Metso Minerals Process Technology Asia Pacific and South America

Transcription

1 An introduction to Metso Minerals Process Technology Asia Pacific and South America Australian Coal Preparation Society Technical Meeting 11 th March 2009

2 Metso Minerals Process Technology Asia Pacific and South America Dr Walter Valery VP Process Technology Asia Pacific Laura Parkin / Stacy Butler Administration Adrian Dance Process Integration and Optimisation David La Rosa Process Control and Instrumentation Sarma Kanchibotla VilimSer Kym Runge Mining Technology Flotation Consulting Flotation Research Juliana Colacioppo Manager South America Serkan Dikmen Michael Wortley Silvio Corsini Robert Crosbie Jaclyn McMaster Edis Nunes Soracaba, Brazil Sonny Mwanza Ben Connolly Michelle Treger Raphael Beaudoin Luis Tapia Santiago Allan Allport Rae De Rousset Roberto Valle Lima Peru Reece Canham Kevin Cummings Eduardo Nozawa Soracaba, Brazil 2

3 Metso Minerals Process Technology Projects # of Projects 79 PIO Projects Support Contracts Greenfield Studies Process Control Projects 3

4 Project breakdown Projects by Commodity Coal, Iron Ore 10% Projects by Type Other 8% Gold 37% Base Metals 45% Other 12% Process Control 27% Flotation Opt. Opt 9% Projects j by b Location i Other 36% Asia Pacific 76% 4 Comminution Opt. 40% Projects by j b Mining i i Co. North America South America 2% 14% Africa 8% Blasting Opt. 12% Freeport Freeport Moran 6% Barrick 8% ll BHP Billiton 20% Rio Tinto 12% Newmont AngloGold 11% Ashanti 7%

5 MMPT Process Control Group Vision Based Systems - VisioRock - VisioTrucki - VisioFroth - SmartRip (Commercial Prototype) Cable Belt Control system (installed at AC Dawson and Lake Lindsay) Acoustics - SmartEar Soft Sensors - SmartCharge - SmartSAG Ore tracking - SmartTag RTD activities 5

6 VisioFroth Metso Process Technology Asia Pacific and South America

7 On line measurement of froth properties Real time froth velocity: X and Y components Bubble size distribution Full histogram D50, D80 values Froth stability Bubble loading Color and brightness indexes Mean values, standard deviations, and an almost infinite options for statistical functions of measured variables are available 7

8 VisioFroth : Froth Image Analyser IP Technology OPC or DDE Communication Setpoints OCS DCS PLC Network Cameras in IP68 housing Low voltage lamp illumination in IP68 housing Easy installation and maintenance free Algorithms embedded in OCS software 8

9 Hardware schematic 9

10 VisioFroth Screen 10

11 VisioFroth on intranet 11

12 Microcel Camera Installation 12

13 VisioFroth interface 13

14 Yes, some maintenance is required. 14

15 Typical rules Velocity SP ~ Mass Pull Set manually by operator as ash in tails not available on-line Σ OCS Velocity Control Cell Velocity Microcel with VisioFroth Frother Dosage 15

16 Response of velocity to frother addition 16

17 Some results Freq quency Mass Yield Before and After OCS Installation 9% 8% Pre-OCS (Oct-Nov Data) Post OCS (Feb-Mar Data) 7% 6% 5% 4% 3% 2% 1% 0% 0% 20% 40% 60% 80% 100% Concentrate Recovery Mass Yield (%) Before OCS After OCS Ave SD Ave SD Coal Recovery (%) Ash Recovery (%) Before OCS After OCS Before OCS After OCS Ave SD Ave SD Ave SD Ave SD Feed Concentrate Tailing

18 VisioFroth References Coal Applications BMA Peak Downs 5 Cameras BMA Gregory 4 Cameras BMA Saraji 8 Cameras BMA Blackwater 6 Cameras Some of our metalliferous applications Anglo Platinum Klipfontein, South Africa Impala Platinum, South Africa Rio Paracatu Rio Tinto, Brazil Troilus Inmet, Canada Kemira Oy, Finland Freeport, Indonesia Cameras Los Pelambres, Chile Codelco El Salvador, Chile Kennecott Copperton, Utah USA Escondida Phase IV, Chile Cameras Northparkes Mines 7 Cameras Mt Keith 1 Camera Telfer 28 Cameras Codelco Andina Antamina, Peru 18

19 SmartTag Metso Process Technology Asia Pacific and South America

20 MMPT AP s Typical Mine To Mill Approach Blast Design MMPT Blast Fragmentation Model Ore Characterisation Lithology zones Rock Strength - PLI - DWi, A x b, ta - Wicr, Wibm, Wirm, Ai Rock Structure - RQD, FF, Mapping ROM Ore size Distribution When will this material enter the concentrator? Primary Crusher Model SAG Feed Size Distribution Particle Size (mm) Grinding Circuit Models TPH Final grind size Mineral recovery Flotation Models

21 Tracking Ore from the Mine to the Mill Ore Type 1 Ore Type 2 Crusher f(x,y,z) Stockpile or ROM Pad or both? f(t) Concentrator

22 Stockpiles and ROM Pads Used for blending of material Residence time variable Can range from minutes or hours in the case of a stockpile depending on level, to months or years in the case of ROM pads How do we make the connection between spatial data f(x,y,z) to temporal data f(t)

23 Why do we need to track ore blocks? Ore blocks with quite different grade, structural and hardness characteristics can exist in close proximity to one another Multiple ore sources Tracking ore allows: - More accurate reconciliation - Ability to change operating parameters in response to actual ore characteristics not just the average - Quantification of ore dilution and loss (with some assumptions)

24 Marking Ore Blocks Radio Frequency ID tags are microchips with an integral antenna - can be detected from up to 1m (non contact) and require no power Each chip can be read only or read write and have a unique identifying number encoded on them - 18,446,744,073,709,551,616 different combinations By hardening them in a robust shell - can then be inserted into the blast stemming - their initial position surveyed and stored - detected as they move through the primary crusher, stockpile and finally into the processing plant

25 RFID Principle of operation

26 SmartTag Variants 26

27 SmartTag Hardware Layout TAG ANTENNA SOLAR PANEL FOR REMOTE INSTALLATIONS WIRELESS COMMUNICATIONS LINK OR DIRECT NETWORK CONNECTION CONTROL SOFTWARE AND DATABASE SmartTag 12VDC/120/240 VAC *not required if solar option installed TAG READER

28 Typical Antenna Locations MUCKPILE ROM PADS [ID, x, y, z] DETECTOR CRUSHER [ID, t] STOCKPILE DETECTOR [ID, t] SAG MILL FEED

29 Crusher Product Installation

30 Inserting into Stemming and Logging

31 Inserting into stemming

32 Some case studies

33 Tag arrival times during a survey of two grinding lines 14 Arrival times of tags at Los Colorados During Survey 3 12 Linea 1 Linea 2 Survey 10 8 Tag /04/ :00 21/04/ :00 22/04/2007 0:00 22/04/2007 6:00 22/04/ :00 22/04/ :00 23/04/2007 0:00 Time

34 Stockpile blending 35 Arrival Times of tags from S7, S9 and Z Stockpile S7 Stockpile S9 Z8 Tag number Mon 08 Sep Mon 15 Sep Mon 22 Sep Date

35 Stockpile residence times 12 Transit Time through Stockpile 10 8 of Tags Number Time (Hours)

36 Correlating throughput with material source 'Low' throughput 'High' throughput Thro oughput (tph) Ta ag number SAG Tonnage Detected Tags Jan 00:00 15-Jan 12:00 16-Jan 00:00 16-Jan 12:00 17-Jan 00: Jan 12:00 Time

37 Linking blast implementation with Mill Performance

38 Thank you