INVESTIGATION OF THE RANDOM VALUE STATISTICAL DISTRIBUTIONS MODELS CHOICE INFLUENCE ON THE MINING OPERATIONS MODELING RESULTS

A. Zatonskiy, P. A. Yazev
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Abstract

The importance of production planning for improving the performance indicators of a mining enterprise is indicated. The possibility of simulation modeling using for this aim is shown. It is shown that the created model has a large number of stochastic parameters. It is investigated that there is a problem of research lack about the choice influence of the mining modeling results with different statistical distributions. It is known that with an increase in stochastic deviations from the initial parameters, the productivity of queuing systems decreases. Purpose of work is to study this influence with four statistical distributions of a random quantity (uniform, normal, negative bi-nomial and Poisson distribution) for individual operations and their combinations. In addition, it is necessary to determine how much a change in one particular parameter will affect the overall result of the modeling. Materials and methods. In the previously created simulation model, a stochastic delay is added to the time of individual operations. The addition of such a delay with different sta-tistical distributions and with the same mathematical expectation is investigated. The simulation re-sults are compared with each other, for each individual operation the absolute and relative devia-tion of the results is shown. Further, a similar simulation is performed when all the simultaneously selected parameters changing. Result. It is shown that the magnitude of the deviation significantly differs among all deviations. It is shown that for various single changes in operations, the largest and smal-lest deviations can be given by different statistical distributions. To study the joint change with all parameters, 3 modeling scenarios are implemented: all uniform distributions (this case is used now), the scenario with the smallest deviation and the scenario with the largest deviation. It is shown that switching to another scenario leads to a significant change in the simulation. Conclusion. It is con-cluded that the used significant influence of statistical distributions choice to the accuracy of model-ing the operation of the mining machine is shown, especially when they are taken into account to-gether. The results can be used to clarify the influence of individual factors in the simulation model and improve the planning of potash mining operations, for individual mining machines too.
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研究了随机值统计分布模型的选择对采矿作业建模结果的影响
指出了生产计划对提高矿山企业绩效指标的重要性。说明了为此目的进行仿真建模的可能性。结果表明,所建立的模型具有大量的随机参数。研究了不同统计分布对采矿建模结果选择影响的研究不足问题。众所周知,随着与初始参数的随机偏差的增加,排队系统的生产率降低。工作的目的是用随机数量的四种统计分布(均匀分布、正态分布、负双项分布和泊松分布)对单个操作及其组合研究这种影响。此外,有必要确定一个特定参数的变化会对建模的总体结果产生多大的影响。材料和方法。在之前创建的仿真模型中,在单个操作的时间上添加了随机延迟。研究了具有不同统计分布和相同数学期望的时滞的附加问题。对模拟结果进行了比较,给出了每个单独操作结果的绝对偏差和相对偏差。此外,当所有同时选择的参数发生变化时,进行了类似的模拟。结果。结果表明,在所有偏差中,偏差的大小有显著差异。结果表明,对于各种单一的操作变化,可以用不同的统计分布给出最大和最小偏差。为了研究所有参数的联合变化,实现了3种建模场景:全均匀分布(现在使用这种情况)、偏差最小的场景和偏差最大的场景。结果表明,切换到另一个场景会导致模拟发生重大变化。结论。结果表明,统计分布的选择对矿机运行建模的准确性有显著影响,特别是在两者同时考虑的情况下。研究结果可用于阐明模拟模型中个别因素的影响,并可用于改进单个矿机的钾肥开采作业规划。
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