Developing an integrated information system to assess the operational condition of deep level mine equipment

Abstract

Deep gold and platinum mines in South Africa are under pressure to remain profitable. These mines typically operate at depths of more than 2 km below surface. Complex systems are used to supply the underground operations with cold water, compressed air and ventilation. The operational condition of these systems has an impact on the mine's production, as well as the safety of the underground workers. It is therefore vital to avoid any unnecessary operational and capital expenditures. Equipment maintenance is one area where deep mines can realise financial savings. Research has shown that preventative maintenance is an effective strategy to improve equipment reliability. Maintenance costs can be reduced by preventing breakdowns and by avoiding major repairs. Mines therefore need to consider a condition-based maintenance (CBM) strategy to lower operational costs, reduce the risk of equipment failure and promote underground safety. CBM can be performed by continuously evaluating the operational condition of equipment. Considering the procurement and installation cost of commercial monitoring systems, the current solutions are not feasible. It is also not feasible to manually inspect or analyse the data of the mine's entire inventory of assets on a regular basis. An innovative methodology was developed to provide maintenance supervisors with information that is summarised and easy to interpret. An automated system, based on the new methodology, was developed to make use of available data and infrastructure to avoid additional capital expenditures. The information system was implemented on six mining sites. Data from remote servers (located on site) was sent to a centralised server to be processed. Daily exception reports provided multiple stakeholders with information regarding operational risks. An online platform was used to provide users with remote access to the risk notifications. The platform also displayed live parameter profiles that were updated every 30 minutes. Two case studies were compiled to document the measured results. Between these two case studies more than one million data samples were analysed per month. The analysis drastically reduced the time it took to locate unsound equipment behaviour. On average, maintenance personnel only needed to evaluate 6% of the input parameters that were identified as exceptions, or possible risks. Where maintenance was performed, the average number of exceptions was reduced from 61 to 25 during the first month. A further reduction to an average of nine exceptions per month was observed during the following four months. The information system improved the operational awareness on the mine and within the corporate structure of the mining group's management. The notifications that were generated by the information system, were incorporated into the mine's maintenance strategy. It was concluded that operational costs and risks can be lowered by integrating CBM with the existing scheduled maintenance.