DOI: 10.18503/1995-2732-2021-19-4-5-15
Abstract
Problem Statement (Relevance). The current stage of global mining industry development is determined by a number of key factors in achieving high technical and economic performance, namely a comprehensive solution of theoretical and applied problems in the mining sector, in the context of implementing the main approaches to Industry 4.0. In terms of economic performance and the relative feasibility of safe extraction of raw materials, the open-pit mining method will remain promising for the near future. The statistical data analysis of mining transport equipment operation at mining enterprises of the Russian Federation and scientific and technical literature has defined that there are no significant changes in idle time reduction for the basic technological equipment. A reduction in failures and, consequently, downtime can be achieved, apart from the renovation and optimisation of the equipment fleets, by implementing the system, reducing the percentage of mining transport equipment breakdowns to minimum, at mining enterprises. Objectives.The study seeks to justify the use of predictive analytics tools to minimise failures of mining transport equipment. Methods Applied. To establish reliability indexes of open-pit excavators operated at mining enterprises of the Ural Federal District, the authors used the reliability theory methodology was used, in particular, the procedure for calculating reliability indexes of non-redundant systems and methods of predictive analytics. Originality.The authors have shown that how predictive analytics methods and tools could be applied to decrease failures of mining transport machines. Result. A failure tree structure, including a graphological scheme, has been developed for a crawler excavator in open-cast mining. Practical Relevance. Forecasting remains a necessary step for prevention of mining transport equipment failures. Introduction of a modern efficient system to forecast the changes in the equipment state is a key tool used to minimize idle time of mining equipment, increase equipment service life, and reduce the equipment maintenance cost at mining enterprises.
Keywords
Mining, predictive analytics, open-pit excavator, equipment, failure, element.
For citation
Velikanov V.S., Musonov O.S., Panfilova O.R., Ilina E.A., Dyorina N.V. Predictive Analytics Tools in Minimising Mining Equipment Failures. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnicheskogo Universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2021, vol. 19, no. 4, pp. 5–15. https://doi.org/10.18503/1995-2732-2021-19-4-5-15
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