moving towards continuous process management in …

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641989

REAL-TIME MINING MOVING TOWARDS CONTINUOUS PROCESS MANAGEMENT IN MINERAL RESOURCE EXTRACTION

FUTURE MINING CONFERENCE

SYDNEY, 5TH OF NOVEMBER 2015

JÖRG BENNDORF, DELFT UNIVERSITY OF TECHNOLOGY

ON BEHALF OF THE REAL-TIME MINING CONSORTIUM


PARTNERS

2


BACKGROUND

Potential of critical raw materials in Europe classified by deposit sizes (PROMINE) 3


The main barriers to overcome for the successful economic exploitation:

o effective grade control, which will maximize resource potential along the whole value chain

o minimization of handling zero-value material introduced by

dilution, thus reducing unnecessary expenditure of energy and financial resources and

o management and control of the geological uncertainty due to

limited information available.

BACKGROUND

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Main Source of Risk: Geological Uncertainty

Limited Information 1:10.000.000

Complex Geology

Tight product specifications

5 Foto: Neves Corvo Mine


THE TRADITIONAL APPROACH Mine Design Equipment Selection Reserve Estimation

Exploration and Data Collection

Resource Modelling

Production Scheduling and Operation

Processing and Sale

SILO 1 SILO 2 SILO 3 SILO 4 SILO 5

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NEW INFORMATION POTENTIAL

Increasing Availability of Sensor Based Online Data:

• Material characterization (geo-chemical, textural and

physical properties)

• Equipment performance, upstream and downstream (e.g.

efficiency, down-time)

• Equipment location and material tracking (e.g. GPS, UPS) 7

Foto: MIBRAG


THE REAL-TIME MINING APPROACH

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THE REAL-TIME MINING PROJECT OBJECTIVE Overall objective: to develop an innovative technical solution for resource-

efficient and optimal high precision/selective mining in geologically complex

settings using online data.

Hypothesis: recovery can be significantly increased by changing mineral

resource management from a ‘batch-type’ to a near-continuous model-based

controlled activity

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REAL-TIME MINING BUILDING BLOCKS

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EXTRACTION METHODS RTM CYCLIC EXTRACTION

Drill Hole

Core

Sample

Ore zone

Muck- pile

LHD

Ore- pass

Ore Transfer

BIN

Crusher

BIN

A

B

C

Control decision points

Sensors for material characterization

Sensors for machine performance

Sensors for geo-referencing (positioning and material tracking)

Selective Loading

Scheduling

Dispatching

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REAL-TIME MINING REAL-TIME DATA

(Lead: RWTH Aachen)

Lead: TU Delft

Lead: SonicSampDrill 12


TEST CASE 1

“Reiche Zeche” Research Mine Freiberg, Germany Source: Description „Test Site Mine ‚Reiche Zeche‘, Freiberg, Saxony, Germany“ provided by TU Bergakademie Freiberg


TEST CASE 2

“Neves Corvo” Copper Mine Portugal (Massive sulphide ore and associated stockwork zone) Source: lundin mining


CASE STUDY UPDATING

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Sensor

Predict

Measure

Reconcile

GC Model

Grade Control (GC) Model

1. Reconcile – Extracted Blocks

2. Update – Scheduled Blocks

Extraction Performance

1. Improve production forecasts

2. Optimize control decisions

(proact)


CASE STUDY UPDATING

Predicted Measurements

Actual Measurements

Reconciliation Software

Prior Block Model

Forward Prediction

Measurement File

Material Tracking/ Material

Flow Simulation in

the Mine

Updated Block Model

replace

Sensor

Source: Wambeke, T & Benndorf, J (2015). Data assimilation of sensor measurements to improve production forecast in resource extraction. In s.n. (Ed.), Proceedings of the 17th annual conference of the international association for mathematical geosciences, IAMG2015 (pp. 236-245). Houston: IAMG.


Simulations

Mean Field

x SMU scale

x

CASE STUDY UPDATING

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Simulations

Mean Field

x SMU scale

x

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CASE STUDY UPDATING


Optimal value

Optimal value

Acceptable range

Acceptable range

Penalty applied

Dai

ly p

rodu

ctio

n in

kt

Gra

de in

%

Forecast of process KPI’s for a given extraction schedule

CASE STUDY OPTIMIZATION


Simulation based optimization of extraction schedule to improve extraction performance

CASE STUDY OPTIMIZATION


ADVANCE WITHIN RTM

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THREE TAKEAWAYS 1. Real-Time Mining is an exciting European Union funded

H2020 project and integrates multiple disciplines

2. Making best use of online production information can lead to a shift in paradigm from a batch-type to a continuous process monitoring and control and can create significant value

3. Real-Time Mining will demonstrate this hypothesis in full industrial scale case studies (TRL 6/7).

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Thank you for your attention and

Glückauf

www.realtime-mining.eu

moving towards continuous process management in …

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