The Use of Common Business Intelligence and Analytics Tools in the Operation and Optimisation of Iron Ore Process Plants.

Fry, M.R.1, Nassis, T.2, Louw, P. 3 and du Toit, T.4

1. DRA Mineral Projects2. Green Team International3. Deloitte Consulting4. Assmang Pty. Ltd.

Khumani Iron Ore Mine, South AfricaOperating since 2008

You can take all the measurements you need but if you don’t have easy and timeous access it does not mean much

Basic Flow Diagram

• Slow access to production data• Integrating data from multiple sources

– different formats, different levels of granularity

• Important data emailed in spreadsheets– e.g laboratory data

• Poor access to long term historical production data – long lead time when requesting data from a vendor

• External consultants/contractors drain resources with data requests

Data Accessibility Issues

• Constant report changes as new managers have different preferences

• Long lead time when requesting report changes from your software vendor

• Software vendor package limitations

Data Visualisation Issues(e.g. reports, dashboards)

Priority No. 1Create a system where non-IT personnel can query data and create their own dashboards or reports.

2. Establish a stable platform of data.3. Create a unified interface for access to all production data.4. Create ‘Plug and Play’ capabilities for new vendor systems to

add/remove their data.5. Create long term continuous data storage and access.6. For IT dept. - Reduce the burden that reporting services create on

source databases

Objectives

Solution

The Use of Common Business Intelligence and Analytics Tools in the Operation and Optimisation of Iron Ore Process Plants.

Microsoft Excel• Everyone knows how to use it

OLAP cube(On-line Analytical Processing)• Technology for processing and then presenting multidimensional

data for analysis• Common business tool that is part of MicroSoft SQL server

Example of Dashboards Created

Feed Target % Var Product % Yield Target % Var13 128 18 000 ‐27% 8 369 64% 81% ‐21%

Jig Plant PerformanceShift Dashboard

2014_11_17 Day Shift

Total Plant Feed Product and Yield

Lumpy Jigs Feed and Yields Lumpy Jigs Cyclone Pressure

Lumpy Jigs Feed Rate and Number of Modules Running Lumpy Jigs Sump Level

1 138 1 072 999920

999

726

1 200

1 400

1 1001 216 1 172 1 186

0200400600800

1 0001 2001 400

06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Feed Rate

Target

0

50

100

150

200

250

300

06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Target

Stream 1

Stream 2

Stream 3

Stream 4

0

10

20

30

40

50

60

70

80

90

100

06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Target

Stream 1

Stream 2

Stream 3

Stream 4299 286 333 307 333 242 400 467 367 304 300 301

3.8 3.8

3.0 3.0 3.0 3.0 3.0 3.0 3.0

4.0 3.9 3.9

0.0

1.0

2.0

3.0

4.0

050100150200250300350400450500

06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Avg. Feed Rate per Module per Operating Hour Feed Rate Tgt No. of streams running

Creating a Dashboard

Footer

Creating a Dashboard

OLAP Cube

Graphically Representationof the OLAP cube

• When - hour, shift, day, month, year• Where - Map ID• What - tons, LIMS, etc.

Where - Map ID’s

• Example of Flow Diagram with Map IDs

What - Measurements

Measurement Device Measurement (s)

Weightometer Mass flow on conveyor belt

Online Chemical analysis Real time chemical analysis: %Fe, etc.

Laboratory Analysis of samples • Delayed Chemical analysis: %Fe, etc.• Delayed Particle size distribution of the sample

Online Particle Size Analyser Particle size distribution of material lying on the conveyor belt

Flowmeter Volumetric flow

Densitometer Slurry density

Pressure Indicator Line pressure

Level indicator Tank Level

Architecture

How is the cube used practically

• Excel sheets automatically populated– Daily laboratory report

Typical Use

Data Granularity

• Laboratory or the analyser calibrating team to check the results from 2 sources

• Enable timeous intervention

Metallurgical Uses

Short term planning cycle• Automatically updating short term planning tools (forecasting)

Metallurgical Uses

Met Accounting tools have been created using the OLAP cube in order to:

• monitor the reliability of the weightometer readings,

• check the mass balance across the plant and its sub-sections,

• checking the reliability of the online sizing and chemical analysers,

• perform investigations as required

Before• Diagrams need to be scrutinised

for the correct instrument tags• Hours are spent gathering and

organising all the data• 1000’s of rows of data• Level of granularity has to be

decided up front and then can’t be changed

Using the OLAP cube• New calculation is made in the

cube• Data can be viewed for any

period• Level of granularity can be

changed as required• No data required, can go

straight to chart

Typical Investigation(e.g. Have the solids to the tailings dam increased?)

Finding Required Data

Data analysts with little knowledge of the plant query data and create reports with Excel

• Example of Flow Diagram with Map IDs

Consultants on site

Consultants on site can be shown the cube to access the data themselves

• No training required

• No reliance on mine resources

• Create their own dashboards as required

IT Advantages

• Permanent storage of data separate from the production systems (e.g. production capturing, mine truck and dispatch systems, laboratory information management systems, etc.).

• Relieves the production systems from reporting workload.

• The OLAP cube technology offers faster access to data for BI systems

• NO licensing fee to pay for 3rd party vendors

Khumani Iron Ore Mine, South Africa

IT solution to empower non-IT users