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The authors introduce the fossil coal classification in terms of useful quality of coal, by using the facet method and the qualimetry principles, in terms of the power-generating coal from the Kuznetsk Coal Basin and coking coal from Southern Yakutia. The new-proposed classification completes the existing classifications on the topic, and describes the full range of coal quality indexes according to a consumer and their significance in the final product quality evaluation.

In working coal deposits, it has become important to control the quality, especially in extracting coking coals. As a rule, coking coals have inhomogeneous petrographic composition, variable ash content, and very variable technical properties. This is clearly seen in Fig. 1, which is a plot of the main indices of the quality of coking coals -the ash content A c and the plastic layer thickness Y -of the extraction blocks along the extraction front of the Moshchnii seam of the Neryungrinskii deposit.The value of the commercial product is primarily determined by the values of Y and A c in the coal concentrate. However, during concentration the plastic properties of the coals remain almost unaltered, and therefore improvement and stabilization of the coal quality according to this index must be wholly effected during extraction and preparation of the coal.Quality control of won coal aims at obtaining mean values of the quality indices within the permissible ranges, at stabilizing the mean values over the periods of operation of the extraction subsystem, and at smoothing the variations of the particular values of the index relative to the mean.The first two methods of quality control are mainly effected during extraction operations by using the following forms of organization of the technical processes : iii) Compiling a timetable of arrivals of transport units from the face at the discharge stations.In this connection, planning of the operational indices of the extraction subsystem can be regarded as a search for the optimal values of the parameters of the forms of organization enabling us to attain the highest coal quality level in the successive stages of the coal extraction technology. Let us consider the solution of these problems, taking as an example the following organization of the extraction and blending technology.A pit contains n extraction faces. The coal from each face arrives in the form of a discrete flowformed by the coal trucks with carrying capacity q. The won coal arrives at the receiving pits of the technical coal preparation complex for processing; the following processes are involved: crushing, screening, and storage in three silo-type bunkers. The capacity of each bunker is equal to the output of the mine in one shift. The construction of the bunkers involves forced bulk flow of coal through hoppers uniformly distributed over the base.The technical scheme will be used as an example to make a mathematical analysis of the transformation of the magnitudes of the quality indices during the processes of extraction and coal preparation, taking one of the quality indices as an example.Let Yij be a random variate characterizing the index being monitored in the j-th coal truck from the i-th face. -We will ass _u~ne that for each value of i, the series Yij, J =1, 2 .... , is a stationary random process with expectation value Yi and dispersion ~i 2 =a2(Yi ), and also that low-frequency harmonics predominate in the spectral expansion of the correlation function of each initial random process. When we intro...

Topicality, concept, principles and tool of the robust control in open pit mining are given. It is shown that each stage of the product quality control must have permissible range of fluctuation for coal properties, loading equipment capacity and work area limits in open pit mines. The goal and capabilities of the robust control is the stable operation of the production system within the set limits and constraints. The article presents methodology and implementation tool for the robust control in open pit coal mines.

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