By consolidating data into a managed data environment, an enterprise mining information system can unlock data and metrics across functional areas for a complete view of mine productivity and profitability and global analytics necessary for decision makers in planning, operations and finance, writes Nathan Pugh, Business Area Director, Mining, Trimble
Safe and profitable mining requires innovative solutions to reduce hazards and to fully optimise resources. Today’s economic pressures and volatile markets have forced mining companies to find solutions to correct inefficiencies and reduce losses in every part of their operations, which spurs innovation by necessity. Geospatial professionals with engineering and design firms have long had a traditional role in pre-mining stages of surveying, exploration, land rights management, environmental impact assessment, and construction. Chief mine surveyors continue these ongoing activities during the mine’s decades of production.
However, there are other areas of rapidly evolving technologies in the production environment that are growth opportunities for geospatial technology and experts: Mine management systems that measure, monitor report and analyse data and remote control and automation systems that replace manual operations. Both of these areas require geospatial data and expertise.
Mine management systems focused in functional areas
Various types of mine management systems survey, measure, monitor, report and analyse data for more effective management of processes and resources. This is the domain of remote sensing, remote imaging, processing and visualisation software that report data that is actionable by mine supervisors. Mine management systems are widely adopted by large-scale mining operations in the highest priority areas for safety and productivity — capital intensive, mobile and hazardous haulage operations. Fleet management systems, vehicle health monitoring systems, truck spotting systems, operator fatigue monitoring systems, and collision avoidance systems are all geared to reduce risk to operators and ground personnel, keep schedules to plan, reduce maintenance and repair costs of machines, and enable the mine to optimise the performance and investment in its resources. These systems are built on a technology infrastructure requiring positioning and wireless communications.
Other types of mine management systems that employ spatial technologies include slope stability monitoring systems using various combinations of laser, radar, geotechnical, and GNSS technology and environmental monitoring systems for regulatory compliance with clean air and water standards.
Next Step: Remote control and automation
Remote control and automation technologies produce more uniform, accurate and reliable outcomes with less risk to personnel by reducing the variance inherent to manual processes and operations. Similar to mine management systems, control and automation systems are built on a framework of remote sensors, remote imaging, processing and visualisation software, but then take the next step to automate the action. Machine control and guidance systems on drill rigs, excavators, wheel loaders, and dozers represent steps towards automation by aiding operators in high-precision operations. Demonstrating the interest in automation in haulage, Rio Tinto, BHP and Fortescue Metals Group now operate fleets of driverless haul trucks at sites in Australia.
In addition to machine control and guidance, automated aerial surveying using UAVs with pre-planned routes is not only faster than terrestrial surveying in many cases, but removes ground personnel from hazardous areas. Like mine management systems, control and automation systems depend on a technology backbone of positioning, communication and redundancy. Multiple positioning technologies are necessary to have the level of redundancy required for automation and to support geospatial awareness of everything on the autonomous site.
Proliferation of geospatial applications in mining
Measurement, control and automation technologies are aiding mines in achieving significant gains in productivity, safety and operating expense savings. With this success and with ongoing economic realities, investment in these technologies is high on the planning and budgetary outlooks for most large-scale operations.
Mining an ore body has always been a 3D activity. From development of the geological model to measuring material volumes at ports, mines operate in a 3D environment but many of the metrics reported by mine management systems reduce the 3D environment to just two measurements: tonnes and time. The proliferation of new technologies that allow mine management to capture the 3D environment throughout the production stage presents opportunities for expansion and integration of geospatial applications. In addition to the fourth dimension — time — the 3D information allows mining companies to reconcile the resource model for actual versus expected ore grade.
Technology trends and proliferation of geospatial data require knowledge and experience for accurate analysis, interpretation and use of the geospatial information. In hands of an expert, geospatial data becomes geospatial intelligence. Mines have geospatial expertise on site in chief surveyors who understand the origins, correct application, and reliability of geospatial data. The new role of a surveyor as a geospatial data manager is a critical service required by all divisions in a mining organisation and has a crucial facet lacking in typical data-serving functions —the origin and limitations of positional data.
The quality, accuracy, and streamlined workflows of geospatial technologies used by mine surveyors will continue to advance, making the data in the hands of surveyors more valuable. Some of the most interesting trends are in realising the full value of this data by connecting the workflows and data from survey to production back to mine planning so the data contributes value to the enterprise throughout the mine planning and operational cycles.
The value of 3D has been extensively debated and assigning true value to 3D has been difficult, but visualisation in 3D adds context to the operational and production data and as a result makes the information accessible, more easily processed, and as a result, more actionable.
Data integration in mine information systems
The value of the data, including geospatial information, produced by many mine management and control systems has not been fully realised since it is not readily collected and integrated for a reliable, complete dashboard view and deeper analytics across mining operations.
Many mining companies are turning their attention to extracting more value and use from their planning, mining and processing data to inform strategic decision making. By consolidating data into a managed data environment, an enterprise mining information system can unlock data and metrics across functional areas for a complete view of mine productivity and profitability and global analytics necessary for decision makers in planning, operations and finance.
There are five principles to successful development and implementation of an enterprise mining information system: validation, integration, consolidation, automation, and applied mining expertise. Validation produces consistency and quality of the data that can be trusted. Integrating disparate data exposes it to new approaches of optimisation. Consolidation provides access to the same validated data for use by a wide audience with useful dashboards and comprehensive analytics to help operations reach their business goals. Automation reduces reaction time to exceptions and reduces time for staff to maintain legacy data management techniques. The fifth principle is mining know-how applied to understanding the data sources, interpreting data, and value of data analysis to make improvements.
GIS: From the planning office to the central office
The leading mining companies are operating global business portfolios. Remote control, automation and enterprise-level mining information systems increasingly allow operational and strategic decisions for remote sites to be made in central information centres. Innovations in mining practices are expected as mining companies can interrogate more data across functional areas and sites to reveal patterns of sub-optimization and benchmark best practices for wider adoption. The geospatial component can connect planning and design data to mining operation data to business office data for a complete view of global portfolio performance, creating opportunities for new geospatial technologies and new roles for geospatial experts.