Technical science/4.Transport

d.t.s., professor Kadyrov A. S.

Kyzylbaeva E. Zh.

Kukesheva A.B.

Karaganda State Technical University, Kazakhstan

Analysis of technical and economic indicators of quarry vehicles operation in "Shubarkol Komir" JSC

One of the main processes in the general technological complex of conducting open pit mining is transportation of minerals and overburden with heavy-duty dump trucks. Therefore, the most resource intensive in open pit mining is quarry vehicles, which accounts for up to 70% of costs associated with the extraction of minerals.

Intensive and timely renewal of the dump truck fleet is currently determined by economic criteria, as in the practice of coal mines the total operating costs for the service life are often 8-10 times higher than the initial cost of the car, which negatively affects the cost of transportation [1].

The current state of mining operations and basic mining equipment, the performance factors of quarry vehicles in the conditions of "Shubarkol Komir" JSC served as the starting point for research on the re-equipment of quarry vehicles, as the variety of used models of dump trucks creates certain difficulties in their operation, maintenance, repair, and also in material and technical supply.

When choosing a quarry vehicles model, it is desirable to take into account the capital and operating costs, reliability, the capabilities of the production and technical base, the actual service life, safety and performance of the machines in specific operating conditions, environmental and ergonomic indicators. Consequently, the choice of the most efficient quarry vehicles is a multifactorial, multicriteria, rather complex problem.

As technical and economic indicators of heavy vehicles in the conditions of the Central mine of "Shubarkol Komir" JSC, in this work: accumulated running time of dump trucks (X1); traffic volume (X2); freight turnover (X3); total mileage (X4); transportation cost (X5); machine hours in operation (X6), in conservation (X7), in current maintenance (X8). As an additional feature, were considered the number of actually used dump trucks of each brand for the under study period (X9).

Due to the large number of different models (domestic and imported) of dump trucks operating in the Neryungrinsky coal mine, in order to apply multiple correlation regression analysis to determine the cost of transportation as a function of many variables, it is required to find out whether the technical and economic performance of dump trucks varies significantly depending on the brand. In other words, with the help of the variance analysis it is required to establish whether significantly or insignificantly differs the sample averages of the surveyed indicators by brands of dump trucks, and if it is established that the factor has a significant effect on the studied value of X, it is necessary to find out which of the levels of the factor has the greatest impact.

The basic idea of the variance analysis is to compare the "factor dispersion" generated by the effect of the factor and the "residual variance" specified to random causes. If the difference between these variances is significant, then the factor has a significant effect on X, in which case the averages of the observed values at each level differ also significantly. All the quantitative signs X1-X9, which are normally distributed random variables, are affected by the factor F - quarry vehicles, which has 12 constant levels (F1, ..., F12) - the number of brands of dump trucks. At each level were produced 4 tests.

Thus, at the level of significance α = 0.05, it is required to test the null hypothesis on the equality of group averages under the assumption that the group general variances are the same. To solve this problem, we introduce: the total sum of the squares of the deviations of the observed characteristic values from the total average S total, the factor sum of the squares of the deviations of the group averages from the total average S fact, the residual sum of squares of the deviations of the observed values of the group from its group average S residual. Then the factorial (2 fact S) and the residual (2 residual S) variances are found as the ratio of the respectively calculated factorial and residual sums to the corresponding number of degrees of freedom (m1 = 11, m2 = 36).

Comparing the factorial and residual variance by the Fisher-Snedekor criterion, we obtain one of the conclusions: if F observation<F critical, then the difference in group averages is insignificant, if F observation> F critical, then the difference in group averages is significant. The results of the variance analysis in terms of characteristics X1 - X9 at F critical = 2.07 are shown in the table.

From the table we have that the group averages differ significantly in terms of such indicators as accumulated running time, freight turnover, total mileage, cost of transportation, machine hours in operation, number of dump trucks, i.е. studies involving these characteristics should preferably be carried out taking into account the brands of dump trucks. In addition, the shares of the influence of the controlled factor on the characteristics under study are low, with the exception of the "cost of transportation" characteristic; most of it is due to the residual balance of random errors of totality. The results obtained should be taken into account when performing the correlation-regression analysis, as well as when developing recommendations for improving the performance of quarry vehicles in the conditions of this field.

References

1. Vasil’ev M.V., Smirnov V.P., Kuleshov A.A. Jekspluatacija kar'ernogo avtotransporta [Exploitation of quarry vehicles] Moscow, Nedra, 1979, 280p.