Simulations for Grade Engineering

Simulating complex mine operations for the integration of new technologies

Grade Engineering® in mining refers to our ability to exploit the natural heterogeneity of an orebody to improve yield. Particular deposits can present higher concentrations of minerals or metals in finer size fractions. Therefore, certain strategies can be implemented to separate the finer from the coarser material, in turn, up-grading the concentration of ore sent for processing.

Common Grade Engineering levers include, but are not limited to differential blasting, screening, sorting and coarse particle flotation. In this scenario the low-value (waste) material can be left in the pit or treated separately from the main processing plant, minimising transportation of waste to and from the mill.

Developed by the Cooperative Research Centre for Optimising Resource Extraction (CRC ORE), Grade Engineering is an innovative approach to the early separation of ore from waste material. It is minimising the impact of declining grades and productivity in the Australian minerals sector. Early physical rejection of non-valuable material through pre-concentration techniques before processing, decreases processing costs and importantly can significantly increase the life of a mine.

Mining3 recently completed an 18-month project sponsored by CRC ORE to develop models and methods for simulating a number of these mining processes, constraints and processing outcomes and studying the risk and overall impact of flow during the introduction of operational changes.
A literature review of the current state-of-the-art revealed that it was clear that the industry lacked a method to simulate complex mining operations where decisions and controls, such as Grade Engineering levers could be implemented. This is particularly due to their inability to manage material characteristics and include processing systems, such as screens and ore sorters, into the simulations of day to day mining activities.

Ore transitions through a multitude of stages from blasting, loading, sorting, separation, transporting and stockpiling before arriving at the plant. Each of these stages introduces a statistical variation in the time of delivery. On top of this, ore is typically mined from multiple faces simultaneously, with a potential of mixing during these stages, impacting on the overall value of the Grade Engineering solution. The problem is further exacerbated by equipment resourcing and planned and unplanned delays. These all affect the characteristics and quantity of material delivered to the mill.

By using a technique called Discrete Event Modelling, Mining3 has developed models to simulate the progress of objects such as trucks or material over time, tracking potential delays, resource utilisation, stockpile levels or bottlenecks. On top of typical mining equipment, a number of mining processes, including screening or crushing, and material characteristics such as grades and grade-by-size distributions were also modelled.

With a statistical analysis present for each potential delay, a number of scenarios with their corresponding value of outputs can be developed. This allows for improved mine planning allowing a response to operational delays while still implementing Grade Engineering solutions.

This research has developed a tool that can simulate multiple variations of a future mine plan with the ability to adjust a wide array of operational parameters. From this, the value of each result can be measured. However, as each simulation takes time to run and there are many parameters that could be adjusted, choosing which parameters to modify can be a complex exercise.

Mining3 is currently working with PhD student, Nick Dendle, to develop techniques to find the combination of parameters that results in the best value within a reasonable time frame.