FINES CIRCUIT DESIGN AND PERFORMANCE ENHANCEMENT ELEMENTS IMPACT ON PRODUCT VIU

Transcription

1 FINES CIRCUIT DESIGN AND PERFORMANCE ENHANCEMENT ELEMENTS IMPACT ON PRODUCT VIU

2 Presentation Summary Overview of Fine Circuit challenges Fines Circuit design data generation o Sample treat techniques and data repair o Analytical loss attribution impacts o Laboratory flotation data challenges Design and Performance considerations o Factor affecting design and performance o Recirculating frother example o Recirculating slimes product quality impact o Bottom size selection aspects Value in Use Impacts o Coking coal scenario o Thermal coal scenario 2

3 Fines Circuit Challenges Overview Historical Discarding of Excess Fines Borecore pre treatment procedures & fines loss attribution Flowsheet design considerations Evaluation of all resource data and product options Total plant design value adding Value assessment models (Value in Use linkages) Maintaining expected throughput Avoiding penalties Inadequate beneficiation i technologies Achieving(budget) production targets Issues & Problems in Fines Processing Inadequate fines circuit design Insufficient or incorrectly pre treated t ddesign dt data Throughput bottlenecks, avoidable coal losses, dewatering issues, etc. Product handling, contractual al penalties Solutions & Rewards from Fines Processing 3

4 Fines Circuit Design Data Generation Aspects

5 Fines Circuit Design Data Generation Crushed Drill Core Data generates an unnatural liberation state (not representativeof run of mine coal) Applying Liberation and Circuit Segregation Models to Crushed Data can transform it into pseudo pre treated washability data Best practice is for samples to be drop shattered with wet pre treatment (simulates natural breakage occurring during mining / CPP operations) This is the only reliable way to deliver realistic data from borecores to model fines circuit yield and ash 5

6 Analytical Loss Attribution Aspects Fine particles are commonly lost tduring laboratory lb pre treatment t tprocesses. Important to attribute laboratory processing losses correctly to deliver accurate data for design the fine coal circuit. Determine ARD Drop / shatter 20 times. Dry 31.5mm Hand Knap/Size Adjust to pass 31.5mm. Loss Occurring Loss Occurring Dry 16.0mm, 8.0mm, 4.0mm and 2.0mm. Loss Occurring RSD RSD 1/4 3/4 Raw Coal Analysis Wet Tumble for 5 Minutes with cubes. Wet 16.0, 4.0, 2.0, and 0.125mm Loss Occurring 6

7 Under Estimating Fines Generation Percent Undersize It is very important to carry laboratory processing losses across all pre treatment phases to correctly model the proportion that will report to the fine coal circuit Generation of samples with a representative plant feed size distribution can only be carried out with drillcores via the application of pre treatment tests, such as Loss Corrected Wet Tumble Size drop shatter Inadequate Loss Corrected dafter Wet-Tumble and wettumble Dry Sizing 1 testing Size (mm) 7

8 Lab Scale Flotation Data Challenges Non selective lab lbscale flotation data over states ash. Need actual representative sample for CCComps. Need realistic yield / ash data for plant design envelopes. Lab scale column cells offers reliable pathways to resolve these challenges. 8

9 Fines Circuit Design and Performance Aspects

10 Some Factors Affecting Fines Circuit Performance Fines Circuit Design Aspects Frother recirculation (Use of available water streams) Slimes recirculation (Selection of stream direction and water balance) Optimum feed presentation (Desliming and loading) Upstream and ddown stream unit capacities Fit for purpose beneficiation and dewatering equipment Bottom size selection (to maximise yield and quality) Performance Optimisation Influences Slimes recirculation (Classification efficiency i and water clarity issues) Optimum feed presentation (Desliming efficiencyand volume / solids stability) Misplacement of coarse particles (Classification efficiency issues) 10

11 Recirculating FrotherExample Correct frother recirculation uses available froth laden water streams within the flotation circuit where possible. Enables maximum effective frother dosage rates. Desliming Screen Underflow 1.4wwmm Desliming Cyclone 0.250mm Jameson Cell 1.4ww+0.250mm Sieve Bend HBF Product Tailings Thickener HBF Filtrate Spirals Tailings Reject Product Flotation Feed Sump Frother Laden Stream 11

12 Recirculating Slimes Product Quality Impact Limited ability to beneficiate the 100 m material, slimes component follows water flows throughout h the plant. Figure illustrates inability of a typical TBS (or Spiral) to successfully beneficiate particles <100 m in size. 80 CUMULATIVE ASH by PARTICLE SIZE Cumulat tive Ash (% Minimal difference in cumulative ash between feed and product streams for particles < 100mm Teeter Bed Feed Teeter Bed Product GMS Particle Size (mm) 12

13 Some Fines Dewatering Comparisons Common Device Advantages Disadvantages Rotary Vacuum Moderate capital and operating costs Horizontal Belt Filter Dewaters all size fractions Higher TM in cakes (HBF) Hyperbaric Disc Filter Dryer cake moisture Dewaters all size fractions Higher capital and operating costs Screen bowl Centrifuge (SBC) New Dewatering Technologies? Coal thickeners Dryer cake moisture Lower capital costs TBC Maintains thickened feed to dewatering devices Can handle significant fluctuation in flotation response Does not dewater 0.030mm material Treatment of effluent required TBC Affected by performance of dewatering devices High capital cost Flocculant dependant 13

14 Bottom Size Selection Impacts 80 Product CV (nar) vs. Estimated Revenue per ROM tonne 0.5mm Bottom Size (DMC & Spirals) mm Bottom Size (DMC & Spirals) Revenu ue (AUD$/RO OM tonne) mm Bottom Size (DMC & Spirals) 0.125mm Bottom Size (DMC & Spirals) 0.063mm Bottom Size (DMC & Spirals) Deslimed Flotation mm (DMC, Spirals & Flotation) Deslimed Flotation mm 24.5 (DMS, Spirals & Flotation) Product CVnar (MJ/kg) 14

15 Value in Use Impacts NOTE: Higher quality product doesn t always deliver the best whole of resource revenue position o o Due to such factors as relative customer location and coal price able to be realised This assessment is intended to provide insight into VIU impacts from coal quality variations only and may not be the optimum whole of resource outcome

16 Coal Quality Improvement Coking Coal Potential ti lcoking Coal limprovements CSN Increase 1.0 Vitrinite Increase 10 % Ash Reduction 0.8% Coal quality improvements can significantly affect market position against world traded dcoking coals Position of coal has improved compared to world traded coals Improving CSN and vitrinite improve coke quality Lower ash product will allow blending with higher ash coals which will benefit customers 16

17 Utilisation Impact on Coke Quality CSR is an important parameter in the assessment of value of coke CSR can increase if coal quality is improved Improvement in CSR has allowed the SSCC to be classified as SHCC A significantly greater number of coals satisfy SSCC constraints than SHCC (SSCC market more competitive) However, various grading of coking coals are used but there are no universally accepted suite of technical specifications 17

18 Location of Steelworks Coking Coal Trade Ex 150Mt Ex 60Mt Ex 15 33Mt Ex 2 2.5Mt Im 0 2Mt Im 2 10Mt Im 10 50Mt Im 50 Mt+ Large number of coals can satisfy SSCC requirements Consequently more competition in this space Upgrade to SHCC Potentially larger number of potential customers 18

19 Coking coal pricing Pricing indices dependenton CSR Platts coking coal indices highly dependent on CSR Increase in CSR may attract US$1.5/t increase in price (2015 Platts model) Higher value coals can travel further and expand market share potential CSR predictor under development by GlobalCoal (Online Trading Company) which may result in stronger linkage to product quality and CSR 19

20 Coal Quality Improvement Thermal Coal Potential limprovements Calorific Value Increase 200kcal/kg Ash Decrease 0.8% Coal quality improvements can significantly affect market position against world traded thermal coals Position of coal has improved for energy and ash as compared to competing coals Potential coal price improvement $2/t (A&B Mylec pricing model) 20

21 Power Plant Suitability Power plants have coal design specifications. E.g. CV, ash, and moisture Blending is common place Improvement in coal quality may result in satisfying specs for new potential ti customers. If energy exceeds spec, coals may be used as blends. Blend with lower quality Indonesian or domestic coal Decrease in ash will assist plants with expensive ash disposal costs. Producer can now trade in new identified markets. 21

22 Power Plant Locations 100+ Mt Import Mt Import Mt Import 1 10 Mt Import 0 1 Mt Import 0 Mt Import 0 1 Mt Export 1 10 Mt Export Mt Export Mt Export 100+ Mt Export Power Plant

23 Value in Use of Thermal Coal Typical Indian power plant simulated General trend of decreasing Generation costs as coal energy increases. Other coal quality parameters can have a significant effect on generation costs (Hence observed scatter) Shows a decrease of $0.25/MWh in Generation costs. Equates to $1.4million pa for 800MWplant. Higher coal price can be negotiated as power plant will achieve lower generation costs. Higher value coals can travel further and expand market share potential.