© Cop yr ig h t 201 4 OSIso f t , LLC .

Presented by

Are you really using your information to increase

the effectiveness of assets and people?

Osvaldo A. Bascur, Metals Industry Principal, OSIsoft, LLC.

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Competence Centers

Further work: Cloud

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Early work and challenges

Current Forcing Factors

What is being done?

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Where is the ‘PI System’ Used in Metals and Mining?Coal and Energy

• Alpha Natural Resources

• BHP Billiton• Cameco• Consol Energy• Energy Coal• Glencore• Murray Energy

Corporation• Peabody• Rio Tinto Coal• Sasol• Suncor Energy• Syncrude• Xstrata Coal

Iron Ore

• Arcelor Mittal• BHP Billiton• CAP• CLIFFS• Companhia Siderurgica

Nacional• Dongbu• Rio Tinto• SeverStal Resurs• TATA Steel• Usiminas• Vale

Copper

• Anglo American• Aurubis• BHP Billiton• Chinalco• Codelco• Escondida• Glencore• Freeport-McMoRan• Grupo Mexico• Ivanhoe Mines• Kennecott Utah Copper• KGHM• Rio Tinto• Southern Copper• Sumitomo Corporation• JianChi Copper

Nickel, Zinc, Lead and Silver

• Asturiana de Zinc• Grupo Paranapanama• KGHM• Glencore• Nyrstar• Penoles• QNI• Teckcominco• Vale• Votorantim

PGM and Gold

• Anglo American• Anglo Platinum• Barrick• Cameco• Goldcorp, Inc. • Umicore• Newmont• Kinross• Oceana Gold• Gold Fields

Diversified and Other Mining Companies

• Aditya Birla Group• Alcoa• Anglo American• Bhpbilliton• Cemex• Climax Molybdenum• Dubai Aluminum• Glencore• Italcementi• Hydro• Logan Aluminum• Mosaic• Rio Tinto

Mining Mineral Processing Metal Processing Product Manufacturing

Upstream Midstream Downstream

Energy/Water In Mineral Processing Plants

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Mining and Mineral Processing Forcing Factors

• Falling Ore Grades• Rising Energy Costs• Ore Type Variations• Remote Operations• Safety and Environmental Regulations• Water• Labor Costs • Rapid technological changes

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TailIngs

Dam

PRIMARYCRUSHER

4%

SAG Mill, 21 % Ball Mills, 31% Flotation

, 14 %

ThIckeners,

5%

Crushing andMilling, 58%

MINE,3%

Flotation, 23%

Oth

er, 7

%

Infra

stru

ctur

e an

d W

ater

, 8%

Oth

er, 7

%

Infra

stru

ctur

e an

d W

ater

, 8%

Electricity consumption in copper mineral processing

MINE,3%

Process AnalyticsRobotics

RemoteSensors

SmartSensors

Advanced Process Control

Continuous Video Monitoring

LearningOn-demand

OfflineDecisionMaking

MobileApps

ModernDesign Tools

BigData

Cloud Based andCollaborative Technologies

New Tools and Technologies in the 21st Century

Information – A Key Enabler for Manufacturing Excellence

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New Technology Enables Improved Productivity through Employee Engagement and Enhanced Functionality to the Business Operating System

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What If Your Company had the Ability to Leverage Its Current Data Assets to…

Improve Enterprise Visibility and Management (Operating

System)

• Establish and Automatically Report Standard KPIs to Measure Performance

• Support Operations through Global and Regional CoEs(Centers of Excellence)

• Drive Real-time Action in Support of Operational Excellence

• Rapidly Identify and Leverage Best Practices

• Increase Employee Engagement with Continuous Improvement Innovation

Improve Awareness and Forecasted Impact of

Uncontrollable Factors

• Rising Energy Rates• Rising Raw Material Costs, Reduced Raw Material Quality

• Rising Water Rates• Rising Labor Rates• Cost of Environmental Regulation / Mandates

More Directly Impact Controllable Costs / Performance

• Continuously Improve Process Productivity / OEE

• Better Control Product Quality / Improve Genealogy Tracking

• Extend Life of Critical Assets / Reduce Maintenance Costs

• Reduce Energy / Raw Material / Natural Resource Consumption

• Continuously Improved Environmental Performance to Meet Regulatory Compliance and Reporting Requirements

Who drives the Value?

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- Operators leverage critical information when and where is needed in the field- Process Engineers develop ad-hoc analysis and “Best Practice” process

- And Visualization standards to improve location production management- And performance

- Supervisors and Area Managers review real time KPI and have drill down - Capability for root cause analysis and problem resolution

- TICoE leverage “Best Practices” analysis and visualization standards - Across the business for “Power Comparison”, root cause analysis- And improved performance

- Business Leadership is insured of timely, accurate and consistent information- For evaluating performance improvements and driving decisions

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What would be the Results?

Improve Operating Cost Position• Reduce Sustaining Operations Cost / Improve Productivity• Reduce Working Capital (Inventory)• Improve Supply Chain Options / Performance

Increase Revenue Stream• Improve Overall Production Capacity / Quality• Improve Capacity / Mix of Higher Margin Products• Increase Asset Availability

Reduce Capital Requirements• Reduce Sustaining Capital Requirements• Reduce Capital Requirements for Information Solutions / System

Integration

The Evolution of the OSIsoft ‘PI System’

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• Deployed in Support of Defined Process / Project Initiatives

• Provides Process Historian Functionality

• Component Pricing / Purchases

• Provides an Information Infrastructure

• Deployed as Data Foundation for the Plant / Enterprise Operating System

• Software / Services Purchased as Enterprise Agreements

What is Driving the Growth with Existing Customers?

Large Metallurgical are large cities

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Metallurgical Complexes

EquipmentAssets

Gas and Electric

Water and

Wastewater

Raw Materials

Process Systems

Material Inventories

Process Productivity / OEE

Optimize Asset Life / Reduce Maintenance Cost

Reduce Energy / Raw Material / Natural Resource Consumption

Environmental, Health, and Safety

Product Genealogy / Quality

Compliance and Reporting

Initiatives for Ore Types, Energy, Water and Metals Recovery

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Harder andVariableOre

IncreasedEnergyConsumption

Sag MillingConcentrate

IncreasedWaterConsumption

MetalProducts

Time

Local vs. Collaborative Decision Making

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KPI Examples: Production, Quality, Costs, Equipment Availability, Environmental and Safety alerts with fast resolution and improved decision making.

Continuous Improvement and Innovation

MONITOR

In Control?

Identify RootCauses

Yes Yes

NoNoKPIs ->

Local Operations/Maintenance

MONITOR

In Control?

Identify RootCauses

YesNo

IMPROVE

EstablishAlternatives

Satisfied?

Operations/Maintenance

Strategic Competence CentersMaintenance/Engineering/Management

Mines, Mills,

Smelters, Refineries

²Min

$$

TechnologyChangeBehavior

OneCenter

Information as an Enabler for the Business Operating System

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The Infrastructure serves as a foundation for competitive advantage through:

With common data, talent across the globe will engage in collective innovation and the pursuit and sharing of best practices. The SMART architecture allows for the rapid deployment of ‘Best Practices’ through leverage of a common computing infrastructure

People Engagement & Best Practice

Process Measurement (KPI) Sharing a common language with other plants will allow us to truly realize Enterprise Advantage. A discovery in one plant can result in procedure, training, and policy changes in the other plants. SMART measures will become common measures. They will allow us to share best practices from one plant to another. Conventional manual data entry / transfers will be reduced.

Continuous Improvement

Better Results

Competence Centers:

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ORE

WATER

CONCENTRATE

ENERGY

EQUIPMENT

The Mining, Mineral and Metals Industries

Mining Mineral Processing

MetallurgicalProcessing

MetalRefining

MetalManufacturing

Asset Optimization

Costs Reduction, Energy, Water, Environmental,

COMPETENCE CENTER Knowledge and Collaboration Data Integration, Validation, Event Frames and Notifications

ISO50001S95

Benefits of the Center Monitoring Diagnostics

• Common model for the operational and maintenance of the processing plants

• On-line expert support distributed for the operations and maintenance

• Transmitting core best practices to the operations• Maintain internal know how• Technological center of operational excellence

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Transforming Data into Actionable Information

Zero SpanCommunications

Low HighFlow Compensation

If ( F>200 and T>100 Then ST=OKIf ( F < 200) Then ST = Trouble

Model PREDICTIONS

Debottleneck

Data Acquisition

Data Validation

Classification &Analysis

Model Selection

Coordination

HIERARCHY

Data History

Events

Actionable Information

Predictive Analytics

Leveraging Mine Mill Integration and Advanced Analysis

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Integrated Mineral Processing

Ore Type 2

Ore Type 1

Grade

Recovery

Optimize Efficiency

OptimizeRecovery and Grade

Optimize Recovery

Optimize Grade

Grade Recovery Maps

Grade Recovery Performance Management

Southern Peru Copper: Cuajone

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Cuajone Production 87,000 MT fine Copper per day. Conventional open-pit mine Concentrator - 10 Grinding Lines.

Traditional Strategy for Grade Recovery Optimization

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TraditionalData Handling

Interface Mining SCADA

DISPATCH(Ultimos datos: )

Round

29/11/2001 20:06:39 418

Meteorización31316

pHDureza

Cu soluble %

Cu %Au g/t

5

0,09

Tipo de roca

4 - Pórfiro P23 - Pórfiro P3

5 - Pórfiro Los Amarillos6 - Andesita9 - Andesita Rubble Zone

Tipo de roca 1°

Tipo alteración

2 - Cuarzo-Magnetita1 - Potásica fuerte

3 - Epídoto-Clorita4 - Fílica5 - Argílica

Meteorización/Enriquecimiento

2 - Completamente meteorizada/alterada. Roca descompuesta y friable1 - Suelo residual. Fábrica original, destruida

3 - "Zona de Lixiviación" No visible Pyrita/Calcopirita.Alta meteorización/alteraciónRoca decolorada y de reducida resistencia por meteorización

4 - "Zona de enriquecimiento" Visible Calcosina/Covelina. Moderada meteorización/alteraciónRoca decolorada, pero su resistencia poco afectada solo en discontinuidades con meteorización

5 - Suave meteorización/alteración, resisrencia inalterada,meteorización solo en diaclasas6 - Fresca e inalterada. Alteración puede resultar en una mayor competencia de la roca (ej.silicificacion).

Dureza de roca

2 - Roca muy blanda1 - Roca extremadamente blanda

3 - Roca blanda4 - Roca de media a dura5 - Roca dura6 - Roca muy dura

3% Tipo de roca 1° 91,1Tipo de roca 2° 6% Tipo de roca 2° 8,9

7,614

0,75

0,84

Datos de mineral de mina al chancador, actualizado por hora.

Leyes Cu-Au-Cu soluble 01/12/2001 13:46:55

15:00 17:00 19:00 21:00 23:00 1:00 3:00 5:00 7:00 9:00 11:000,

1,6

0,

1,6

0,

1,

Round-Tipo de roca . 01/12/2001 13:46:55

15:00 17:00 19:00 21:00 23:00 1:00 3:00 5:00 7:00 9:00 11:0020000,

35000,

0,

6,

0,

6,

0,

100,

0,

100,

Round-Dureza-pH-Meteorización 01/12/2001 13:46:55

15:00 17:00 19:00 21:00 23:00 1:00 3:00 5:00 7:00 9:00 11:0020000,

35000,

0,

7,

5,

10,

0,

6,

Tendencias de las últimas 24 horas - Hacer doble click para ampliar

Ore Type Events

GPS

Mine Planning

Round #

Rock Type

Hardness

Operational Unit Events

Production

Production time

Production target

Startup Shutdown

Reduction

Running = Key Variables within acceptable rangeTrouble = Equipment not meeting Production target, Environmental, QualityDown = Equipment brokeStopped = Equipment idleMaintenance = Scheduled Maintenance

OperatingEvents

Ore B Ore A

EventCapture

(Time Slices)

[St, Et}

STDev=(-15m, *,x, Trouble)STDev=(-1month,x, Ore B)

Event

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New Strategy for Grade Recovery Improvements

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Events

EventsEvents

Big Data, Events and Business Intelligence tools

ProductionLines

Prod 1

Prod 3Prod 4

Prod 2

Mineral 1

Mineral 2

Mineral 3

Mineral 4

Ore Type

Time

01:00 02:00 03:00

44.70044.79044.70044.790

44.70044.79044.70044.790

69.03093.79069.03093.790

69.03069.79069.03069.790

42.793242.84042.793242.840

42.793242.84042.793242.840

85.13285.98085.13285.980

85.13285.98085.13285.980

94.11094.85394.11094.853

94.11094.85394.11094.853

81.23081.23481.23081.234

85.23085.23485.23085.234

Crushing

Thickening

Grinding

Flotation

Process Characteristics

Historical

OKTroubleDownStoppedMaintenance

Events

Southern Peru Copper: Cuajone

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Sharepoint, PI AF, Excel Data Services, PI Slicers Using Latest Power Pivot in Memory technologies

Slicers

Process

AF Model

AnalyticsResults

Results: Advanced Mine to Mill Integration

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Economic Benefits:

Production Benefits:

Integration of Mine Feed Knowledge with Milling, Flotation and Dewatering.

UC 2010

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