Journals →  Tsvetnye Metally →  2017 →  #10 →  Back

ArticleName Simulation model of bar iron cutting
DOI 10.17580/tsm.2017.10.12
ArticleAuthor Kapralov D. S., Donchan D. M., Salikhov M. Z.

Institute of Control Sciences RAS, Moscow, Russia:

D. S. Kapralov, Post-Graduate Student of Laboratory 41, e-mail:
D. M. Donchan, Post-Graduate Student of Laboratory 41, e-mail:
M. Z. Salikhov, Senior Researcher of Laboratory 41


Commercializing led to the influence of all financial costs of rolled products manufacturing on rolled products competitiveness. The crop end volume is sufficient among all these costs, because those rolled products, sub-standard by geometrical dimension, are sold to consumers at a low price or they are able to sequent melting and further technological stages of production. We carried out the analysis of the reasons of crop end formation on the rolling mill 250 with two-stage cutting of bar iron. The mathematical models of thermal broadening of bar iron and material flows on the rolling mill 250 are shown. We found the correspondence of the problem of optimal cutting of bar iron to the knapsack problem (NP-complete problems). We also briefly analyzed and offered the existing methods of this problem solving. We stated the universal target function for cutting of rolled products made of non-ferrous metals, alloys and ferrous metals. The initial data for mathematical model of the considered system are given. The analysis of the obtained graphic results was carried out, and the convergence for the final number of iterations was shown. We developed and briefly described the software complex OPTIKS 1.0, where all the mathematical models considered above, are realized. This software complex has a graphical user interface and works as an adviser of cutting operator. The main function of this software complex is an early calculation of the best cutting mode (before rolling)and its visualization for operator.

keywords Minimization of crop end, best cutting, OPTIKS, cluster analysis, genetic algorithm, Monte-Carlo method, knapsack problem, stock of orders

1. Kantorovich L. V. Mathematical methods of production scheduling and organization. Leningrad : LGU, 1939. 68 p.
2. Valiakhmetova Yu. I., Filippova A. S. Theory of optimum resource utilization by L. V. Kantorovich in cutting-packing problems: overview and history of development of solving methods. Vestnik Ufimskogo gosudarstvennogo aviatsionnogo tekhnicheskogo universiteta. 2014. No. 1. pp. 186–197.
3. Technological of rolled product ends and bar iron cutting on the mill 250. JSC “Izhstal”, 2014.
4. Salikhov Z. G. Modeling of singularly perturbed multi-criterion optimal control workflows. IFAC-PapersOnline. 2015. Vol. 48, No. 3. pp. 1254–1258.
5. Christos H., Kenneth S. Combinatorial optimization: algorithms and complexity, dover pubns. Unabridged edition, 1998.
6. Schrijver A. A Course in Combinatorial Oprimization. Amsterdam, 2006.
7. Salikhov Z. G., Genkin A. L. Modeling and control of technological processes of metal forming. Metally. 2015. No. 6. pp. 103–108.
8. Kantorovich L. V., Zalgaller V. A. Efficient cutting of industrial materials : third edition. Saint Petersburg : Nevskiy Dialekt, 2012. 304 p.
9. Batishchev D. I. et al. Solving of discrete problems by evolution-genetic algorithms. Nizhniy Novgorod : NNGU, 2011.
10. Gladkov L. A., Kureychik V. V., Kureychik V. M. Genetic algorithms : tutorial, second edition. Moscow : Fizmatlit, 2006. 320 p.
11. Goldberg D. E. Genetic algorithm in search, optimization, and machine learning. Boston : Addison-Wesley Longman Publishing Co. 1989. 412 p.
12. Salikhov Z. G., Ginsberg K. S. Investigation into the evolution of identification of metallurgical process mathematical models when creating real automatic control systems. Tsvetnye Metally. 2016. No. 11. pp. 105–112.
13. Dyuran B., Odell P. Cluster analysis. Moscow : Statistika, 1977. 128 p.
14. Salikhov Z. G., Gazimov R. T., Genkin A. L., Nikulina I. V. New solutions for thermal treatment of flat products using self-adjusting mathematical models with partly observable parameters. IFAC-PapersOnline. 2015. Vol. 48, No. 3. pp. 1242–1247.

Language of full-text russian
Full content Buy