Implementation of business intelligence system to analyze the data for mining mechanization – case study

IF 2.2 4区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Acta Montanistica Slovaca Pub Date : 2022-12-08 DOI:10.46544/ams.v27i3.14

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Abstract

In this article, we focused on the experimental implementation of the Power BI application in the field of mining mechanization. This application was created to demonstrate how an interactive data visualization tool can streamline data exploration and provide new insights that can be used to optimize selected processes. The monitored company uses a large number of reports in connection with the organization of the company. They collect many data from the attendance system and the electronic resource planning system, but also a lot of operational data related to the performance of mining mechanization. These data are evaluated in the company only at one-month intervals. Our intention was to transform the data for the year 2021 and create various visual reports through the power BI program, which, thanks to detailed analysis and evaluation, will help to improve the management of mining mechanization. The source of information in our case were tables that contained very poorly arranged data that could not be imported into the Power BI program in the given state. After collecting the data, we had to transform them, which was a very time-consuming process. Due to limited resources, we had to adjust our original plan. From the entire portfolio of mining mechanization, which consists mainly of mining drills, loaders and trucks, we decided to only process data from mining trucks. The result will be a demonstration of the usability of the power BI system in a mining company to manage information related to mining trucks, but the same approach can be used for all types of mining mechanisms. Implementation of the power BI system was performed on data from one of the biggest underground mines in Slovakia.

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实现商业智能系统对采矿机械化数据的分析——案例研究

在本文中，我们重点研究了Power BI应用在采矿机械化领域的实验实现。创建此应用程序是为了演示交互式数据可视化工具如何简化数据探索，并提供可用于优化选定流程的新见解。受监控的公司使用大量与公司组织相关的报告。他们从考勤系统和电子资源规划系统中收集了许多数据，但也收集了许多与采矿机械化性能相关的操作数据。公司仅每隔一个月对这些数据进行评估。我们的意图是转换2021年的数据，并通过power BI计划创建各种可视化报告，通过详细的分析和评估，这将有助于改善采矿机械化的管理。在我们的案例中，信息源是包含排列非常糟糕的数据的表，这些数据在给定状态下无法导入Power BI程序。收集数据后，我们必须对其进行转换，这是一个非常耗时的过程。由于资源有限，我们不得不调整原来的计划。从主要由采矿钻机、装载机和卡车组成的整个采矿机械化组合来看，我们决定只处理采矿卡车的数据。其结果将证明采矿公司的电力BI系统在管理与采矿卡车相关的信息方面的可用性，但相同的方法可用于所有类型的采矿机制。电力BI系统的实施是根据斯洛伐克最大的地下矿山之一的数据进行的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Acta Montanistica Slovaca 地学-地球科学综合

CiteScore

3.60

自引率

12.50%

发文量

审稿时长

30 weeks

期刊介绍： Acta Montanistica Slovaca publishes high quality articles on basic and applied research in the following fields: geology and geological survey; mining; Earth resources; underground engineering and geotechnics; mining mechanization, mining transport, deep hole drilling; ecotechnology and mineralurgy; process control, automation and applied informatics in raw materials extraction, utilization and processing; other similar fields. Acta Montanistica Slovaca is the only scientific journal of this kind in Central, Eastern and South Eastern Europe. The submitted manuscripts should contribute significantly to the international literature, even if the focus can be regional. Manuscripts should cite the extant and relevant international literature, should clearly state what the wider contribution is (e.g. a novel discovery, application of a new technique or methodology, application of an existing methodology to a new problem), and should discuss the importance of the work in the international context.