Applying Sensor-Based Information Systems to Identify Unplanned Downtime in Mining Machinery Operation

Area of Science:

• Mining Engineering
• Industrial Automation
• Information Technology

Background:

• Underground mining is complex, with environmental conditions and unplanned machine downtime posing significant challenges.
• Modern mining operations increasingly rely on sophisticated machinery, making downtime a critical issue impacting productivity.
• Existing methods for tracking downtime are often subjective and lack detailed cause identification.

Purpose of the Study:

• To develop and present a methodology and IT system for objective recording of mining machine downtime.
• To identify the root causes of unplanned interruptions in mining machinery operation.
• To improve the utilization efficiency of mining machinery through data-driven insights.

Main Methods:

• Implementation of a sensor-based information system to register mining machinery parameters.
• Utilizing an industrial automation system and SCADA system for continuous, operator-independent data acquisition.
• Development of an IT application within an ERP system to analyze registered data and identify downtime causes.

Main Results:

• The developed system enables objective registration of machine downtime.
• The IT tool successfully identifies the causes of most recorded machine interruptions.
• Application to a shearer loader demonstrated the system's potential for improving machinery utilization.

Conclusions:

• The proposed methodology and IT system provide a robust solution for managing mining machine downtime.
• Objective data acquisition and cause identification lead to enhanced machinery performance.
• The system offers significant potential for improving overall mining production efficiency.