Automation for non-ferrous Metals

PresenterNeil Freeman

Honeywell

2

Agenda

• Value Proposition• Case Studies

- Process Improvements- Business Improvements- Asset Effectiveness- People Effectiveness

• Summary

Value Proposition

4

Market Characteristics

• Cyclical pricing• Downward pressure• Consolidation (eg BHP Billiton, Rio Tinto)• Responsible attitude amongst producers• Need to work ‘Smarter’

Copper LME Cash Pricing

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Date

$US/

Tonn

e

Copper LME Cash Pricing

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Date

$US/

Tonn

e

5

ERP

CostingMaterial

ManagementProductionPlanning

Sales andDistribution

QualityManagement

PlantMaintanance

Manufacture Execution System

DCS

Production History Database and Work Center

OperationManagement

OperationScheduling

OperationTracking

ERPIntegration

DVM

NETWORK

ServerStation – Logical Console

ACE

AssetManagement

The Process

Plant Fire and Security

The Smart Control Advantage

Maintenance

Recovery YieldThroughput

MaterialConsumption

ReagentConsumption

Energy

Labour SafetyWorkforceSkills

EnvironmentQualityCosts

IncidentAvoidance

Process Improvements

7

Advanced Control

Economics and IdealTarget Values

DisturbanceValues

ControlVariables

ManipulatedVariables

Product ValueOptimization

RMPCT Algorithm

8

Control ImplementationOre Bin

Spent liquor to oversize hopper

Spent liquor to mill feed

DSM Screen

SAG Mill

LCDHT3

SC

FCSLFE3

FCSLOH3

FIMP31

DCMP3

Sump

WCM3

Mill Load

MPC

FCSLT3

FCSLMD3

Spent Liquor

Spent Liquor

WCBM3

ZXMFC3ST

LCBST3

Slurry Density

Slurry Flow

Bauxite feed rate

JCM3

MillPower

Spill TrayIndicator

9

Control Matrix

10

Benefits

• On/Off tests• Nominally 12 hours• Analysed by overall average• Operators mimicked controller actions

11

Performance Tests

Controller ON Controller OFF

Average Throughput (wtph) 588.0 579.3

Sample Number 5007 6853

Mean Difference 8.7 wtph (1.5%)

95% Confidence +/- 11.6 wtph (+/- 2.0%)

Off/On Cycle

Mea

n Fe

ed tp

h P

V

0 5 10 15 20 25 30

500

520

540

560

580

600

620

on

on

on on

onon

on

on

on

on

on on

on

on on

on

onon on

on

on

on

on

onon

on

on

on

on

on on

on

off

off

off

off

off

offoff off

off offoff

offoff

off off

off

off offoff off off

off

off

off

off

off

off

off

off

off

off off

off

12

Non Quantifiable Benefits

• Reduction in mill spills• Decrease in hose water (illegal dilution)• Record mill throughputs• Stabilisation of mill operations• Acceptance from control attendants

13

Long Term Trend

Wagerup Daily Averages3 Day Rolling for Feedrate

480500520540560580600620

1 14 27 40 53 66 79 92 105

118

131

144

157

170

183

196

209

222

235

Days since 19/4/99

TPH

SmartGrind Commissioned

Over 9% Improvement Indicated

Business Improvements

15

What is MES ?

• MES is an Integrated Software System- It links operations on the plant floor to business processes

tracking customer orders, production costs and material inventories and KPI’s.

MES Key Functions - Data collection - Product/material tracking- Document control - Quality management- Performance analysis - Maintenance Support- Resource allocation, status and synchronization- Operations scheduling and dispatching- Labour management

Automation(Level-1 Controller)

ERP

MES(Manufacturing Execution System)

TIME FRAME

Days Months

HoursShiftsDays

SecondsMinutes

PURPOSE

OptimiseRevenue &

Profit

OptimiseProduction

Control & Stabilise

Production

16

WMC ODO Process

UndergroundMining

Precious MetalsRefining

Copper RefiningSmelter

Milling/Concentrator

SurfaceStockpiles

HydrometUranium Oxide

Gold & Silver

Copper

Tailings

17

Production Balance Objectives

• Integrated Metal Balance for Operations-Mining to final metal

• Consistent methodology for metal balances• Improve metallurgical reconciliation time

18

Balance Scope and phases

UndergroundTonnes

Factorisation

UndergroundGrades

Reconciliations(5)

Hoist TonnesBalance

ConcentratorMetal Balances

(4)

Hydromet MetalBalances (4)

Hoist ComponentBalances(5)

Smelter MetalBalances(4)

Refinery MetalBalances (4)

Precious MetalsBalances(4)

Component BalanceSequential by metal

Simultaneous by area

Implemented

Planned

19

Overview

Plant Metal Balance - Overall Plant

Link Name

LEGEND

12100SP0001

(Mill Stockpile)

24220GM0003(Svedala Mill)

21S101

21S1023

4220GM0005(Fuller Mill)

44200HDER0001(Mill Header)

424220RG0001

(Slag Regrind Mill)

42

RG

01

42G501

42G301

144700SLG0001

(Mill Electric SlagStockpile)

74600CLCH0001(Concentrate

Leach)

54200CONC0001

(Mill Concentrator)

42HD01

42CO01

64200TAIL0002(Mill Tailings)

42

CO

02

44EW02

84311FPRP0001

(Feed Preparation)

94311POND0001

(Feed PreparationPond)

46

CL0

1

43

PD

01

47

SL0

1

48T141

43FP02

43

FP

01

43EF03

43

S1

01

194300SA0001

(Smelter #1 Anodeson Pad)

43

S2

01

164300SF0001

(Shaft FurnaceSmelter #1)

184300RS0001

(Smelter RefineryScrap)

114300SS0001

(Smelter ScrapBunker)

104300FF0001

(Flash Furnace)

154300AF0002

(Anode FurnaceSmelter #2)

204300SA0002

(Smelter#2 Anodeson Pad)

174300SA0003

(Smelter RefineryRejects)

124300EF0001

(Electric Furnace)

134600SLG0001

(Revert Stockpile)

214300AM0001

(Anode Moulds)

46

SL0

1

43

EF0

2

43EF01

43FF03

43EF04

44

TH

02

44ER02

43FF04

43FF02

43

SF0

1

43RS02

43SS01

43

FF0

1

43

AF0

2

43

AM

01

43S301

44

RA

05

43

RS

01

44ER01

43

FF0

6

43FF07

43FF08

43

SF0

24

3S

10

2

43

S2

02

43

S2

03

44

EW

03

584300HDER0001

(Electric FurnaceHeader)

43

HD

01

43

HD

02

364400HDER0001

(Tails LeachHeader 1)

374710CUSX0001(Copper Solvent

Extraction)

355000TD0001

(Tailings Dam)

494450PCK0001

(Uranium PackingShed Inventory)

344411TLCH0001

(Tails Leach Stock)

42TA01

44

TC

01

44

TC

03

44HD02

47CU01

44PB01

44

TC

02

44US05

384450USX0001

(Uranium SolventExtraction)

44AD0139

4450ADU0001(Ammonium Di-

Urinate)

404450PB0001

(Uranium ProductBin)

44US01

50

TD

01

44HD03

47CU02

41U_IN_TRANSIT

(Uranium inTransit)

44PK01

44HD04

44HD05

46

CL0

3

44US02

44

US

03

44US04

44EW05

44

TC

04

47CU03

554440HDER0001

(Uranium SolventExtraction Header)

44

HD

06

47CU04

44HD08

44HD07

294400ER0001

(ER Cathode Stock)

324400EW0002(EW Cathode

Stock)

314400EW0001

(EW Tank House)

224400RA0001

(Refinery AnodeSmelter #1)

244400RA0003

(Total refineryRejects)

254400TH0001

(ER Tank House)

264400RS0001

(Refinery Scrap)

284810TK0014

(Refinery BleedHeader) 30

ER_IN_TRANSIT(ER in Transit)

33EW_IN_TRANSIT(EW in Transit)

564300AM0002

(Anode Moulds)S3

574300AM0003

(Anode Moulds)5U

49AU09

44TH06

444900AU0001(Gold Room)

434900SL0001

(Slimes in BatchTanks)

49AU07

49AU08

49

SL0

4

49AU01

49AU02

49

SL0

2

49

SL0

3

49AU10

49

SL0

1

47AG_IN_TRANSIT

(Silver in Transit)

454900BL0001(Gold Silver

Bullion)

46AU_IN_TRANSIT(Gold in Transit)

49BL01

49BL02

49AU05

49AU0349AU04

49AU06

43

S1

03

43

SF0

3

44

RS

01

43SS02

43

FF0

5

44EW04

44EW06

44

EW

01

44RA03

44

RA

01

44TH03

44TH01

44TH06

44TH07

44TH08

44TH05

SIZE DWG NO REVA3 5300054-DWG-324-PLANT R6

SCALE N/A SHEET 1 OF 6

A.C.N. 000 646 882

ODO PID Project

Equipment NoEquipment Name

(Descriptor)Concentrator

Equipment NoEquipment Name

(Descriptor)Smelter

Equipment NoEquipment Name

(Descriptor)Refinery

Equipment NoEquipment Name

(Descriptor)Hydromet/Tailings

Equipment NoEquipment Name

(Descriptor)Gold/Silver

46

CL0

2

20

Production Balance©

21

Results

• Month end reporting speed• Consistency of results

- Data integrity- Reliability- Understanding- Audit capacity

• Input integrity- Measurement bias- Data collection processes- Calculation processes

Asset Improvements

23

Assets

• Alarm Management• Loop Management• Maintenance Analysis• Root Cause Analysis

EHM

EHM

Equipment H

ealthM

anagement

ASM

ASM

Abnorm

al Situation M

anagement

24

Asset Tree Map

25

Asset Tree View

26

Loop Performance Monitoring

Performance ClassifiedThree ways:

1. All loops in dataset

2. For each unit

3. For each loop type

4. Summary by Performance

27

Root Cause Analysis

People Improvements

29

Training Simulation

TraineeTraineeOperatorOperatorStationsStations

RemoteRemoteFunctionsFunctionsConsoleConsole

PrinterPrinter

EngineerEngineerConsoleConsole

ModemModemPrinterPrinter

SimulationSimulationComputerComputer

30

25 Tanks

47 Pumps

75 Control valves

100 Other process equipment(eg. Heat exchangers, cyclones)

1100 Controllers - 3000 Points

± 2% Accuracy

Bright Hydrate Model

31

Justified on extra production of KHN-30

Reduced commissioning time by 21 days

Reduced off-specification product by 50%

Once off revenue increase of several million dollars

Hard Benefits

32

First principals model based on chemical and kinetic properties

Valve repositioning

Vertical filter operation

Verification of operating procedures

Soft Benefits Design Verification

33

6 training modules (4 hours each)

120 training sessions held

5 shift crews

500 hours operational experience prior to start up

Operators learn

Process Flowsheet

Process Dynamics

How to control process

Soft Benefits Operator Training

34

Controller tuning prior to commissioning

Regulatory control scheme tested

Displays pre-commissioned

Control available for operator training

Enhanced control schemes tested and commissioned

Soft Benefits Control Configuration

Summary

36

Downtime reduction and avoidance

Reduce Waste Basic Technical SupportProcess Target Accuracy

Improved Production (more tons)Upgrade costSoftware Support CostCustom Software and Hardware

Requirements & justification analysisWork Process improvementProcess Target Accuracy

Upgrade costSoftware Support CostCustom Software and Hardware

Advanced Regulatory ControlInfo Application DevelopmentCustom Software and Hardware

System configuration accuracyDocumentation

System configuration accuracy 0.2DocumentationOpen Systems Software Support Tighter Molar Ratio Control

Custom Software and Hardware System and application integrationInventory Costs

Reduce WasteAdvanced Process Control Information Integration

Reduce WasteProcess OptimisationInformation IntegrationConfiguration cost savingsInformation IntegrationSystem and application integrationLower Unified Solution Cost

Work process ImprovementReduce Caustic UseEnergy reductions

Knowledgeable, Empowered Workers

Typical Cumulative Benefit Contribution

Work ProcessImprovement

DowntimeReduction &Avoidance

Quality &Manufacturing Plan vs Actual

Tighter Energy Control

Reduced Reagent Usuage

The Result

160,000$4,300

20%

Low Medium High2% 4% 6%

Margin Contribution ($/y) $2,752,000 $5,504,000 $8,256,000Margin Improvement ($/t) $17.20 $34.40 $51.60

Margin (%)

Benefit (%)Benefits

Typical Improvements in CopperOperation size (TPY)Copper sell (US$/Tonne)

37

Conclusions

• Significant benefits are achievable through- Process Improvements- Decision Support- Asset Utilisation- People Effectiveness

• Best Practice uses an integrated solution• Millions $ per year benefits

Thank You