Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
cетевое издание
issn 2310-6018


Kabulova E.G.  

UDC 004.89
DOI: 10.26102/2310-6018/2019.24.1.022

  • Abstract
  • List of references
  • About authors

To date, the level of development of metallurgical production imposes high requirements to production management systems and the quality of steel products, due to the development of information technology. Metallurgical production from the point of view of management and multistage character of production is a complex, large system with different characteristics of subsystems and elements of processing. Traditional methods of modeling for the management of such systems are ineffective, as one of the main problems is the choice of optimal management decisions taking into account current situations and restrictions on changes in the values of technological parameters. In this regard, there is a need to develop a methodology that would improve the management of technological systems, organize decisionmaking support in the face of uncertainty, to ensure the speed and accuracy of information to improve the quality of metal products and technical and economic indicators and the reliability of production. The application of new methods of analysis of complex production systems of information processing, management improvement and decision-making will improve the efficiency of enterprises and reduce the proportion of low-quality products. The aim of the study is to use new methods of analysis of complex production systems of information processing, improvement of management and decision-making, which will improve the efficiency of enterprises and reduce the share of low-quality products. As a result, the formalization of the problem of integrated management of output indicators of product quality, taking into account the uncertainty of internal factors of metallurgical production. The software implementation of the algorithms will increase the efficiency of decision-making by determining the optimal technological parameters from the range of permissible values.

1. Bestuzhev-Lada I. V. working book on forecasting. M.: Mysl, 1982. 430 p.

2. Kabulova E.G. Mathematical modeling of production processes in metallurgy. Stary Oskol: TNT Publishing house, 2014. - 131 c.

3. Mesarovich M., Mako D., Takahara I. theory of hierarchical multilevel systems. M.: Publishing House "Mir", 1973. - 344 c.

4. Rozhkov I. M., Vlasov S. A., Malko, G. N. A mathematical model for the choice of rational technology and quality control of steel. M.: Metallurgy, 1990. - 398 p.

5. Baldwin J.F., Guild N.C. Comparison of Fuzzy Sets on the Same Decision Space // Fuzzy Sets and Systems. - 1879. - Vol. 2. - № 3. - Pp. 231-231.

6. Gitman M.B., Trusov P.V., Fedoseev S.A. On optimization of metal forming with adaptable characteristics // Journal of Applied Mathematics and Computing. - 2000. - Vol. 7. - No. 2. - Pp. 387-396.

7. Matsko I.I. Adaptive fuzzy decision tree with dynamic structure for automatic process control system o of continuous-cast billet production // IOSR Journal of Engineering. - 2012. - Vol. 2. - № 8. - Pp. 53-55.

8. Merkuryeva G. Computer Simulation in Industrial Management Games // Proc. of MlM 2000. IFAK Symp. on Manufacturing, Modeling, Management and Control. University of Patras, Rio, Greece. - 2000. - Pp. 69 -73.

9. Michalska H., Ellis J.E., Roberts P.D. Joint coordination method for the steady state control of large-scale systems // Int. J. Syst. Sci. - 1985. - № 5. - Pp. 605 - 618.

10. Saati T. and Kerns K. Analytical planning. Organization of systems. M: Radio and communication, 1991. - 224 p.

11. Saati T.L. Decision-making. Method of the analysis of hierarchies. M.: Radio and communication, 1993. - 278 p.

Kabulova Evgeniya Georgievna
Candidate of Technical Sciences Associate Professor
Email: evgenia791@mail.ru

Stary Oskol Technological Institute named after A.A. Ugarov (branch) NUST «MISIS»

Stary Oskol, Russian Federation

Keywords: metallurgical production, intelligent control support, multi-stage technology in the context of uncertainty, metallurgical production

For citation: Kabulova E.G. INTELLIGENT CONTROL OF MULTISTAGE SYSTEMS OF METALLURGICAL PRODUCTION. Modeling, Optimization and Information Technology. 2019;7(1). Available from: https://moit.vivt.ru/wp-content/uploads/2019/01/Kabulova_1_19_1.pdf DOI: 10.26102/2310-6018/2019.24.1.022 (In Russ).


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