Christian Potocan 2013-05-23
SpectraFlow Online Analyzer
Iron Ore / Sinter Application
© SFA Ltd
April 17, 2020 | Slide 1
Contents

History

Near Infra Red (NIR) – The Technology

The Model Development

Comparison of different analytical methods

SpectraFlow in the Sinter Production Process

SpectraFlow – The hardware setup

References
© SFA Ltd.
April 17, 2020 | Slide 2
History – SpectraFlow: a real success story

2006: ABB started the development of the SpectraFlow Analyzer

2007: First trials in the USA and Switzerland

2008: Test installations for Limestone Quarry and Sinter in Italy, Norway and Germany

2009: First commercial installation on a conveyor belt in a Cement plant in Slovakia

2010: First tests for the airslide application

2011: Multiple installations around the globe: Saudi Arabia, Oman, Iran, Pakistan, Germany
and Switzerland

2012: First commercial installation on an airslide after the Raw Mill in Switzerland and Brazil

2013: Foundation of SpectraFlow Analytics and transfer of the SpectraFlow business from
ABB to SFA

2013: 10 successful installations around the world and multiple orders received. SpectraFlow
is established in the market and technically mature
© SFA Ltd.
April 17, 2020 | Slide 3
NIR Technology - Objectives of the development

Select a proven and accepted analysis technique that will give fast and reliable analysis

Make sure that no hazardous materials are needed in the operation of the system


Eliminate radioactive sources, neutron generators or X-Ray components

Eliminate the need for permits or licences for the operation of the system
Provide real-time on-line analysis for any kind of bulk material by a single technology to
analyse all

Molecules

Mineral phases

Module parameters
© SFA Ltd
April 17, 2020 | Slide 4
NIR Technology - Minerals have a NIR signature
SiO2
Fredrickson : Characterisation of hydrated
Alumina by NIR 1954
Hunt, Salisbury: Visible and Near Infra Red Spectra of
Minerals and Rocks 1970
Hunt, Salisbury: Visible and Near Infra Red Spectra of
Minerals and Rocks 1970
FeO
CaO
Hunt, Salisbury: Visible and Near Infra Red Spectra of Minerals and Rocks 1970
© SFA Ltd
April 17, 2020 | Slide 5
NIR Technology - Principle of the measurement

When energy (light) hits any matter this matter gets excited and starts to vibrate

This vibration is characteristic for any mineral or molecule and according to that consumes a specific
energy
Symmetrical stretching
Asymmetrical stretching
In plane scissoring
Out of plane wagging
Out of plane twisting
In plane rocking

As the amount of energy emitted is known and the amount of energy reflected is measured, the amount
of energy consumed is calculated

The consumed amount of energy is the mineralogical fingerprint of the raw material

As the information of the raw material is determined out of the movement of the crystal structure and
molecules and not the elements, all elements can be measured
© SFA Ltd
April 17, 2020 | Slide 6
NIR Technology - Principle of the measurement
FTIR
Spectrometer
TCP/IP Connection to RMP
Input Lens, which ascertains
parallel beams inside
spectrometer
Lamp shining at
the material
Belt Conveyor
© SFA Ltd
April 17, 2020 | Slide 7
Light Paths
Industrial
PC with
Soft PLC
Lamp shining at
the material
Iron Ore Mix
Model development - The Principle
TRAINING
=
CALIBRATION
FeO 65.50 %
CaO 0.95 %
SiO2 1.3 %
H2O 5.6 %

How much FeO, CaO, SiO2 and Moisture does this Spectra mean?

The analyzer has to be trained, to translate the Spectra into the chemical composition
© SFA Ltd
April 17, 2020 | Slide 8
Model development - The calibration process
© SFA Ltd
April 17, 2020 | Slide 9

To develop the relationship reference material has to be supplied

The reference material has to represent the range of the material
to be measured

The reference material has to be delivered with accurate chemical
analysis

Depending on the complexity of the application 20 to 50 samples
are needed to develop the initial calibration

The samples are measured in a dynamic mode and the spectra for
the different materials are obtained
Comparison of different analytical methods
XRF
PGNAA
SpectraFlow
Measurement Method
Offline
Online
Online
Source of Energy
X-Ray Tube
Radioactive Source
Lightbulbs
Analysis Basis
Elements possible to
measure
Dependency
Electron Shells
dependent on Calibration: from
F (WDX) or Na (EDX)
Vacuum, Sample Preparation
Nucleus
from Na (Cf source)
(neutron tube)
Belt Speed, Belt Load
Molecules, Mineral Phases
Depth of Analysis
µm
Up to 500 mm
µm - mm
Measurement Principle
Possible Measurement
Positions
Reports
Reflexion
Transmission
Reflexion
Conveyor Belt
Conveyor Belt, Airslide
Elemental Analysis
Elemental Analysis
Mineral Phases, Oxides
Repeatability
Fair to Good
Poor
Good
Measurement time
Analytical
Error
Sampling
Accuracy
Error
Seconds
Minutes
high to low dependent on
Element
Seconds
high to very high
low
very low
high to very high
low
very low
X-Ray tube
Radioactive Source
light-bulbs
Total Error
Consumables
© SFA Ltd
April 17, 2020 | Slide 10
very low
from O
all elements: including H
no nonlinear layering
low
Model development - The resulting models
71.00
70.00
69.00
68.00
67.00
66.00
65.00
64.00
63.00
62.00
61.00
60.00
Model for SiO2 on Pos A
Predicted Concentration
[%]
Predicted Concentration
[%]
Model for FeT on Pos A
62.00
64.00
66.00
68.00
70.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
0.00
1.00
XRF Concentration [%]
0.2000
0.3000
0.4000
Predicted Concentration
[%]
XRF Concentration [%]
© SFA Ltd
April 17, 2020 | Slide 11
4.00
5.00
6.00
Model for Al2O3 on Pos A
Predicted Concentration
[%]
0.1000
3.00
XRF Concentration [%]
Model for CaO on Pos A
0.4500
0.4000
0.3500
0.3000
0.2500
0.2000
0.1500
0.1000
0.0500
0.0000
0.0000
2.00
0.5000
2.50
2.00
1.50
1.00
0.50
0.00
0.00
0.50
1.00
1.50
XRF Concentration [%]
2.00
2.50
Model development - The accuracy of SpectraFlow
Sample Number
1
2
3
4
5
6
7
8
9
10
Sample Number
1
2
3
4
5
6
7
8
9
10
© SFA Ltd
April 17, 2020 | Slide 12
Iron (FeT)
actual/%
67.42
67.60
66.64
69.14
61.74
62.35
66.71
66.30
CaO
actual/%
0.4300
0.3400
0.3500
0.3700
0.0000
0.0200
0.0400
0.0400
0.0200
0.0100
predicted / % Rel Error / %
66.74
1.00
66.96
0.95
65.08
65.89
1.13
68.99
0.22
69.82
62.25
0.83
61.87
0.76
67.19
0.72
66.75
0.68
predicted / % Rel Error / %
0.4156
3.34
0.3509
3.21
0.3418
2.34
0.3735
0.93
0.0062
0.0222
11.25
0.0389
2.86
0.0406
1.57
0.0196
2.08
0.0114
14.28
Sample Number
1
2
3
4
5
6
7
8
9
10
SiO2
actual/%
1.48
2.30
2.01
2.30
0.62
0.60
5.30
4.90
3.62
4.32
predicted / % Rel Error / %
1.72
16.18
2.16
5.94
2.21
10.16
2.29
0.28
0.56
9.36
0.62
3.48
5.32
0.37
4.76
2.81
3.87
6.89
4.09
5.32
Sample Number
1
2
3
4
5
6
7
8
9
10
Al2O3
actual/%
0.46
0.51
0.50
0.55
0.42
0.40
2.04
1.93
0.58
0.57
predicted / % Rel Error / %
0.47
2.31
0.52
1.36
0.50
0.81
0.53
3.28
0.41
2.71
0.40
1.22
1.98
2.97
1.96
1.32
0.58
0.75
0.57
0.75
Comparison of different analytical methods
XRF
SOLBAS™
PGNAA
Measurement Method
Offline
Online
Online
Source of Energy
X-Ray Tube
Radioactive Source
Lightbulbs
Analysis Basis
Elements possible to
measure
Dependency
Electron Shells
dependent on Calibration:
from F (WDX) or Na (EDX)
Vacuum, Sample Preparation
Nucleus
from Na (Cf source)
from O (neutron tube)
Belt Speed, Belt Load
Molecules, Mineral Phases
Measurement Principle
Possible Measurement
Positions
Reports
Reflexion
Transmission
Reflexion
Conveyor Belt
Conveyor Belt, Airslide
elements: including H
PGNAA can’ t measure iron ore: due to a veryallhigh
response
no nonlinear layering
of Fe all
Depth of Analysis
µm other elements
Up tocan’
500 mm t be recognized
µm - mm
Elemental Analysis
Elemental Analysis
Mineral Phases, Oxides
Beside
the
important
elements
FeO,
CaO
and
SiO2 also
Repeatability
Fair to Good
Poor
Good
Measurement time
Seconds
Minutes
Seconds
moisture
can
be
measured
Analytical
high to low dependent on
Accuracy
Error
Sampling
Error
Total Error
Consumables
© SFA Ltd
April 17, 2020 | Slide 13
very low
Element
low
high to very high
low
very low
high to very high
low
very low
X-Ray tube
Radioactive Source
light-bulbs
SpectraFlow - Position in Sinter production process
Control the quality of the Iron
Ore for stable Stockpiles
POSITION A
SPECTRAFLOW
ANALYZER
IRON ORE
STOCKPILE B
IRON ORE
STOCKPILE A
Control the Bacisity (CaO/SiO2ratio) of the sinter mix
IRON ORE
STOCKPILE C
POSITION B
CONTROL SOFTWARE
LIMESTONE
ADDITIVE
WATER
WATER
RETURNS
COKE
RAW MIX
HOPPER
BLENDED
ORE
COKE
MIXING DRUM
BURN THROUGH
AREA
IGNITION
HOOD
Lower returns due to more
consistant quality of the feed
ROLLER
CRUSHER
TO ATMOSPHERE
WIND BOXES
COOLING
FANS
GAS
CLEANING
FAN
HOT RETURN
FINES
BLAST
FURNACE
© SFA Ltd
April 17, 2020 | Slide 14
HOT
SCREEN
COLD
SCREENING
BUNKER
COLD
RETURN
FINES
SpectraFlow – The hardware setup
Spectrometer
Box
Control Panel
Illumination
Head
© SFA Ltd
April 17, 2020 | Slide 15
SpectraFlow – The hardware setup
FTIR Spectrometer
Light and dust
shield
Lamp
Use 4 lamps 50 Watt
each
Bulk Material
© SFA Ltd
April 17, 2020 | Slide 16
Lamp holder
SpectraFlow - The hardware setup
Spectrometer
Compartment
Flap which
can be
opened to
access the
lights
Overall view
Entry for the
reflected
Infrared into
Spectrometer
Flap open
Interfaces
Power Supply
for the spots
Industrial PC (IPC)
Light Spots
View of the inside ceiling
© SFA Ltd
April 17, 2020 | Slide 17
Electronic Panel opened
SpectraFlow – ROI Calculation of the investment
Increased production due to
reduced rejects because of a
more stable quality
GAINS FROM THE ANALYZER2)
PRICES
Analyzer costs total [CHF]
Analyzer costs total [JPY]
Sinter/t [JPY]
Production cost of Sinter/t [JPY]
Number of Analyzers
Costs per Analyzer [JPY]
Calcualtion on a 2
years pay back
COMMERCIAL CONDITIONS
5)
1.50 Interest Rate [%]
CHF 450'000 Increased Throughput [%]
Pay Back Time [y]
¥47'250'000
¥15'000
¥5'000
1
¥47'250'000
10%
4)
SpectraFlow has a payback time of 3 months as the
increased throughput is based on the reduction of the
rejects
PROFIT
CALCULATION
Output Today [t/h]
3)
253.75 Increased earnings/y [JPY]
Output with SF [t/h]
Operation [d/y]
4)
240 Earnings/d [JPY]
PROFIT DURING PAY BACK
-¥27'225'000.00
¥216'000'000.00
¥188'775'000.00
¥216'000'000.00
PAYBACK PER YEAR6)
GROSS PROFIT PER YEAR7)
NET PROFIT DURING PAY BACK TIME 8)
NET PROFIT AFTER PAY BACK TIME 9)
Increased earnings per year
during pay back
© SFA Ltd
April 17, 2020 | Slide 18
21'600
250.00 Increased Throughput/y [t]
1)
¥216'000'000.00
¥591'780.82
Increased earnings per year after
pay back
2
Reference List (17 analyzers in 10 countries worldwide)
© SFA Ltd
April 17, 2020 | Slide 19
SpectraFlow Analytics Ltd
Seestrasse 14b CH-5432 Neuenhof
Tel: +41 56 406 12 12 Fax: +41 56 406 12 48
www.spectraflow-analytics.com
© ABB Group
April 17, 2020 | Slide 20