Integrated analysis of electric energy demand of autogenous grinding mills at concentration factories

The relevance of the electric energy demand calculation at concentration factories is governed by the requirement to save on electricity bills in the overall production cost. One of the most energy-hungry phases in mineral processing is grinding using autogenous mills. The aim of this study is to estimate the electric energy demand of the mills using the methods of the statistical and correlation analyses. In conformity with the aim, the scope of the research encompasses: the mill statistics analysis, the correlation of the energy consumption and productiveness of the mills, the definition of the specific energy consumption of the mills. Using the experimental research findings and the statistical design methods, the computation procedure is developed for the energy response and specific energy consumption of the autogenous grinding mills; the procedure contains the necessary and sufficient number of criterion-based checkouts of the initial statistical data, and provides the basic parameters of the statistical law, as well the estimates of the correlation coefficient and the coefficients of the linear regressional relationship between separate samplings. It is found that the productiveness and energy consumption of the autogenous grinding mills have a low correlation coefficient, which points at the weak connection between the parameters P and Q. The Student’s t-test confirms that at  = 0.05, the correlation coefficient of the productiveness Q and the specific energy consumption , and the coefficients of the linear regressional relationship are significant. For minimizing the specific energy demand, it is recommended to operate within the optimum mode range at the maximum allowable capacity of the mill at 136.5 t/h.

Klyuev R. V., Khetagurov V. N., Gavrina O. A., Plieva M. T. Integrated analysis of electric energy demand of autogenous grinding mills at concentration factories. MIAB. Mining Inf. Anal. Bull. 2023;(5-1):145-156. [In Russ]. DOI: 10.25018/0236_1493_2023_51_ 0_145.

R.V. Klyuev, Dr. Sci. (Eng.), Assistant Professor, Professor, Moscow Polytechnic University, 107023, Moscow, Russia, e-mail: kluev-roman@rambler.ru, ORCID ID: 0000-0003-3777-7203,
V.N. Khetagurov¹, Dr. Sci. (Eng.), Professor, e-mail: hetag@mail.ru, ORCID ID: 0000-0002-2151-9309,
O.A. Gavrina¹, Cand. Sci. (Eng.), Assistant Professor, e-mail: Gavrina-Oksana@yandex.ru, ORCID ID: 0000-0002-9712-9075,
M.T. Plieva¹, Cand. Sci. (Eng.), Assistant Professor, e-mail: madosya80@mail.ru, ORCID ID: 0000-0003-2633-0617,
¹ North Caucasian Institute of Mining and Metallurgy (State Technological University), 362021, Vladikavkaz, Russia.

R.V. Klyuev, e-mail: kluev-roman@rambler.ru.

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