Scientific and Design Association “RIVS”, Saint-Petersburg, Russia:

А. М. Arustamyan, Chief Project Engineer, A_Arustamyan@rivs.ru

Navoi Mining and Metallurgy Plant, Navoi, Uzbekistan:
K. S. Sanakulov, General Director, Doctor of Engineering Sciences

The authors emphasize the demand for new approaches to evaluation of mineral beneficiation efficiency based on the methods of in-depth statistics. The domestic and international experience gained in this research area is analyzed. It is found that the data of laboratory and full-scale studies on flotation are commonly interpreted using the methods of classical descriptive statistics with disregard of the modern mathematical apparatus of in-depth statistics, which degrades reliability of determination of interrelation between parameters of an object under study. The application of the harmonic analysis of flotation processes at Talnakh, Pyukhasalmi and Zyryanovskaya processing plants and in laboratory investigation of copper ore from Udokan deposit is exemplified. It is shown that it is most efficient to apply the method of harmonic analysis to periodic processes connected with circulation flows of pulp slurry, variation of operating conditions, operation of automatic control systems and variation of types of batch mixture under treatment.

1. Chanturiya V. A., Bocharov V. A. Modern state and basic ways of technology development for complex processing of non-ferrous mineral raw materials. Tsvetnye Metally. 2016. No. 11. pp. 11–18. DOI: 10.17580/tsm.2016.11.01
2. Chanturiya E. L., Chanturiya V. A., Zhuravleva E. S. Prospects of application of water preparation of electrochemical technology in copper-zinc ores flotation. Tsvetnye Metally. 2016. No. 1. pp. 13– 19. DOI: 10.17580/tsm.2016.01.02
3. Electronic tutorial on statistics. StatSoft. Available at: http://statsoft.ru/home/textbook/default.htm (accessed: 28.03.2015).
4. Gritsenko V. A., Belosevich E. V., Artishcheva E. K. Mathematical methods in geography : tutorial. Kaliningrad : Kaliningradskiy universitet, 1999. 75 p.
5. Borovikov V. P., Ivchenko G. I. Forecasting in the system STATISTICA in Windows. Electronic theory basis and intensive practice : tutorial. Moscow : Finansy i statistika, 2000. 384 p.
6. Borovikov V. P. Art of electronic analysis of data: for professionals. Second edition (+CD). Saint Petersburg : Piter, 2003. 688 p.
7. STATISTICA Neural Networks: Methodology and technologies of modern analysis of data. Ed.: V. P. Borovikov. Second edition, revised and enlarged. Moscow : Goryachaya liniya – Telekom, 2008. 392 p.
8. Bocharov V. A., Ignatkina V. A., Khachatryan L. S. About the separation of minerals of massif pyritepyrrhotite ores of non-ferrous metals. Resource-saving and protection of environment during the concentration and processing of mineral resources (Plaksin readings-2016): materials of International conference, 26–30 September 2016. Ed.: V. A. Chanturiya. Moscow : “Ore and Metals” Publishing House. pp. 97–99.
9. Mashevskiy G. N., Petrov A. V., Romanenko S. A., Sufyanov F. S., Balmanova A. Zh. A new approach to regulating the process of sulfide minerals selective flotation separation from pyrite in lime medium. Obogashchenie Rud. 2012. No. 1. pp. 12–16.
10. Petrov A. V., Romanenko S. A., Sufyanov F. S., Balmanova A. Zh. Regulation of copper sulfides separation from pyrite in lime medium in flotation process by pulp electrochemical potential. Obogashchenie Rud. 2012. No. 2. pp. 40–42.
11. Mashevskiy G. N., Petrov A. V., Romanenko S. A., Sufyanov F. S. Development of ore types processing classification principles on the basis of flotation process parameters control and neural network modeling. Obogashchenie Rud. 2012. No. 4. pp. 36–42.
12. Romanenko S. A. Effectiveness of multisensor ionometry systems and neural network modeling methods application in flotation processes laboratory studies. Obogashchenie Rud. 2013. No. 1. pp. 18–22.
13. Mashevskiy G. N., Romanenko S. A. Copper-pyrite ores flotation cleaning cycle mathematical model. Obogashchenie Rud. 2014. No. 4. pp. 27–33.
14. Arustamyan K. M., Romanenko S. A. Reclaimed water treatment for production data improvement in terms of Nikolaevskaya Processing Plant. Gornyi Zhurnal. 2016. No. 11. pp. 60–64. DOI: 10.17580/gzh.2016.11.11
15. Arustamyan K. M., Romanenko S. A., Arustamyan A. M. Using potentiograms in assessment of process properties of copper ore in terms of Zhezkazgan deposit. Gornyi Zhurnal. 2016. No. 11. pp. 65–70. DOI: 10.17580/gzh.2016.11.12
16. Ignatkina V. A. Selective reagent regimes of flotation of non-ferrous and noble metal sulfides from refractory sulfide ores. Tsvetnye Metally. 2016. No. 11. pp. 27–33. DOI: 10.17580/tsm.2016.11.03
17. Korobeynikov A. F. Forecasting and searches of mineral deposits : tutorial for universities. Second edition, revised and enlarged. Tomsk : Izdatelstvo Tomskogo politekhnicheskogo universiteta, 2009. 253 p.
18. Heikkinen S., Mashevskiy G. N. Algorithmic base for flotation control. Obogashchenie Rud. 2005. No. 6. pp. 32–37.
19. Veki L. The use of seawater as process water in concentration plant and the effects on the flotation performance of Cu-Mo ore. Master’s thesis Degree Programme of Process Engineering. OULUN YLIOPISTO, 2013. 117 p.
20. Boujounoui K., Abidi A., Bacaoui A., Amari K. E., Yaacoubi A. The influence of water quality on the flotation performance of complex sulphide ores: case study at Hajar Mine, Morocco. The Journal of The Southern African lnstitute of Mining and Metallurgy. 2015. Vol. 115. pp. 1243–1251.
21. Mashevskiy G. N., Heikkinen S., Isokangas A. New system of computer modeling of flotation process. Obogashchenie Rud. 2007. No. 1. pp. 45–48.