the modular python processing plant – designed for ... · in october 2008, a 20-tph modular...

MINERALS & METALLURGICAL PROCESSING May 20101

The modular Python processing plant – designed for underground preconcentrationT.R. Hughes and A.H. GrayGekko Systems Pty. Ltd.Ballarat, Victoria, Australia

AbstractHow do you fit a processing plant underground with minimal change to mine infrastructure and yet maintain economic recovery, operability and maintainability? By combining fine crushing, continuous-gravity recovery and flotation. A modular, transportable processing plant has been designed that is capable of being installed in underground drives/drifts or on the surface. The Python processing plants have been designed to treat 20 or 50 tons per hour of ore to a particle size of approximately 500 µm and recover gold and sulfides into the concentrate. The plant is only three meters wide (including bolt-on platforms) and can be installed on a 1:50 slope, making for very simple installation. Test work carried out by Gekko Systems Pty. Ltd. has indicated that up to 50% of ores tested to date would achieve gold recovery rates of over 90% using this method. The projected benefits of this strategy are numerous and include low overall capital and operating cost, significantly less power consumption compared with traditional milling circuits and low environmental footprint.

Paper number MMP-09-046. Original manuscript submitted October 2009. Revised manuscript accepted for publication March 2010. Discussion of this peer-reviewed and approved paper is invited and must be submitted to SME Publications Dept. prior to November 30, 2010. Copyright 2010, Society for Mining, Metallurgy, and Exploration, Inc.

IntroductionHistorically, most hard rock ores are processed

using large, high-energy-consuming crushing and grinding circuits, which require large structures installed on significant concrete foundations. To be able to significantly lower haulage costs, increase hoisting capacity, produce backfill underground and/ or reduce surface footprint, a number of mine owners have investigated relocating their processing plants underground. The size of these plants made relocating them challenging, with very few examples in practice (but see Dominy et al., 2009). Also, mature mining operations do not have the mining resources avail-able to excavate large caverns for their installation or have the mine power infrastructure in place to be able power conventional plants.

In October 2008, a 20-tph modular transportable processing plant capable of installation underground was commissioned on the surface at Central Rand Gold Ltd’s mining operation in Johannesburg, RSA. The plant, called the Python processing plant (Gekko, 2007), was the result of a four-year research and de-velopment program funded by the Australian govern-ment and built on Gekko’s 10+ years of experience with high-mass-pull gravity concentration. This experience included the development of laboratory procedures to characterize orebodies, engineering knowledge to ensure the gravity circuit operated at its optimum level and improvements in the design and control of the key gravity recovery component,

the InLine Pressure Jig (IPJ). The application of existing equipment in innovative ways

was essential to keeping the plant’s dimensions at the target level, while the use of fine crushing to minimize energy use enabled the production of a design for easy installation under-ground and a lower operating cost. The knowledge gained from the first (surface) installationhas been incorporated into the latest design of the Python 20 tph (Python 200) plant and in the scale-up to a nominal 50 tph version (Python 500).

This paper describes both Python processing plants and the methodology involved in their manufacture.

Design concept The Python relies on the use of coarse and fine crushing, wet screening, continuous gravity concentration, flash flota-tion and water recycling to concentrate greater than 90% of the gold into a high mass pull concentrate of 10 to 40% of the mass. The higher mass pull level is used in underground mines, where only 60% of the tailings or less can be returned as backfill, due to the swell factor of the tailings, or where high recoveries are desired.

The narrow dimensions of the Python enable it to be installed in development drives or drifts close to the working face and in distributed locations to minimize ore tramming distance andbackfill pipework (see Fig. 1).

The design of the Python is based on two key factors (Hughes and Cormack, 2008):

1. Concentrate the ore as soon as it is liberated.

Key words: Gold/ gold ores, Gold processing, Milling circuits

May 2010 MINERALS & METALLURGICAL PROCESSING2

Figure 1 — Python underground distributed system.

tor (VSI). The VSI, see Fig. 2, uses rock-on-rock crushing to liberate minerals at the grain boundaries. Figure 3 shows pyrite crystals liberated from Lihir Gold’s Ballarat Goldfields ore.

Typically, the recirculating load around a VSI is of the order of 300%, similar to a conventional milling circuit. Installing the IPJ in this recirculating load enables it to recover friable minerals at as coarse a size as possible, which makes gravity recovery easier, as well as prevents overgrinding.

The VSI is also insensitive to moisture content, making it ideal to couple with wet fine screening. Bogging due to sticky material has been overcome by the use of under-rotor water sprays, which keep material moving without adding extra water to the VSI feed. The under-rotor sprays are particularly efficient at undercutting the crushing chamber buildup, ensuring there is no restriction of crusher discharge.

Figure 2 — Vertical shaft impactor (VSI).Figure 3 — Pyrite crystals liberated by a VSI at Ballarat

2. Combine continuous high mass pull gravity (via the IPJ) with flotation to recover both the fine and coarse particles as soon as possible.

To concentrate the ore as soon as possible means locating the primary recovery device in a recirculating crushing circuit to capture coarse minerals as soon as they are liberated. This concept is realized in the Python using a vertical shaft impac-

Goldfields (scale is in cm).


Excessively wet ore will create issues with wash-ing out the buildup in the crusher rotor and rock box. These problems can be overcome by prescreening the ore to remove fines and sizing the secondary screen to size. Dewatering oversize particles to less than 15% moisture enables them to be more effectively handled by the VSI’s rotor. The rotor itself is designed to cen-trifuge water out of the feed through drain holes in the rotor walls. This step ensures that material designed to build up on the walls (to reduce wear in the rotor) doesn’t slump out.

Final wear/blockage control is enacted by measur-ing and controlling the water spray flowrate to ensure the water addition is optimized to throughput and wear control.

High mass pull gravity recovery in an IPJ has been used for over ten years in many applications, including gold, sulfides, tin and diamonds (Gray and Hughes, 2008). This technique relies on the unique operating

methodology of the IPJ (Fig. 4). The IPJ combines a circular bed with a moveable sieve action. The screen is pulsed vertically by a hydraulically driven shaft, the length and speed of which are fully adjustable. Inside the IPJ, hydrophobic issues associated with conventional jigging are eliminated, as the IPJ is kept hydrostatically full. The slurry within the IPJ also acts as a pseudo dense medium above the jigging bed, assisting with the separation.

Laboratory testing (discussed later) of a wide variety of ores using high mass pull gravity recovery in the IPJ has shown nearly 20% of samples tested could achieve gold recoveries at around 90% in a gravity-only circuit (see Fig. 5).

Floating the gravity test tailings has been carried out on just over 100 samples. These tests indicate that preconcentration using gravity and flotation pushes the percent of samples having a recovery greater than 90% to 50% (see Fig. 6).

The synergy between coarse gravity recovery with an IPJ and fines recovery using flotation has been reported previously (Gray and Hughes, 2007). The actual data from a milling circuit operating a flash flotation cell in combination with an IPJ in the cyclone underflow

Figure 5 — Gekko laboratory testwork indicating for approximately 20% of all samples tested, a gold-recovery-to-concentrate greater than 90% could be achieved with gravity only.

Figure 6 — Gekko laboratory testwork indicating for approximately 50% of all samples tested, a gold-recovery-to-concentrate greaterthan 90% could be achieved with gravity and flotation.

Figure 7ship for an IPJ and flash flotation cell operating in a mill

— Dove-tailed, single-pass-size recovery relation-

recirculating load.

Figure 4 — InLine Pressure Jig cross-sectional view.


stream shows the IPJ recovering gold down to 106 µm and the flotation cell recovering gold in the finer fractions (see Fig. 7).

It is the above two principles that have enabled the develop-ment of a high-recovery, low-energy consuming flowsheet that can be engineered into a narrow, portable processing plant.

Python descriptionThe Python process flow is shown in Fig. 8 and described

below.Run-of-mine ore is tipped over a static grizzly to a feed

hopper. Ore is withdrawn from the hopper by a chain conveyor or vibrating feeder that discharges onto a rubber conveyor. A belt magnet removes tramp metal (e.g., bucket teeth, rock bolts and plates) off the conveyor prior to ore delivery to a vibrating grizzly feeder. The vibrating grizzly undersize reports to the jaw crusher discharge conveyor whilst the oversize reports to a single toggle jaw crusher.

The jaw crusher, operating at a tight closed side setting, discharges ore through a vibrating feeder onto a belt conveyor, where it is carried to the primary screen (45 mm aperture). The oversize ore reports to two rubber belt conveyors that return the oversize material to the jaw crusher. The undersize ore is conveyed via weight-metered belt and transferred to a second belt, which discharges to the wet secondary screen (3 mm aperture). The oversize material from the secondary screen is discharged to the conveyor belts feeding the vertical shaft impactor (VSI).

The secondary screen undersize slurry is pumped to the rougher IPJ(s). The IPJ concentrate (gold and/or other heavy minerals) is pumped to another IPJ for cleaning. The tailings from the rougher IPJs flow to the tertiary screen (0.6 - 0.85 mm aperture). The tertiary screen oversize is discharged to the conveyor belt feeding the vertical shaft impactor for reprocess-ing. The tertiary screen undersize is pumped to water recovery (a hydrocyclone designed to recover most of the solids in the

underflow and recycle water in the overflow back to the IPJs and screens).

The dewatering cyclone overflow reports to the dirty water side of the recycled water tank. Fine solids settle out and are discharged via a sludge valve into the gravity tailings sump, while the “clean” water overflows a baffle into the recycled water side of the tank. The recycled water is topped up with mine water and recycled to the IPJ and screen water sprays.

The dewatering cyclone underflow reports to the gravity tails sump, where it is mixed with flotation reagents before being pumped to the flash flotation cells in parallel. The con-centrate from the cells is pumped to the final concentrate sump pump, where it is combined with the concentrate from the IPJ for pumping to the concentrate storage/processing facility or dewatered and hauled to surface.

The clean IPJ tailings flow under pressure to the second-ary screen for reprocessing through the jig circuit and to help “wet” the new feed. The clean IPJ concentrate flows to the final concentrate pump.

The flash flotation cell tailings (final tailings) are pumped to the tailings storage facility or dewatered and used in backfill.

Flotation reagents are stored in 1500-L storage tanks on one of the modules and administered to the processor via header tanks or dosing pumps.

Process control is achieved using an Allen Bradley Program-mable Logic Controller (PLC) with SCADA interface. All motor starters and electrics are housed in stand-alone motor control centers.

There are currently two Python “models,” with dimensions and capacities as shown in Table 1.

InstallationAs can be seen from Table 1, the Python units are very narrow.

Fig. 9 shows a projection of the Python 200 model installed in a five-meter-wide drive (excluding the bolt-on walkways). It is

Figure 8 - Python processing plant flow diagram.


possible to drive a light vehicle down the side of the installed Python without having to increase the width of the drive.

The modules are also designed to be installed on a sloping floor (up to a 1:50 slope), as it was recognized that no drive in an underground environment can be level due to flooding/drainage issues (see Fig. 10). The modules need to be lev-eled across their width (up to 2.3 m) and length (up to 11 m) but only a very few need to be level in respect to each other.

The units also do not need to be installed in a straight line, as once the process reaches the gravity stage, all transfers are by pump and pipe. Therefore, the “wet end” of the Python can be installed on a different level in the mine or, if on the surface, parallel to the dry end, as shown in Fig. 11.

Figure 11 also shows the small amount of concrete needed underneath the plant to act as bunding and to aid clean-up around the plant.

Operation of the Python on the surface has shown the ability of the circuit design to minimize the effect of dust emission normally associated with fine crushing circuits. Dry crushing is kept relatively coarse, at approximately 35 to 50 mm. Dust control at this point is achieved by the use of atomizing water sprays at key transfer points. Fine crushing is carried out after wet screening and at typical moisture contents of 10 to 15%, eliminating any dust emissions.

Maintenance of the Python does require a shift from typical surface processing plant paradigms. To keep the plant narrow and remove the need for large storage bins, the crushing circuit

is directly coupled to the concentration circuit and there is no provision for standby equipment. As such a relatively low plant availability of 83% has been budgeted for the Python plant. This allows 28 hours per week, every week for routine and unplanned maintenance.

Due to the restricted space in and around the Python, critical areas around pumps and larger equipment have built-in lifting devices to enable easy removal of heavy wear liners. For the Python itself, a monorail is required above the crushers to enable the removal of the jaw crusher wear liners and larger VSI components.

An advantage of the Python design is that no component is more than five meters above the ground, resulting in minimal work-at-height situations.

To combat corrosive mine water likely to be used in and around the Python, the experiences of the Western Australian Goldfields and offshore diamond processing ships have been used. The high salinity of the WA goldfields water (typically 100 000 + total dissolved solids) and high sulfide ore content has required the use of galvanized steel to reduce corrosion rates. The IPJ units have been successfully used in marine diamond dredges for almost ten years. A specific paint specification

Python 200 Python 500

Nominal capacity* 20 tph 50 tph

Availability 83% 83%

Annual throughput 145 000 tpa 360 000 tpa

Installed power 450 kW 1 000 kW

Operating power 240 kW 600 kW

Final crush size 500 µm 500 µm

Dimensions – L*W*H 96*2.6*4.8 m 130*3*5.5 m

Max module length 9 m 11 m

Max module weight 20 t 40 t

VSI power input

(max)

160 kW 400 kW

Top feed size 250 mm 250 mm

Mass pull to concen-

trate

1 to 8 tph 2.5 to 20 tph

Major equipment

Jaw crusher (mm *

mm, installed power)

600 * 400, 30

kW

750 * 500, 55

kW

VSI 160 kW / 110

tph

400 kW / 320

tph

Sec screen 5’ * 10’ 6’ * 20’

IPJ rougher/cleaner 2 * 1500/ 1 *

1000

2 * 2400/ 1 *

1500

Flotation 1 or 2 * SK80 3 * SK80

Figure 10 — Python 200 installed and operating on a 1:50 slope.

Table 1 — Python processing plant model specifications.

* Dependent on ore hardness and final crush size.

Figure 9 — Python 200 installed in a five-meter drive.


has been developed to provide long service intervals.The modular, skid-based design of the Python does

provide the ability to replace sections of the steelwork if corrosion rates are unacceptable, without having to replace a whole structure, as in a surface plant. It is also possible to have an entire module on standby, prewired with or without major equipment, to enable an entire module to be removed and refurbished with only a one-day downtime for the plant.

Python amenability test work proceduresIn order to determine if an ore will be amenable

to the Python processing methodology, a detailed test work program is required, covering:

- mineralogy- impact crushing work index- vertical shaft impactor amenability- gravity recovery versus crush size – yield

versus recovery- flotation recovery versus crush size – yield versus recovery

Mineralogy. The ideal starting point for a Python ame-nability test program (or any metallurgical test program), is to determine the gold occurrences via detailed mineralogy. Of importance to the Python are the gold occurrences – free, locked in sulfides, locked in other minerals – and the liber-ated particle size of the gold, if it is free, and the gold-bearing minerals if not.

Both gold and gold-bearing mineral particle sizes are criti-cal, as the QEMSCAN image indicates (Fig. 12).

The gold in this case was approximately 5 µm, whereas the gold-bearing pyrite was almost 400 µm. Pyrite has a specific gravity of 5.2, making it easily recoverable in the IPJ at its natural grain size (Gray and Hughes, 2008) and as such a high continuous gravity gold recovery was achieved.

Crushing amenability. The bond impact crushing index test is carried out on selected rock samples (50 mm by 75 mm) and the result is used to calculate the net power requirement for crushers and to determine the required open side setting for a jaw crusher. This requirement is very important in the case of the Python, as there is a fine balance between creating a small jaw crusher product size for further processing versus a reduction in crushing capacity at small closed side settings.

The capacity of each Python model needs to be carefully considered vis-a-vis the hardness of the ore as determined by this crushing test.

VSI amenability. This test is conducted to deter-mine the amenability of processing the sample through a VSI crusher. It involves reducing the sample to -11.2 mm in a lab-scale jaw crusher, screening the material to the desired product size (e.g., 1.18 mm, 850 µm, 600 µm, 425 µm) and passing the sample through the laboratory scale VSI. The product from the single pass is sized to determine the production rate of the required product size (Fig. 13).

The curve for Sample 1 showed a high amenability for VSI crushing, with over 40% of -600 µm product produced in a single pass. Sample 2, on the other

hand, barely produced 20% passing 1 mm in a single pass

Figure 11 — Python 500 installed on surface in a “U” shape.

Figure 12 — QEMSCAN image of a 500 µm pyrite particle with 10 µm gold inclusion.

Figure 13 — VSI amenability curves.


and would not be amenable to this type of crushing, due to excessive recirculating loads.

The lab-scale VSI used in these tests has been calibrated against actual VSIs operating in Australia and South Africa in fine gold ore crushing applications.

The production rate of product size is used in combination with a LIMN mass balance to determine the ore’s amenability to VSI crushing.

Continuous gravity recovery. A laboratory-size Wilfley shaking table is used for the tabling test. A thin film of water is applied to the shaking surface and several concentrate ports are available to separate the products. The tails are then reduced in size using a VSI and passed over the table again. The tails of the second stage can then be reduced in size again for a third pass over the table, if required. The concentrates from each pass are retabled to produce a number of concentrate products

which are weighed and assayed. A yield-recovery curve is determined for that sample (Fig. 14).

This test can be repeated at various final crush sizes to de-termine the optimal liberation size for the ore. This recovery-versus-crush size was significant in the case of the Ballarat Goldfields processing plant, where initial tests were carried out at a fine grind size, 106 µm, then got progressively coarser. The tabling test showed a significant increase in recovery as the grind was coarsened (Fig. 15). This effect is believed to be the result of overgrinding naturally coarse sulfides (up to 5 mm), resulting in fines that aren’t gravity-recoverable. In practice, the Ballarat Goldfields’ IPJ gravity circuit achieved sulfide recoveries that were double what was achieved in the laboratory. This result was due to the presentation of the sulfides to the IPJ at up to 5 mm rather than the 1 mm top size used in the test work.

Flash flotation recovery. Flash flotation testing is used due to the Python operating at crush sizes that are too coarse for conventional float cells. The procedure used is recom-mended by the manufacturer (Outotec), with the modification of extended float times. These times are intended to simulate longer residence time in the Python flotation cells compared to conventional milling circuit applications.

The procedure involves screening the gravity tail at 600 µm to remove coarse particles, which won’t float but will damage the laboratory float cell. Then the float reagents are added in quick succession to simulate short conditioning times and col-lection of flotation concentrates over four 30-second periods, followed by an extended collection over five minutes.

The test is very aggressive in terms of float residence time and reagent conditioning, but is required to enable the design of the smallest float circuit practicable.

The flotation and gravity results are combined to produce a gravity-plus-flotation yield-recovery curve at the test crush size (see Fig. 16). The data contained in this curve are then interpreted to determine the required mass yield from each stage to give the desired recovery.

Projected Python advantagesThere are numerous projected advantages (Dominy et al.,

2009) to preconcentrating the ore underground. These advantages drove Gekko to undertake the research project and can be summarized as follows:

• Processing capacity can grow at the same or similar rate to the underground production rate for new mines. That is, excess capital isn’t sunk in the early project phase.

• Improvement in Mine Call Factor, due to fewer handling points for the ore en-route to the plant.

• Reduction in tramming and hoisting costs, due to lower tonnage being moved.

• Increased metal capacity of hoisting systems, due to higher grade.

• No necessity for backfill to be produced on the surface and sent back underground.

• Reduction in required surface plant capacity and costs due to higher grade.

• Much-reduced power consumption over conventional processing (estimated underground

Figure 14 — Gravity yield-recovery curve.

Figure 15 — Effect of overgrinding on gravity gold recovery.


consumed power of 10 kWh/t versus 20-25kWh/t conventional milling power consumption)

• No detoxification requirements on backfill produced by this stage of processing, as it has not been exposed to cyanide.

Most of these advantages can also be applied to using this type of circuit on the surface with the additional advantages of:

• Money isn’t sunk into the ground with expensive founda-tions and infrastructure.

• Only a simple concrete pad, one electrical connection to the motor control center and two water connections are required.

Figure 16 — Gravity + flotation yield-recovery curve.

• Plant design can be easily expanded with extra modules being able to plug and play into the existing plant.

• Maintenance and operating system have already been developed and are “preloaded.”

• Easily relocatable to the next mining area.The projected operating cost for this type of plant, with

its simple comminution system and low power consumption, is dependent on local labor cost but is estimated for a typical South African application (Table 2). The wear cost on a VSI crusher is typically much higher than on conventional crushers and operating experience suggests a cost for parts of the order of US$1/ton. However, these costs are still significantly less than grinding mill liner and grinding media costs. Exact costs are hard to predict, as each ore will vary in hardness, abrasive-ness and reagent consumption and each location will vary in pumping distances, backfill requirements, power costs, etc.

The operating cost, $/t, would be comparable to much larger throughput plants and is a significant benefit of this type of flowsheet.

The expected environmental benefits are also significant, with improvements in cyanide consumption from treating a lower mass of concentrate, significantly less power consump-tion, “benign” tailings at a coarse grain size and significantly less surface footprint.

ConclusionsThe benefits from focusing on the liberation size of the

gold-carrying components of the ore, rather than of the gold itself, has led to a plant design which is modular, transport-able and simple to install in either underground tunnels or on the surface. The Python has a projected low overall capital requirement, low power consumption and low operating cost, with significant environmental benefits as well.

The Python has been installed and operated on the surface, but not in an underground mine. As such, this paper does require the reader to decide for themselves if a minimization of plant width, height, installation requirements and power consumption compared with a surface plant removes the historical restric-tions for processing ore underground.

AcknowledgmentsThe authors would like to thank the management team of

Gekko Systems Pty. Ltd. for their data and kind permission to present the information detailed in this paper.

ReferencesDominy, S., C., Hughes, T. R., Grigg, N. J., Gray, A. H., and Cormack, G., 2009,

“Development of underground gravity gold processing plants,” paper pre-sented to Physical Separation 2009, Falmouth, UK.

Gekko Systems Pty Ltd, 2007, “Mineral Processing Apparatus,” Australian Provisional Patent Application 2007905245.

Gray, S., and Hughes, T., 2007, “A focus on gravity and flotation concentration and intensive leaching rewrites conventional milling circuit design and im-proves environmental and cost outcomes,” paper presented to World Gold Conference 2007, Cairns, 22-24 October 2007.

Gray, S., and Hughes, T., 2008, “Improvements in the InLine Pressure Jig ex-pands its applications and ease of use for gold, silver, sulphide and diamond recovery,”paper presented at Metallurgical Plant Design and Operating Strategies 2008, Perth.

Hughes, T.R., and Cormack, G. 2008, “Potential benefits of underground pro-cessing for the gold sector – conceptual process design and cost benefits,” paper presented at First International Future Mining Conference, Sydney, 19-21 November 2008.

Table 2 — Projected operating cost for a Python plant (oper-

ating in RSA).

Summary Estimated cost per ton, USD

P200 P500

Labor $ 2.80 $ 1.20

Management 1.60 0.60

Consumables 3.30 3.30

Reagents 0.60 0.60

Loader hire 2.00 0.80

Diesel/mains

power

1.50 1.50

Water 0.30 0.30

Assaying 0.20 0.20

Equipment hire 0.10 0.10

Other 0.10 0.10

Total $12.50 $ 8.80

* This table assumes three operators per shift and a power cost of $US 0.10/kWh.

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