and 2002, respectively. He received the Ph.D. degree in electromechanical Engineering from the University of Macau, China in 2007. He is currently an associate professor at Central South University, China.

His research interests include multi-agent system, robotics and intelligent control.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cai, Y., Wu, M., Zhou, JN. et al. Design of a digital management system for the sintering material ground. Int. J. Autom. Comput. 9, 587–593 (2012). https://doi.org/10.1007/s11633-012-0683-8

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11633-012-0683-8

Keywords

Navigation