Chemical and Metallurgical Institute named after Zh. Abishev (Republic of Kazakhstan):

Malyshev V. P., Doctor of Engineering Sciences, Professor, Head of Laboratory, eia_hmi@mail.ru

Makasheva A. M., Doctor of Engineering Sciences, Professor, Chief Researcher, eia_hmi@mail.ru

National Scientific-Technological Holding «Parasat» (Republic of Kazakhstan):
Bekturganov N. S., Academician of National Academy of Sciences of the Republic of Kazakhstan, Doctor of Engineering Sciences, Professor, Scientific Consultant

Kazakhmys Corporation (Republic of Kazakhstan):
Tokbulatov T. Ye., Head of Project Group

Zhezkazgan Concentrator (Republic of Kazakhstan)

Kravchenko V. G., Chief Preparator

E. A. Buketov Karaganda State University (Repubic of Kazakhstan)

Kaykenov D. A., Researcher

In elaboration of the probabilistic model of grinding, proposed by the authors, the new probabilistic model application for commercial mills adjustment to actual operation conditions on the basis of direct comparison of actual and calculated particle size fractions distribution of mill product is shown. The work was performed together with the staff of Chemical-metallurgical Institute (Karaganda), AO «NNT Holding Parasat» (Astana), TOO «Kazakhmys Corporation» (Zhezkazgan) and the Karaganda State University named after Ye. A. Buketov. The measurements were performed by the personnel of the Zhezkazgan Concentrating Plant 1. Hard ore from an underground mine, blended with up to 40–45 % of «Zhomart» open pit ore with hardness similar to that of Zhezkazgan ore, was processed. 3.2х3.1 MShR grate discharge mill operated in primary grinding stage in locked circuit with КСН spiral classifier. On the whole, it may be stated, that in spite of numerous disturbances in operating conditions, the probabilistic model of grinding represents grinding process realization adequately and objectively, and may be used as a performance management tool for this most complex process, and the described sequence of this model adaptation may be employed as a technique for commercial mills Computer Modeled parameter processing. Correlation of theoretical and actual data on particle size fractions distribution may be used, if required, for correction of mill operating parameters. With that, a seeming complexity of theoretical calculations may be easily overcome through their programming for computer processing within the framework of Automatic Process Control systems, available in modern production.

1. Malyshev V. P. A new aspect in the theory of ore grinding and control of this process. Obogashchenie Rud, 1995, No. 4–5, pp. 4–14.
2. Malyshev V. P., Turdukozhayeva (Makasheva) A. M., Kaykenov D. A. Ore grinding theory development on the basis of molecular approaches Obogashchenie Rud, 2012, No. 4, pp. 29–35.
3. Malyshev V. P., Turdukozhayeva A. M. Equilibrium self-organizing of nanoscale clusters of solid phase in fluid. Entsiklopediya Inzhenera-Khimika = Encyclopaedia of Chemical Engineer, 2009, No. 4, pp. 2–8.
4. Malyshev V. P., Bekturganov N. S., Turdukozhayeva A. M., Kaykenov D. A. Effect of different size balls and their mixture upon grinding of materials. Obogashchenie Rud, 2013, No. 6, pp. 32–35.
5. Abramov A. A. Sobraniye sochineniy (Collected Edition). Vol. 1. Obogatitelnyye protsessy i apparaty (Beneficiation processes and devices). Moscow, Gornaya Kniga, 2010, 470 p.