Review of Key Performance Indicators for Process Monitoring in the Mining Industry

Abstract

The sustainable development of an organisation requires a holistic approach to the evaluation of an enterprise’s goals and activities. The essential means enabling an organisation to achieve goals are business processes. Properly managed, business processes are a source of revenue and become an implementation of business strategy. The critical elements in process management in an enterprise are process monitoring and control. It is therefore essential to identify the Key Performance Indicators (KPIs) that are relevant to the analysed processes. Process monitoring can be performed at various levels of management, as well as from different perspectives: operational, financial, security, or maintenance. Some of the indicators known from other fields (such as personnel management, finance, or lean manufacturing) can be used in mining. However, the operational mining processes require a definition of specific indicators, especially in the context of increasing the productivity of mining machines and the possibility of using sensor data from machines and devices. The article presents a list of efficiency indicators adjusted to the specifics and particular needs of the mining industry resulting from the Industry 4.0 concept, as well as sustainable business performance. Using the conducted research and analysis, a list of indicators has been developed concerning person groups, which may serve as a benchmark for mining industry entities. The presented proposal is a result of work conducted in the SmartHUB project, which aims to create an Industrial Internet of Things (IIoT) platform that will support process management in the mining industry.

Modern Solution for Fast and Accurate Inventorization of Open-Pit Mines by the Active Remote Sensing Technique—Case Study of Mikoszów Granite Mine (Lower Silesia, SW Poland)

“…The measurements from both systems provide data for developing a digital representation (the so-called Digital Twin) of the geometry of a mining excavation, which may be used over the mine life cycle in such applications as monitoring the exploitation state of the mining excavation, performed in the form of cyclical measurements in order to control and optimize (improve) the efficiency of the mining process, constructing a management model of an active or a closed excavation, providing information about the state of the closed excavation and constructing its revitalization model. The methods here proposed allow quick access to the excavation-related data with a minimum workload required from an operator to acquire and process the data and, as such, they reflect well the principles of Industry 4.0 [21][22][23][24][25].…”

Development of a measurement instrument to evaluate integrated management systems and differences in perception: an approach to item response theory and the quality management process

“…Typically, operational performance is measured by Key Performance Indicators (KPIs), which allow process evaluations by comparing practical performance (actual) versus the programmed target (estimated) (Parmenter, 2015;Peral et al, 2017). To this end, works such as (Gackowiec et al, 2020) reviewed the KPIs used for monitoring processes in the mining industry, classifying them into different dimensions (technical, temporal, spatial, safety and maintenance) for different groups of people (superintendent, shift supervisor, operator, and maintenance manager). Otherwise, considering the series of standards (International Organization for Standardization, 2014aStandardization, , b, 2017Standardization, , 2018 that specify the main KPIs used in manufacturing operations management, (Kang et al, 2016) presents a framework of relationships between KPIs and their supporting elements, and (Bhadani et al, 2020) analyzes KPIs for aggregate production using dynamic simulation.…”

“…In the context of Industry 4.0, technological development aims to enable the acquisition of measurable process parameters and acquisition of information directly from the equipment, thus being the process capable of integrating multiple devices into an integrated system, collecting data from the entire infrastructure and environment, as well as improved measurement and management of the mine's spatial and intertemporal compliance with the plan in open-pit mines in a holistic and integrated manner (Gackowiec et al, 2020;Otto & Musingwini, 2020).…”

Evaluation of Data-Driven Decision-Making Implementation in the Mining Industry

“…• Gackowiec et al [22] state that data collection is the starting point for implementing improvements at all levels of management in an organisation.…”