Журналы →  Gornyi Zhurnal →  2017 →  №5 →  Назад

EXPERIENCE OF MINING AND PROCESSING TECHNOLOGY AND EQUIPMENT IMPROVEMENT AND ARRANGEMENT
Название Introduction of automated control over mining and transportation
DOI 10.17580/gzh.2017.05.20
Автор Sorokin O. I., Shokov A. A.
Информация об авторе

JSC Lebedinsky GOK, Gubkin, Russia:

O. I. Sorokin, Head of Office for Communications and Transmission Media
A. A. Shokov, Deputy Head of Office for Production and Analysis – Head of a department, shokov_a_a@lebgok.ru

Реферат

One of the factors of success of modern production is application of automated checkout and control facilities. A new step along the way of improving such equipment at Lebedinsky GOK has become the introduction of automated mining and transportation control system Dicpatch manufactured by Modular Mining Systems. The main objective of the system introduction is to increase productivity of heavy dump trucks owing to automation of their routing for loading, fueling and shift change. This is achieved through automated control over rock rehandling by motor transport, checkout of fuel quantity in tanks and tire pressure in every dump truck as well as by means of instrumentation-assisted estimation of quality of roads in the open pit mine. The automated routing is based on the mathematical calculation of optimal cargo flows in accord with the production objectives. On the ground of this calculation, the system assigns tasks for each machine and follows up the execution. For example, the system, in real time, using the downloaded optimization algorithms, after a dump truck is unloaded, automatically assigns a specific shovel for the vacant dump truck to go to. After the system introduction, the time loss, which negatively influenced equipment efficiency (downtime of machines whilst awaiting loading, idle time of shovels awaiting dump trucks, duration of fueling, etc.), has drastically been reduced. The effi ciency of dump trucks per shift has increased by 11.6%.

Ключевые слова Automation, control system, mining and transportation system, shovel, dump truck, equipment efficiency
Библиографический список

1. Trubetskoy K. N., Kuleshov A. A., Klebanov A. F., Vladimirov D. Ya. Modern systems for mining transport complexes management. Saint Petersburg : Nauka RAN, 2007. 302 p.
2. Trubetskoy K. N., Klebanov A. F., Vladimirov D. Ya. Automation of mining transport complexes management on open pits. Gornyi Zhurnal. 2009. No. 11. pp. 38–41.
3. Ilin S. A., Kovalenko V. S., Pastikhin D. V. Increasing of economic efficiency of open-cast. Gornyi Zhurnal. 2012. No. 6. pp. 56–65.
4. Pomelnikov I. I. State and prospects of iron-ore industry development with stable decrease of global iron ore prices. Gornyi Zhurnal. 2015. No. 7. pp. 78–87. DOI: 10.17580/gzh.2015.07.11
5. Nikolaev K. P. Modern history of iron ore industry on the territory of Russia and neighbouring states. Moscow : Master, 2015. 320 p.
6. Thomoson R., Hahn S., Pastor S. Development of mine haul road surfacing condition monitoring through digital image processing. Mining Engineering. 2015. Vol. 67, No. 9. pp. 34–45.
7. Green J. J., Hlophe K., Dickens J., Teleka R., Price M. Mining robotic sensors. International Journal of Engineering and Advanced Technology. 2012. Vol. 1, No. 4. pp. 8–15.
8. Brown C. Autonomous Vehicle Technology in Mining. Autonomous Mining. 2012. No. 1. pp. 30–32.
9. Frank U. Multi-perspective enterprise modeling: foundational concepts, prospects and future research challenges. Software & Systems Modeling. 2014. Vol. 13, Iss. 3. pp. 941–962.
10. Kul’ga K. S. Use of an integrated computer-based information system at chemical and oil-andgas machine production enterprises. Chemical and Petroleum Engineering. 2014. Vol. 50, Iss. 7. pp. 445–451.
11. Lee С. К. H., Choy K. L., Ho G. T. S., Lam С. H. Y. A slippery genetic algorithm- based process mining system for achieving better quality assurance in the garment industry. Expert Systems with Applications. 2016. Vol. 46. pp. 236–248.
12. Garcia S., Luengo J., Herrera F. Tutorial on practical tips of the most influential data preprocessing algorithms in data mining. Knowledge-Based Systems. 2016. Vol. 98. pp. 1–29.
13. Sengupta A., Mazumdar C., Bagchi A. A formal methodology for detecting managerial vulnerabilities and threats in an enterprise information system. Journal of Network and Systems Management. 2011. Vol. 19, Iss. 3. pp. 319–342.
14. Fayoumi A. Ecosystem-inspired enterprise modelling framework for collaborative and networked manufacturing systems. Computers in Industry. 2016. Vol. 80. pp. 54–68.
15. DISPATCH. Open-cast mining. MODULAR. Available at: http://www.modularmining.com/ru/ (accessed: 9.02.2017).

Полный текст статьи Introduction of automated control over mining and transportation
Назад