Using Statistical Methods to Assess Indicators Impacting Coal Ash Content for Underground Mining

Abstract

This article dwells upon the improvement of coal ash content management efficiency for underground mining, which can help increase the efficiency of coal mining companies. The authors demonstrate that statistical methods are best suited for determining the key factors impacting the ash content of the produced coal. The authors selected the statistical methods to help solve the stated problems. To analyze the factors increasing the ash content of the coal mined underground, the authors used the Ishikawa method to identify problems and their causes. They used the expert method and ranked experts’ assessments obtained to select the most significant indicators in terms of their impact on the ash content of the coal mined underground for each of the indicator groups established. To select the most significant indicators, the authors used the Pareto method and ABC-analysis. As a result, they obtained indicator categories. The subsequent analysis within each of the categories helped formulate homogeneous indicator groups and select the ones that have the highest impact on the ash content of the coal produced underground. The set of the statistical methods used helped identify five indicators that have the greatest impact on the ash content of the coal produced in underground mines. These include the total thickness of intermediate rocks, mining face length, the operating width of the combine actuator, shear thickness, and bed thickness. These can be used to form an ash content management system for underground coal mining.