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Smyslova Simulation modeling of logistic system for liquid iron transportation at metallurgical plant

https://doi.org/10.17073/0368-0797-2020-1-71-77

Abstract

During the study of technological data of the process of liquid iron transportation, it was found that the number of locomotives and mixers depending on the duration of operations and especially on the inter-operational downtime does not always ensure normal rhythm of the main production. It leads to significant production losses, therefore, the work of the producing and transport complex is not effective enough. The authors have developed a simulation model of a logistics system for transporting liquid iron at a metallurgical plant. The study and construction of the model was performed using AnyLogic. Real data from production, namely the schedule of blast furnace smelting for a three-week period, was used as the initial data. To prove adequacy of the model, the results were compared with the actual tact of the mixers movement, as well as with the theoretical need of the converter shop. Values of the liquid iron weight delivered to the converter shop were obtained during the simulation and were related to the theoretical ones. Efficiency of the model is achieved by automatically collecting in real time of statistical values of the parameters of simulation objects. The system analyzes the collected data and makes decisions based on them for a short period of time (less than one second). In default operation mode of the simulation model, motion of the mixers is controlled automatically without participation of the dispatcher, which improves efficiency, as well as decision-making speed. Such model provides simulation of failures in operation of the converter shop. According to the simulation results, it can be concluded that the system delivers less liquid iron to a converter shop, but retains its rhythm. After resuming the operation of all converters, the tact of transportation reaches the required level.

About the Authors

K. O. Vinogradov
Cherepovets State University
Russian Federation
Postgraduate of the Chair “Automation and Management”


A. L. Smyslova
Cherepovets State University
Russian Federation

Cand. Sci. (Eng.), Assist. Professor of the Chair “Automation and Management”



References

1. Emel’yanova N.Yu. Information technology for control of liquid iron transportation. Sistemy obrabotki informatsii. 2010, no. 9, pp. 32–36. (In Russ.).

2. Jun-qing Li, Quan-ke Pan, Pei-yong Duan. Improved artificial bee colony algorithm for solving hybrid flexible flowshopwith dynamic operation skipping // IEEE Transactions on Cybernetics. 2016. Vol. 46. No. 6. P. 1311 – 1324.

3. Su L., Qi Y., Jin L.-L., Zhang G.-L. Integrated batch planning optimization based on fuzzy genetic and constraint satisfaction for steel production // International Journal of Simulation Modelling. 2016. Vol. 15. No. 1. P. 133 – 143.

4. Xiaoyan Yang, Bingmou Cui, Jie Chen. Intelligentized dispatching control of railway transport of molten iron in metallurgical enterprise // Proc. of 2013 Int. Conf. on Information Science and Computer Applications. Jianguo Hu ed. 2013. P. 287 – 293.

5. Gusev Yu.V. Matematicheskaya model’ protsessa transportirovaniya chuguna v konverternyi tsekh [Mathematical model of iron transportation to converter shop]. St. Petersburg: Piter, 2007, pp. 287–293. (In Russ.).

6. Bin Ge, Kai Wang, Yue Han. A design for simulation model and algorithm of rail transport of molten iron in steel enterprise // Сomputer Modelling & New Technologies. 2014. Vol. 18. No. 11. P. 1056 – 1061.

7. Feliks J., Majewska K. Agent-based modeling of steel production processes under uncertainty // METAL 2015: Proc. of Int. Conf. on Metallurgy and Materials, June 3 – 5, 2015, Brno, Czech Republic. P. 1739 – 1744.

8. Liu F. Analysis on organization and capability of hot iron transportation at Baosteel // Baosteel Technology. 2001. No. 5. P. 1 – 6.

9. Hua Yan, Jun Xuan, Nai-yuanTian. Research of time distribution in hot metal supply process // Iron and Steel. 2005. Vol. 40. No. 3. P. 21 – 24.

10. Sun J., Xue D. A dynamic reactive scheduling mechanism for responding to changes of production orders and manufacturing resources // Computers in Industry. 2001. Vol. 46. No. 2. P. 189 – 207.

11. Lixin Tang, Gongshu Wang, Jiyin Liu. A branch-and-price algorithm to solve the molten iron allocation problem in iron and steel industry // Computers & Operations. 2005. Vol. 2007. No. 34. P. 3001 – 3015.

12. Tang L., Wang X. Simultaneously scheduling multiple turns for steel color-coating production // European Journal of Operational Research. 2009. Vol. 198. No. 3. P. 715 – 725.

13. Tang L., Rong A., Yang Z. A review of planning and scheduling systems and methods for integrated steel production // European Journal of Operational Research. 2001. Vol. 133. No. 1. P. 1 – 20.

14. Tang L., Luh P.B., Liu J., Fang L. Steel-making process scheduling using Lagrangian relaxation // International Journal of Production. 2002. Vol. 40. No. 1. P. 55 – 70.

15. Engin O., Ceran G., Yilmaz M.K. An efficient genetic algorithm for hybrid flow shop scheduling with multiprocessor task problems // Applied Soft Computing. 2011. Vol. 11. No. 3. P. 3056 – 3065.

16. Ruiz R., Rodríguez J.A.V. The hybrid flow shop scheduling problem // European Journal of Operational Research. 2010. Vol. 205. No. 1. P. 1 – 18.

17. Wang Wenrui. Iron melt control and management system in Baosteel [Part one] // Metallurgical Industry Automation. 2001. No. 4. P. 22 – 24.

18. Liu Y.Y. The mix integer programming model for torpedo car scheduling in iron and steel industry // International Conference on Computer Information Systems and Industrial Applications. 2015. P. 731 – 734.

19. Kupriyashkin A.G. Osnovy modelirovaniya sistem: ucheb. posobie [Basics of system modeling: Manual]. Noril’sk: NII, 2015, 134 p. (In Russ.).

20. Boev V.D. Komp’yuternoe modelirovanie: posobie dlya prakticheskikh zanyatii, kursovogo i diplomnogo proektirovaniya v AnyLogic 7 [Computer modeling: Manual for practical classes, course and degree design in AnyLogic 7]. St. Petersburg: VAS, 2014, 432 p. (In Russ.).


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For citations:


Vinogradov K.O., Smyslova A.L. Smyslova Simulation modeling of logistic system for liquid iron transportation at metallurgical plant. Izvestiya. Ferrous Metallurgy. 2020;63(1):71-77. (In Russ.) https://doi.org/10.17073/0368-0797-2020-1-71-77

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ISSN 0368-0797 (Print)
ISSN 2410-2091 (Online)