Sensor Base Sorting New Developments

United in Separation

Lütke von Ketelhodt 062009

Mintek 75th Anniversary, June 4, 2009

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2002

20062003

2009

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Contents

l Introducing Commodas/Ultrasortl Sorting Principlel Product Linesl Why Sensor Based Sortingl Mineral Applications for Sensor Based Sortingl Sensors within Electro Magnetic Spectruml Colour Sorting Examplesl NIR Sorting Researchl XRT Sorting Examplesl Conclusion

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Commodas UltraSort - Members of in the TOMRA ASand TiTech Group

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TITECH GROUP

Central Europe North America South Africa South America Russia

TOMRA Systems AS, Norway

Food Mining Recycling

Leading global provider of advanced solutions enabling recovery and recycling of materials

World leader in sensor based sorting technology

Listed on the Oslo Stock Exchange

Australia

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Sensor Based Sorting - Schematic principle

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1 Material feed

2 Vibratory feeder

3 Free fall acceleration

4 Sensor - Line scan camera(s)

5 Data processing

6 Air pressure valves

7 Accept stream

Reject stream

8 Network interface for central control

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Mechanical Design

§ Particle size range 16mm to 250mm§ Simple system without moving parts§ Robust§ Compact design, small footprint§ Ideal for double sided scanning

§ Gems & Diamonds - Particle size range 1mm to 30mm

§ High capacity ROM Sorters – Particle size range 6mm to 300mm

§ All individual particles are traveling with the exact same speed before being presented to sensor.

§ Varying density particles can be handled

§ Suited to Multi-Sensor sorting

Chute based Belt driven

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Product Lines

Run of Mine (ROM) Series

Industrial Processing (PRO) Series

Gem Stone (GEM) Series

l Extremely rugged belt sorters

l +6..-300 mm covered by two models

l Sensors RM, PM, EM and XRT

l Simple and efficient free-fall sorters

l +3..-250 mm covered by four models

l Sensors COLOR, EM and NIR, XRT

l Sophisticated wet/dry sorters

l Precon, Recon and SPS systems

l Sensors XRF, XRT COLOR

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Concentrator:ScreeningMillingFlotation

Tailings (fines) Product

Crushing

Run of Mine

Traditional Mineral Processing

Why Sensor Based Sorting?

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Today's Challenges:

l High Energy Cost

l Water scarcity

l Decreasing Head Grades

l Increased Rehabilitations Costs

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l Rejecting waste rock at early stage:

- reduces transport costs- minimises downstream crushing

and milling requirements- reduce surface tailing dumps

l Better utilization of low grade resources

- recovering misplaced reef- improves mill head grades- Consistent mill head grades

l Reduce usage of chemicals

l Saves energy and water

Concentrator:ScreeningDense media separationMillingFlotation

Tailings (fines) Product

Crushing

Removing waste rocksby sensor based sorting

Waste Rock(mine backfill)

Run of Mine

Mining process with pre-concentration

Sorting integrated in Mineral Processing

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Sensor Based Sorting Applications

Base Metals PreciousMetals

IndustrialMinerals Fuel

IronManganeseCopperZincNickelTungstenSlag

CalciteFeldspar Dolomite TalcQuartz Magnesite Salt

Diamonds Tanzanite Emeralds

Diamonds& Gems

UraniumCoal

GoldPlatinum

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Available Sensors within the Electro Magnetic Spectrum

10-12

10-11

10-10

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

101

102

103

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Ultraviolett (UV)

Visible light (VIS)

Near Infrared (NIR)

Microwaves

X-ray

Gamma-

radiation

Alternating current (AC)

Radio waves

[m]

Infrared (IR)

* Under development

Sensor/Technology

Material Property Mineral Application

RM (Radiometric) Natural Gamma Radiation Uranium, Precious Metals

XRT (X-ray transmission) Atomic Density Base/Precious MetalsCoal, Diamonds

XRF Visible Fluorescence under X-rays

Diamonds

COL (CCD Color Camera) Reflection, Brightness,Transparency

Base/Precious MetalsInd. Minerals, Diamonds

PM (Photometric) Monochromatic Reflection/Absorption

Ind. Minerals, Diamonds

NIR (Near Infrared Spectrometry)*

Reflection, Absorption Base metalsIndustrial Minerals

IR (Infrared cam)* Heat conductivity, heat dissipation

Base MetalsIndustrial Minerals

MW-IR (heating in conjunction with IR)*

Sulfides & Metals heat faster than other minerals

Base/Precious Metals

EM (Electro-Magnetic sensor)

Conductivity Base Metals

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Example 1:South Africa, Witwatersrand GoldWaste Rock Dumps

• Grade 0.3 to 0.9 g/t• Fines -16mm blended

into ROM feed to Mill• Oversize +16mm

stockpiled as waste• Some mines tried hand

sorting• Some mines mill the

entire waste dump• Kloof GM Sorting Pilot

Plant 2003/4

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Containerized Sorter, Kloof Gold Mine, South AfricaOctober 2003 – June 2004

•• Sorting gold reef from waste rockSorting gold reef from waste rock•• Size Range Size Range --80 +16mm80 +16mm•• Feed rate Feed rate ±± 80tph80tph

•• Feed grade 0.3 g/tFeed grade 0.3 g/t•• Sorter Concentrate 5 g/tSorter Concentrate 5 g/t•• Mass pull 5%Mass pull 5%

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Full-Scale Gold Waste Dump Plant

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Dump Sorting Plant Key Data:

l Feed to Plant 180 000 t/m @ 0.7 g/t

l Two Product Streams:

- < 16mm Fines - 99 000 t/m @ 0.9 g/t- Sorted reef plus wash-fines 6 000 t/m @ 6.0 g/t

l Combined Product of 105 000 t/m @1.2 g/t

l Gold Produced 124 kg/m (4 000 oz/m)

l Investment Plant USD 3.5 million

l ROI 6 months

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Example 2:Platinum Sorting at Waterval

•• Sorting UG2 from waste rockSorting UG2 from waste rock•• Size Range Size Range --300mm +50mm300mm +50mm•• Feed rate up to 300 tphFeed rate up to 300 tph•• Waste rejected between 20% & 65%Waste rejected between 20% & 65%

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Example 3:South Africa, North West ProvinceAlluvial Diamonds

• Sorting free diamonds from Recovery tailings dump

• Transparency properties

• -8mm +2mm• 10 to 14 tph• Recovered low/non-

luminescent diamonds

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Near-Infrared (NIR) Spectroscopy

l Widely used in recycling

l NIR Spectrometers used to log drill core

l For Sorting Minerals the technology was adapted to have Ø fast processing ratesØ Higher resolution Ø Extended frequency range

l Two measurement chambers Ø Each record 16 channelsØ 2 different wavelength

l A rotating polygonal mirror scans the passing rockØ an image is created for analysis

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NIR Sorting of White Minerals

•• The NIR reflectance spectra shows The NIR reflectance spectra shows clear differentiation between clear differentiation between Talc, Carbonates and QuartziteTalc, Carbonates and Quartzite

•• Good potential for other Good potential for other minerals e.g. Rareminerals e.g. Rare--EarthEarth

•• More research requiredMore research required

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Röntgenröhre

Einzelkorn

Röntgen-zeilensensor

X-Ray Tube

Particles

X-Ray Line Scan Sensor

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XRT Sorter at Mintek

• Throughput 16 – 40 tph• Size Range -40mm +10mm• Compressed air 55 kW ;pressure 8 bar

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Example 1:Coal de-shaling

Shale – SG +1.7

Coal – SG – 1.3

Sample X-Ray Image Simulation Image

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0

10

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30

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50

60

70

80

90

100

1.2 1.3 1.4 1.5 1.6 1.7 1.8

Nominal SG

Part

ition

Co-

Effic

ient

50% Blue 25% Blue 75% Blue

l Cut-point is controlled by sensitivity of program

Partition Curves X-Ray Sorting Coal/Shale

l At 75% blue a cut-point SG of 1.6 is achieved

l At 50% blue SG 1.5

l At 25% blue SG 1.45

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Example 2.Diamonds

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Example 3:Narrow Vein Sulphide-Type Gold

Flat Vein Swarms

Shale

Dolomite

Quartzite/Shale

Granite

Narrow stopes

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Medium-Grade Sulfide ore

Low-Grade Sulfide Ore

Massive -Sulfide ore

ALGORITHM EVALUATION

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ALGORITHM EVALUATION

Quartzite Waste

Norite Waste

Granite Waste

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XRT Sorting of DMS Floats

l DMS Float = XRT Feed grade ~ 1.3 g/t

l XRT concentrate grade ~ 3.8 g/t

l Mass pull 30%

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XRT Sorting of DMS Floats

l XRT waste grade ~ 0.2 g/tl Mass pull 70%

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Features of XRT Sorting

l Dry beneficiation process

l Potential for coal beneficiation in coarse size -150mm +30mm

l Good results for narrow vein-type sulphide oresØ NickelØ CopperØ Gold/SilverØ Polymetallic

l Excellent detection of Diamonds

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Conclusion

l Sensor Based Sorting is a technology gaining significance in the mining industry

l Proven technology (over 150 sorters in mining)

l Recover value from low-grade dumps and marginal ore bodies

l Physical sorting process – no chemicals, heat

l Placing sorter between mine and mill has numerous benefits

l Mill the Ounces , not the Waste!!

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Thank you for your attention !

Questions???

“With the ongoing further development of sensor technology, sensor based sorting will become established as a standard process for pre-

concentration in the future”Professor Hermann Wotruba, University of Aachen