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Data Analytic Approaches for Mining Process Improvement—Machinery Utilization Use Case

机译:采矿过程改进机械利用用例的数据分析方法

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This paper investigates the application of process mining methodology on the processes of a mobile asset in mining operations as a means of identifying opportunities to improve the operational efficiency of such. Industry 4.0 concepts with related extensive digitalization of industrial processes enable the acquisition of a huge amount of data that can and should be used for improving processes and decision-making. Utilizing this data requires appropriate data processing and data analysis schemes. In the processing and analysis stage, most often, a broad spectrum of data mining algorithms is applied. These are data-oriented methods and they are incapable of mapping the cause-effect relationships between process activities. However, in this scope, the importance of process-oriented analytical methods is increasingly emphasized, namely process mining (PM). PM techniques are a relatively new approach, which enable the construction of process models and their analytics based on data from enterprise IT systems (data are provided in the form of so-called event logs). The specific working environment and a multitude of sensors relevant for the working process causes the complexity of mining processes, especially in underground operations. Hence, an individual approach for event log preparation and gathering contextual information to be utilized in process analysis and improvement is mandatory. This paper describes the first application of the concept of PM to investigate the normal working process of a roof bolter, operating in an underground mine. By applying PM, the irregularities of the operational scheme of this mobile asset have been identified. Some irregularities were categorized as inefficiencies that are caused by either failure of machinery or suboptimal utilization of the same. In both cases, the results achieved by applying PM to the activity log of the mobile asset are relevant for identifying the potential for improving the efficiency of the overall working process.
机译:本文调查了过程采矿方法在采矿业务中的移动资产过程中的应用,作为确定提高此类运营效率的机会的手段。工业4.0相关广泛数字化的工业流程的概念使得收购能够并且应该用于改善流程和决策的大量数据。利用此数据需要适当的数据处理和数据分析方案。在处理和分析阶段,最常是应用广泛的数据挖掘算法。这些是以数据为导向的方法,无法映射过程活动之间的原因效果关系。然而,在此范围内,越来越强调了导向过程的分析方法的重要性,即处理挖掘(PM)。 PM技术是一种相对较新的方法,它能够基于来自企业IT系统的数据构建过程模型及其分析(数据以所谓的事件日志的形式提供)。具体的工作环境和与工作过程相关的多种传感器导致采矿过程的复杂性,特别是在地下操作中。因此,必须在过程分析和改进中用于参与待使用的事件日志准备和收集上下文信息的个人方法是强制性的。本文介绍了PM概念的第一次应用,以研究屋顶螺栓的正常工作过程,在地下矿井中运行。通过申请PM,已经确定了该移动资产的运营方案的不规则性。一些不规则性被分为效率低下,这是由机械或其次优不同的失败引起的。在这两种情况下,通过将PM施加到移动资产的活动日志所实现的结果对于提高整体工作过程效率的潜力是相关的。

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