A generic software platform for performance monitoring of deep-level mine systems

MEng (Computer and Electronic Engineering), North-West University, Potchefstroom CampusSystems of a deep-level mining operation are integral to the working of a mine. These systems help with water reticulation, compressed air, and energy used for mining minerals. A mine relies on these capital-intensive systems for the health and safety of employees and the mining of minerals. As the mine deepens to mine more minerals, these systems become more complex and expensive to operate and more difficult to maintain. This leads to the need to monitor deep-level mining systems to ensure the optimal efficiency operation of these mining systems. Personnel are often responsible for several systems and projects. This can influence decision making and more informed decisions due to the amount of data that needs to be analysed. In this study, performance monitoring of deep-level mines will be investigated to develop a generic software platform for performance monitoring of various deep-level mining systems that will reduce the cognitive overload of Big data that needs to be analysed for decision making to increase a mine’s profit margins. For this study, a software platform was designed and implemented to monitor the performance of energy efficiency initiatives implemented by an ESCo. The performance of multiple systems on various deep-level mines can be monitored with ease by personnel when using the platform. By using the performance monitoring software platform, personnel are able to monitor the performance of initiatives on deep-level mining systems on a multi-level overview. Each initiative’s data can be viewed in detail to improve problem identification of initiatives that are performing poorly. By monitoring the performance of mining systems and improving the efficiency of these systems, a combined estimated cost saving of R 8.6 million per annum is achievable for the case studies that were presented. A total of 105 initiatives for deep-level mining systems’ performance monitoring were configured, that enabled personnel to monitor multiple systems’ performances without the need to process and analyse data. The performance monitoring software platform enabled personnel to reduce system data analysis time between 60 and 70%. The objectives of the study were achieved by the development of a software platform for performance monitoring that enabled ESCo and mine personnel to monitor the day-to-day performance of implemented initiatives on deep-level mining systems.Master