Following our article looking at areas in which minerals processing operations typically lose money we have selected the most important topics and will be running a series of articles exploring ways to avoid value loss in more detail. We believe that as times become tougher through the minerals industry consideration of where additional value can be achieved and how costs can be reduced is of paramount importance.
Over the years, MinAssist has been involved in many optimisation programs and when asked to examine areas for optimisation in a processing plant invariably we will begin by looking at the feed material, specifically it’s variability and the impact that is having on stable operation of the process circuit. Often this area is the major cause of lost value in an operation and the impacts of its effects continue right through the process flowsheet.
Too often operations utilise ore type definitions that are based on geological or mining characteristics and have little relation to the processing behaviour of the material. This is perfectly valid for resource definition and mine planning but when applied to processing can be misleading. While there are situations where the relationship is valid, for the majority of operations there do remain subtle differences in how ore domains should be processed.
To examine the impacts of variable feed characteristics in a process circuit we can use total recovery as an example. Our example operation has three distinct ore types, all requiring different conditions in the grinding and flotation circuits. The ore types all differ from the geological ore types used in mine planning and for this reason the process is experiencing changes in feed ore type every 4 hours. When the process is stable recovery of 95% can be achieved for each ore type but they all require different processing conditions. In this scenario, when the ore type changes it takes the operators 30 minutes to detect the change and then another 30 minutes to achieve stability in the process again. During this time the average recovery drops to 80%.
What we see here is that for a quarter of the time this example operation is only achieving 80% recovery, when all the targets are set for 95% recovery. This equates to an actual overall recovery for the operation of 91%, which means that target production is not being achieved and management is being asked some serious questions. In addition, the operators and process metallurgists are spending their whole shift trying to stabilise the process, leaving little time for implementation of continuous improvement programs or any sort of optimisation.
Although the operation may not have the capacity to alter the mining plan to provide more even flow of feed material, measures can be taken to reduce the impact of variability. By understanding the ore types and identifying early warning indicators that a change has occurred we might be able to reduce the time for detection and to achieve stability to 30 minutes, rather than an hour. This would result in an overall increase in average recovery of 2% to 93%, simply from understanding the ore fundamentals more completely.
For another example see our article in the February issue of Mining Magazine on finding value through Process Mineralogy.
A number of key symptoms and possible solutions to ore variability impacts have been detailed below.
Variation in the hardness of ores is common in many resources. This has a direct impact on the throughput of a process as softer ores will be ground faster than harder ores. Alternatively, if a consistent throughput is maintained then softer ores will become overground, with wasted energy going into the comminution circuit and potential issues with fines generation affecting downstream process circuits. Harder ores will not receive sufficient grinding and adequate liberation of key minerals may not be achieved, resulting directly in losses to tailings. Constantly changing ore hardness can also result in blocking or excessive wear at points within the circuit.
Variability in the mineral composition of ore material fed to a flotation circuit can have a significant impact on the reagent requirements. The presence of deleterious minerals that can scavenge collector will require more collector addition. Alternatively, a higher proportion of fast floating minerals may require less reagent addition. In extreme situations where the mineralogy between ore types is significantly different there may be a requirement to use depressants for deleterious minerals with some ore types but not others.
Variability in the proportion of sulphide minerals can lead to significant variation in mass pull to concentrate. This may be correlated with the grade of the material but where gangue sulphide minerals are present can lead to dilution of the concentrate and potentially smelter penalties if the concentrate is to be sold.
Fluctuations in the tailings grade is often the first indication given of a change in feed ore type, which means that the new ore type has been fed to the plant for at least the time it to progress all the way through the circuit and have tailings samples assayed. The tailings grade will often rise due to inefficient grinding caused by harder material fed to the comminution circuit or insufficient residence time in the flotation circuit caused by slower floating minerals.
A simple test of whether ore type has changed can be based on the density of the slurry, which may be measured on site. Change from a quartz based ore type to a massive sulphide ore type will be associated with a significant change in density. This needs to be accounted for in any mass balancing for the process or in determining parameters such as reagent addition requirements.
The key aspect for dealing with feed variability is to understand the ore domains within the resource and how they may affect processing. Ideally, this would take the form of a geometallurgical model for the resource and mine planning that accounts for metallurgical characteristics. Where feasible blending programs can be used to even out feed characteristics but space or mining capacity constraints often make this difficult.
Often retrofitting a geometallurgical model in an existing operation is viewed as a costly and inefficient process. However, much of the information required to generate an understanding of metallurgical ore domains is available in geological ore type definitions and historic processing data. MinAssist is experienced in developing programs targeted at identifying metallurgical ore domains for existing operations using this information, along with mineralogical characterisation as verification. Although this doesn’t compare to a dedicated geometallurgical model it provides a cost effective avenue for an operation to begin implementing the concepts and increase the information they have available to reduce the impacts of ore feed variability.
If you would like further information on how MinAssist can assist in developing strategies to measure and reduce the impact of ore feed variability feel free to contact us to discuss your project. This is a key area in which many operations lose significant value and can be readily addressed through use of a cost effective and targeted process mineralogical program.