Abstract
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.
Highlights
Introducing digitalization to the mining industry provides opportunities to improve productivity [1].The acquisition of large amounts of machine data allows obtaining a more complete picture and in-depth knowledge of the efficiency in which processes are carried out
The results achieved by applying process mining (PM) to the activity log of the mobile asset are relevant for identifying the potential for improving the efficiency of the overall working process
Business Process Management (BPM) has received considerable attention in recent years due to its potential for significantly increasing productivity and saving costs [29]. This discipline can be seen as an alignment of Information Technology (IT) infrastructure with current organizational demands of process improvement [30]
Summary
Introducing digitalization to the mining industry provides opportunities to improve productivity [1].The acquisition of large amounts of machine data allows obtaining a more complete picture and in-depth knowledge of the efficiency in which processes are carried out. Decision-making can be supported, and indications for processes efficiency improvement identified [2]. Mining companies aspire to continuously improve processes to increase the operational efficiency and safety of their personnel. Mining processes are characterized by very demanding and complex activities due to the challenging physical aspects (heat, cold, vibrations, noise) and the unpredictable conditions of work. In such environments, human errors, and defective equipment, as well as natural hazards, are serious risk factors. Risks in mining operations arise from the use of heavy equipment and the occurrence of different types of energy (electrical, mechanical, other), which holistically
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