The document discusses using a digital twin simulation software called NIAflow to optimize mineral processing plants. A digital twin is a digital replica of a physical asset that can be used for various purposes like testing modifications. The simulation model represents the real plant's machinery and processes. It is connected to real plant data and behaves the same way. This allows modifications to be tested without incurring capital or production costs. The document provides an example of optimizing a mineral processing plant in 3 steps - modeling, verification, and optimization - to increase throughput while meeting production specifications. Modifications like screen changes allowed the plant's capacity to be increased by 20%.

1. HAVER & BOECKER
HAVER & BOECKER
Optimization of Mineral Processing Plants
with Simulation Software „NIAflow“
Mines of the Future, Aachen 23-24.05.2018

2. HAVER & BOECKER
Industry 4.0 – The digital twin
Digital twin refers to a digital replica of physical assets (physical
twin), processes and systems that can be used for various purposes.[1]
Digital twins integrate artificial intelligence, machine learning and
software analytics with data to create living digital simulation models
that update and change as their physical counterparts change.
1. "Minds + Machines: Meet A Digital Twin". Youtube. GE Digital. Retrieved 26 July 2017.

3. HAVER & BOECKER
The twin of a mineral processing plant …
 Represents
machinery and
processes of the
real plant
 Is connected to the
real plant by means
material- and
processing data
 Shows the same
behavior than its
counterpart
Modifications can be tested using on the model prior to CAPEX or production loss.

4. HAVER & BOECKER
 This is the main purpose of a processing machine - defined by their main
objective e.g. crusher modification of PSD
 Each machines also produces side effects e.g. change of bulk density, angle
of repose, temperature… If significant, these modifications have to be
applied to all downstream machinery -> Inheritance
 Processing machinery can be grouped by there main objective
– Transportation
– Storage
– Distribution, Blending
– Comminution, Agglomeration
– Grading
– Sorting
Machines materials interaction

5. HAVER & BOECKER
 All machinery is affected by the material being processes.
 When modelling limits have to be defined to ensure proper operation of
the machine
– Max. feed tonnage
– Max. feed size
– Max. layer
– Max. temperature
– Max. water content
– etc. …
 Limits have to be monitored during calculation
Materials affecting machines

6. HAVER & BOECKER
Background – how machinery affects material
Class Affects on material Example
Transportation None
Storage Tonnage
Distribution,
Blending
Tonnage, PSD
Comminution,
Agglomeration
PSD
Grading Tonnage, PSD
Sorting
Tonnage, concentration of sorting
properties, PSD

7. HAVER & BOECKER
1. Modelling
2. Verification
3. Optimization
Plant optimization in 3 steps

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„Jon Doe Aggregates“
 Maximize of production in three operation modes
 Meet road building specs
 No CAPEX

9. HAVER & BOECKER
Model - Primary
 Scalping
 <40 waste
 Crusher at CSS 120

10. HAVER & BOECKER
Model - Secondary
 Cone crusher (CSS 40 mm) in
closed circuit
 Product <22 to tertiary product
screen A
 Products 22/32 and 32/45
stockpiled or to tertiary

11. HAVER & BOECKER
Model – Tertiary
 Road gravel production
 VSI with selectable re-crushing
circuit

12. HAVER & BOECKER
Crusher Product PSD’s
Primary
No affect on product PSD’s
Tertiary
Product PSD = f(feed rate)
Left to right:
• <125 t/h
• 125-275 t/h
• >275 t/h
Secondary
Static product

13. HAVER & BOECKER
Crusher products – particle shape
Cone crusher
VSI
< 125 t/h
VSI
125 t/h - 275 t/h
VSI
> 275 t/h
5,6 - 8 40 85 84 80
8 - 11,2 50 87 80 83
11,2 - 16 55 93 85 88
16 - 22,4 65 88 86 81
22,4 -31,5 60 94 90 88
Fraction
Cubical content [%]

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Screen media
Screen media
Opening 25 18,3 12,5 9 6,5 2,5
Type PU PU
Opening shape rectangular
rectangular,
cross flow
Open area 38,6% 64,7% 65,1% 60,4% 57,1% 21,6%
Production screen A Produkction screen B
square square
wire cloth

15. HAVER & BOECKER
Operating modes
Normal Min. re-crush Max. re-crush
10.00 50/50 100/0 0/100
12.00 50/50 100/0 0/100
17.00 50/50 0/100 100/0
19.00 50/50 0/100 100/0
Setting per operation mode
Splitter

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 Modelling
Verification
 Optimization
Plant optimization in 3 steps

17. HAVER & BOECKER
Plant sampling in one operation mode
Start objects, crusher (modelling, verification)
Collecting belts (detailing, verification)
Products (verification)
Machinery analysis

18. HAVER & BOECKER
Model calibration by tonnage and PSD
Plant
Model

19. HAVER & BOECKER
Model calibration on screens
 Values differ equally at all measuring points
– Calibration on plant level (global adjustment of all
screen cut-curves)
 Values differ at individual machines
– Correct improper machine setup and re-sample
• screen opening
• open area
• blind areas etc.
– If above is not successful -> calibration on machine
level

20. HAVER & BOECKER
Verification completed

21. HAVER & BOECKER
Plant optimization in 3 steps
 Modelling
 Verification
Optimization

22. HAVER & BOECKER
Optimization - Limits
lower upper
0/2 10-15 85-99
2/5 0-10
5/8
8/11
11/16
16/22
Product
Spec. limit Cubical
content
0-15
90-99
n/a
80
Secondary 500
Tertiary 400
Crusher Max. throughput [t/h]

23. HAVER & BOECKER
Cubical content
 Cubical content not met

24. HAVER & BOECKER
Process Modification
 Cubical content met in
all operation modes

25. HAVER & BOECKER
Throughput 300 t/h - Normal Operation
Production screen B
cut 2mm, opening
change 2,5mm -> 2,7mm
New problem product 0/2
Production screen B
Cut 2mm
PU -> Flexmat
opening 2,5mm -> 2,24mm
open area 21,6% -> 46,2%

26. HAVER & BOECKER
Throughput 340 t/h - Normal Operation
Production screen A, cut 16mm
opening 18,3 mm -> 18,6 mm
open area 64,7% -> 73,6%
Production screen A, cut 11,2mm
opening 12 mm -> 12,5 mm
open area 65,1% -> 84,1%

27. HAVER & BOECKER
Throughput 380 t/h – Normal Operation
Crusher over capacity limit. Plant throughput adjusted to 360.
360 t/h is the new maximum plant throughput in normal operation
mode (prior 300 t/h)

28. HAVER & BOECKER
Summary
 Three optimization limits have been used: particle shape, misplaced particles, max. tonnage
 Plant capacity could be increased to 120% before hitting CAPEX restriction
 „Digital Twins“ can be utilized to simulate plant conditions at low risk and low cost
 Proper modelling and sampling provided, the model will behave identically to the plant
 Aside from particle shape and PSD other target values can be modelled (e.g. color, density)
 Biggest optimization potential can be found in machines that affect more then one target
value. In most cases these are production screens affecting product - PSD and tonnage.

29. HAVER & BOECKER OHG
Carl-Haver-Platz 3 • 59302 Oelde • Deutschland
+49 2522 30-0 • haver@haverboecker.com • www.haverboecker.com
HAVER & BOECKER
Thank you very much for your attention!
Dr.-Ing. Rüdiger W. Heinrich