3.5 Minerals processing

Comminution (crushing and grinding) is responsible for at least 40% of total energy usage in mining and mineral processing. Footnote 21 Improved flow sheet design strategies reduce the direct and indirect energy usage for comminution by:

  • maximising gangue rejection ahead of the next downstream step to reduce the amount of material that requires treatment by comminution
  • ensuring the use of the most energy-efficient crushing technologies ahead of the energy-intensive grinding step
  • ensuring the use of the most energy-efficient grinding technologies.

There are many specific energy-efficiency strategies for comminution, which are outlined below. Note that these strategies are best applied to the design of greenfield comminution circuits, when an increase in capacity is required, or when a change in ore hardness is expected for an existing operating circuit.

Use new and more energy-efficient grinding technologies

Studies show that in some mines the amount of input energy going into the grinding process can be reduced by as much as 40% using the latest efficient equipment. Footnote 22 Computer simulations using the discrete element method show that most rocks larger than the discharge grate size do not break in the first collision. Instead, they accumulate damage in multiple collisions before breaking, which is an inefficient use of energy.

A wide range of comminution equipment is available for many materials and for many different conditions. The choice of equipment and design of circuits has a significant influence on energy use.

In addition, the combination of the use of energy-efficient crushing and fine grinding equipment helps to reduce energy use by:

  • reducing the primary and secondary recirculating loads, leading to lower power requirements, a smaller volume of ore to handle, and potentially a switch to a smaller mill
  • creating a steeper distribution of particle sizes, leading to easier mineral liberation and more efficient downstream processing
  • reducing the need to use grinding media that have high embodied energy (for example, as HPGR circuits do).

Select the coarsest possible grind size

The target product size, or grind size, has a large influence on the size and energy use of a comminution circuit. As the product becomes finer, the internal flaws in each particle become fewer, the particles become more difficult to fracture, and the grinding energy increases.

An alternative approach for the selection of a target product size for multi-mineral ores is the progressive liberation strategy. This involves liberating one mineral or one group of minerals at a time by applying the following concepts:

  • Multiple valuable minerals are grouped, increasing their effective concentration, and enabling the desired level of liberation to be achieved at coarser target product sizes.
  • Fully liberated particles (100% valuable mineral) are recoverable in a flotation process.
  • Particles containing at least 15% valuable mineral by sectional area are recoverable in a flotation process using the appropriate flotation conditions and flotation reagents. Footnote 23

If minerals are sufficiently liberated or recoverable (in composite particles), they can be separated from the ore before further comminution. This strategy can also be used to remove gangue from the ore, leading to less grinding energy and more efficient separation in downstream processes. However, this strategy requires a good understanding of the particle composition at different product sizes.

Optimise particle size

The reduction ratios for each successive crushing and grinding process influence the distribution of particle sizes and the energy use of the process. Energy use is relatively low when particle sizes are consistent. Finer particles, having less microcracks and being more difficult to fracture, resist breaking and are instead displaced, causing energy to dissipate; they also lead to the generation of slimes.

Screens and filtering devices help to achieve a more consistent particle size. A consistent distribution of particle sizes is expected to produce superior flotation performance.

Use more advanced and flexible comminution circuits

Using a single comminution circuit with very large semi-autogenous grinding mills has enabled companies to expand economically into large, low-grade ore bodies and treat large volumes of ore. A disadvantage of this approach is that comminution becomes less efficient as ore body concentrations decline but there is only one circuit operating. Therefore, many companies have moved to using comminution circuits with at least two (in some cases, more than four) parallel milling circuits. This allows high- and low-grade ores to be processed simultaneously, but on separate circuits, enabling each grade to be ground closer to its optimal recovery size, increasing grinding efficiency and reducing energy use (Box 17). Footnote 24

It is possible to optimise, design and build comminution equipment perfectly fitted for each ore body Advances in modelling by CSIRO and the University of Queensland can now assist in determining and optimising the design of the most energy-efficient comminution equipment. Research teams have developed theoretical approaches and software packages for modelling different combinations of comminution circuits to minimise overall energy use across the circuit.

The discrete element method (DEM) is increasingly useful as a tool that can help provide fundamental insights into comminution processes and into the behaviour of specific comminution machines. Footnote 25 It can contribute to the design and rapid manufacture of new comminution equipment, the improvement of existing equipment, and increases in the operational efficiency of all comminution unit processes. For example, DEM modelling can now allow detailed exploration of the particle flow and breakage processes within comminution equipment, allowing a clearer and more comprehensive understanding of those processes.

Box 17: Modifying the secondary dry circuit for Wonnerup mine

The North Shore mineral separation plant receives mineral-rich ores, known as heavy mineral concentrate, from the Cristal Australia mining site at Wonnerup, which is near Busselton in Western Australia, and the Broken Hill mineral separation plant. Changes to the physical characteristics of the concentrate occur, which generally relate to the location of an ore body or other factors. The new ore body at Wonnerup contains increased amounts of leucoxene and finer grain secondary minerals. The existing equipment at the North Shore secondary dry circuit will only be able to process the non-magnetic portions of this heavy mineral concentrate at a feed rate of 7.2 tonnes/hour without significant loss of product recovery. Additionally, the existing technology will not capture all of the fine grain materials. This results in

  • higher energy consumed per unit of product available for sale
  • a higher proportion of material returned to site, increasing freight costs and diesel consumed and CO2-e produced.

An opportunity was identified to implement process changes that increase product recovery and the processing rate, reducing energy per tonne produced.

The existing process relies on the magnetic and conductive properties of the leucoxene and uses induced roll magnetic and electrostatic separators to separate the target mineral. However, an induced roll magnetic separator machine uses electricity to maintain the magnetic field. New rare earth roll magnetic separator machines use permanent magnets, without electricity.

The process change includes the introduction of a new 300 mm rare earth roll magnetic separator machine, reducing the energy in the early stage of the process. For the Wonnerup mineral, this change will allow an increase in production of 39% to 10 tonnes/hour. However, for the Wonnerup ore body, the old induced roll magnetic equipment will be introduced to the back end of the circuit to increase the recovery of Wonnerup’s finer grain secondary minerals. This will

  • reduce total electrical energy consumed
  • reduce the energy per unit of production
  • reduce greenhouse gas emissions
  • increase production throughput by 39%.

It is estimated that this project will reduce energy consumed by around 808 GJ, resulting in a net reduction of greenhouse gas emissions of 200 tonnes CO2-e/year. The change has a capital cost of $560,000. The value of the increase in production, plus energy and maintenance savings, is $770,000, giving the project a payback of less than 9 months.

Source: Cristal Australia Pty Ltd, EEO Opportunities Register, http://eex.gov.au/opportunities-register/cristal-australia-pty-ltd-opportunity-o/.

Improve the efficiency of separation processes

Froth flotation is a method of mineral separation that relies on the different chemical properties of minerals compared to gangue. Optimising the chemistry in the flotation cells reduces energy intensity. Energy savings are possible through using more advanced froth flotation technologies and control engineering.

For example, technologies such as the Jameson cell produce smaller bubbles more consistently than previous flotation cells, enabling the process to be more energy efficient. Mixing and adhesion occur more quickly and in a smaller space compared to traditional froth flotation cells. A higher percentage of mineral is recovered, improving the economics of a mine. The Jameson cell also has no need for a motor, air compressor or moving parts.

Improvements are also being made in control engineering of flotation systems to achieve further energy-efficiency improvements.

Optimise existing systems

Systems optimisation is an ongoing process involving the use of frequently measured and calculated system inputs in order to manage and optimise productivity and quality. It sits above existing process control systems, which are widely used to monitor and control particular processes within a mining, manufacturing or infrastructure plant. Based on information received from remote stations (sensors), automated or operator-driven commands are sent to remote station control devices (actuators). These systems control factors such as raw material feed rates or boiler temperatures in a manufacturing process.

Systems optimisation is more dynamic than traditional approaches to analysing energy performance. It can support effective energy management by helping to identify areas of wastage, helping to understand the energy consumption of the process, highlighting changes to energy consumption patterns and reaching an optimal condition for the supply of power. In most cases, energy-efficiency benefits are achieved by improving productivity.

While the benefits are dependent on the primary objectives of the project, the following outcomes are those that are generally achieved through effective implementation of systems optimisation:

  • increased output
  • increased energy efficiency
  • reduced energy cost increased product quality
  • reduced emissions
  • reduced downtime
  • reduced environmental impact
  • reduced human input
  • improved work health and safety.

An example of the application of systems optimisation to the processing plant at Anglo Gold’s Sunrise Mine is outlined in Box 18.

Box 18: Process optimisation at Anglo Gold’s Sunrise Mine

AngloGold owns and operates the Sunrise Dam goldmine near Laverton, Western Australia. The mine, which has been in operation since 1995, began with open-pit operations and in 2003 began underground mining. The processing plant at Sunrise Dam is typical of many goldmining operations, consisting of crushing and grinding processes, and carbon-in-leach technology to recover gold.

The company initially considered systems optimisation as a means to improve productivity by reducing downtime in the milling and crushing plant. The objective was to improve throughput by maximising the productivity of the plant. The project team sought to increase production by finding the optimal processing rate and sustaining that rate as much as possible by eliminating causes of downtime or process bottlenecks.

Before looking at any equipment upgrades, the engineers first investigated how they could unlock the potential of the operating equipment that was already installed. The existing control systems and operating methodologies were designed to avoid out-of-control events or unstable events, and were working reasonably well in this regard. However, the plant was avoiding unstable events by running well below the capability of the equipment.

Many of the operating costs of the processing plants are fixed regardless of throughput, while other parts of the process become more efficient at higher levels of utilisation. Maximising the throughput of the plant lowers the energy consumption cost per tonne. Increasing the throughput results in an increase in power demand, but the overall energy intensity improves, resulting in an improvement in profitability.

The project team investigated options to minimise idling time in crushing and milling equipment, and the time that equipment spent operating outside its ideal speed or throughput range. They also investigated instances when the circuit became unstable, to gain a better understanding of the constraints and limitations of the plant.

For example, if the feed supplying ore into the mill stopped but the mill continued to operate, the mill would still draw a substantial amount of power while adding to wear and tear on the milling balls. One area of optimisation was to ensure that the mill ran only when sufficient feed was supplied. Other problems can occur if the mill is optimised to run at a certain throughput and the throughput is increased, resulting in an overload. This may require the circuit to be stopped while the overload is rectified, resulting in a net loss of productivity.

Before making any changes to the control system, the project team developed a full understanding of the ideal operating range for each part of the circuit. They looked for other events that caused faults and downtime, and those were fixed first.

Implementing systems optimisation

All systems optimisation upgrades were implemented through changes to the logic and control algorithms of the programmable logic controllers. Before implementation, the initiative was given a high profile and promoted by the processing manager at Sunrise Dam. It was regularly discussed in production meetings and became a part of the performance evaluation process. The process manager for each area of the plant was responsible for identifying opportunities, developing the business case, implementing opportunities and measuring the results with SCADA. Optimisation projects were scoped and budgeted and then ranked based on payback period and production improvement. Once changes were approved, external contractors were engaged to implement the programming changes.

Training operators

As new control system upgrades were implemented, it was important to minimise manual intervention by the plant operators. Systems were put in place to monitor how often control loops were in automatic mode and to log times when the plant was switched to manual control

A training program for plant operators was introduced to support the changes. Under the old system, operators had to intervene regularly in the process to make changes, often prompted by warnings or alarms from the SCADA system. The training focused on how to use the data in the control system to be proactive rather than reactive.

Operators were still able to take manual control of the system at any time, and were instructed to do so if they felt the need to switch off the automatic control system. They were also asked to make a note of the reason they had to switch out of automatic mode, so that the process engineers could understand what the limitations of the automatic control system were, and which issues to address next.

Benefits achieved

The operators now proactively use the control system to keep the plant working within defined operational parameters. The benefits achieved to date include:

  • fewer maintenance events (less downtime)
  • increased throughput
  • improved energy efficiency
  • reduced unit costs.

Source: Department of Industry, Case studies in systems optimisation to improve energy productivity, Canberra, 2013, http://eex.gov.au/files/2014/08/Systems-Optimisation-Case-Study-2013.pdf.

Footnotes

Footnote 21
See, for example, Z Pokrajcic, R Morrison, Ά simulation methodology for the design of eco-efficient comminution circuits’, in DZ Wang, CY Sun, FL Wang, LC Zhang, L Han (eds), Proceedings XXIVIMPC, volume 1, 2008.

Return to footnote 21 referrer

Footnote 22
For example: Z Pokrajcic, RD Morrison, NW Johnson, ‘Designing for a reduced carbon footprint at greenfield and operating comminution plants’, in D Malhotra, PR Taylor, E Spiller, M Le Vier (eds), Proceedings of Mineral Processing Plant Design 2009—An update conference, Society for Mining Metallurgy and Exploration, Tucson, Arizona, 30 September - 3 October 2009, pp. 560-570.

Return to footnote 22 referrer

Footnote 23
Pokrajcic et al., ‘Designing for a reduced carbon footprint at greenfield and operating comminution plants’: see footnote 22 for details.

Return to footnote 23 referrer

Footnote 24
MS Powell, AR Bye, Beyond mine-to-mill.

Return to footnote 24 referrer

Footnote 25
GW Delaney, PW Cleary, MD Sinnott, RD Morrison, Novel application of DEM to modelling comminution processes’, IOP conference series, Materials Science and Engineering, 2010,10(1), CSRP Project 2B1 Extension.

Return to footnote 25 referrer

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