how the camsizer solves sieving problems february 2015 · sieving practice such as overloaded sieve...
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© 2015 HORIBA, Ltd. All rights reserved. 1© 2015 HORIBA, Ltd. All rights reserved. 1
How the CAMSIZER SolvesSieving Problems
HORIBA ScientificParticle Characterization
Ian Treviranus
February 18, 2015
© 2015 HORIBA, Ltd. All rights reserved. 2
What we’ll talk about
• Review of common sieving challenges
• CAMSIZER technology
• Simple, intelligent sieve correlation
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Size analysis via sieving
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Sieves go way back
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Labs can look like this
Image courtesy of Tom Gapinske and Summit Envirosolutions*original located here: www.horiba.com/fileadmin/uploads/Scientific/Documents/PSA/Webinar_Slides/AP034.pdf
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•(A) Low accuracy, low precision measurements form a diffuse, off-center cluster; (B) Low accuracy, high precision measurements form a tight off-center cluster; (C) High accuracy, low precision measurements form a cluster that is evenly distributed but distant from the center of the target; (D) High Accuracy, high precision measurements are clustered in the center of the target.
LOW ACCURACYLOW PRECISION LOW ACCURACY
HIGH PRECISION HIGH ACCURACYLOW PRECISION HIGH ACCURACY
HIGH PRECISION
Accuracy vs. precision
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Sampling
Sample division
Test Sieves
Sieve shakers
Evaluation
Accessories& cleaning
Sieve measurement workflow
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Separation happens during- Transport processes (container, train and
truck)- Feeding processes (funnels, vibration feeders,
belts)- and Storage (bulk pile, silo)
Sampling and Sample Splitting
Segregation
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Hell
Sampling and Sample Splitting
Sampling & sample splitting
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0
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Q3
(x)
/ %
50 100 500 1000 5000 10000Particle size / µm
Quartz
Sample 1Sample 2Sample 3
Randomsampling
3 accurate analyses = 3 different results!
Consequence of sampling
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If sieve analysis is used for quality controlwithin the context of DIN EN ISO 9000:2000
then both the sieve shaker and thetest sieves must be subjected to
test agent monitoring.
w = mesh widthd = wire diameter
Tolerance for mean value (Y):The mean value of the mesh width must not differ from thenominal value w by more than the tolerance ± Y.
w
w
Ø d
Ø d
Technical requirements & testingaccording to ISO 3310
Standards compliant sieves
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100 200 300 40040 50 60 70 80 90Particle size x[µm]
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Q3 [%]
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Q3 [%]
44%
+Y 66.7
36%
-Y 59.3
63 µmTolerance ± Y = 3.7 µm
40%
Importance of mesh width
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Spheroidal particles
x [µm] 200 400 600 800 1000 1200 0
10
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50
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90 Passing [%]
Sample-1__xc_min_002.rdf Sample-1__xc_min_001.rdf Sieving-Nominal-S1.ref
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1400µm 1400µm 1429.5µm
Mesh sizes warp Mesh sizes weft
Nominal Sieve Mesh = 1400µm Real Sieve Mesh >1400=1455
only beads < 1400µm
will pass the sieve mesh
beads > 1400µm will not pass the sieve mesh
Upper mesh size range ~1455µmsieve No. 03033531 (nominal 1400µm)
Theory: Reality:
Influence of mesh width
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x [µm] 200 400 600 800 1000 1200 0
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90 Passing [%]
Sample-1__xc_min_002.rdf Sieving-upper-range-S1.ref
Real mesh width
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0
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100Q
3(x)
/ %
10 50 100 500 1000 5000Particle size / µm
Identifiers
AMP- 2AMP- 0.5AMP- 1.2
Quartz sand, Sieving time: 2 min.
Effect of amplitude
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F2
F1
1. Move
2. Sliding friction
3. Static friction
xc_min [mm]0.5 0.6 0.7 0.8 0.9 1.00
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Q3 [%]
0
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q3 [%/mm]5454_PT100_xc_min_008.rdf5454_random_xc_min_009.rdf5454_Huntsman-sieve.ref
Roundparticles
arecapturedwithout
rerelease
Applications - Proppants
Overloading sieves
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- robust and accepted- easy handling- references available from user
Advantages
Disadvantages- high amount of time and work- low resolution, small number of classes available
- limited sample amount- no shape analysis possible
Competing Measuring Methods
Worn out sieves
Sieving pros & cons
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Sieve support issues
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Processing during Ro-Tap
• Resin-coated sands may be altered by mechanical energy– Clusters break, hiding potential issue– Resin abrades, overstating dust
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• Sampling problems:wrong sampling (pouring and “spooning“)
• Sieve problems: overloading of sieves (blinding / blocking), cross contamination from trapped material, nominal size real sizes of meshes (wide specification and worn out sieves), sieving machines are not calibrated
• Balance problems:low resolution (0.1 grams), not sensitive for small weights (contamination) of joints and moving parts, interference with air flow
• Time problems:Sieve analysis too long to meet business requirements
Issues with sieving
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Sieves aren’t always fast enough
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What we’ll talk about
• Review of common sieving challenges
• CAMSIZER technology
• Simple, intelligent sieve correlation
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Featured technologies• LA-960
Laser Diffraction
• SZ-100Dynamic Light Scattering & Zeta Potential
• CAMSIZER & CAMSIZER XTDynamic Image Analysis
• PSA300Static Image Analysis
• SA-9600Flowing Gas BET Surface Area
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CAMSIZER Dynamic Image Analyzers
• High resolution size & shape• Intelligent sieve correlation• Patented dual capture• CAMSIZER
– 20 µm – 30 mm– Free flowing powders, granules
• CAMSIZER XT – 1 µm – 8 mm– Cohesive or free flowing
powders– Suspensions with
accessory
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Take a picture,
measure for size
Measurement Results
Image analysis in a nutshell
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Two camera system
Basic-Camera Zoom-Camera
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Use gravity, or, better, vacuum (from a compressed air supply and venturi) in order to draw particles through instrument. Vacuum helps keep the windows clean.
Moving particles
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CCD - Basic CCD - ZoomDetection of particles
One pixel is element of a projection when at least half of the pixelis covered.
Resolution
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Resolution
mixture of six sizes of grinding balls
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Advantage of image analysisBetter Size Analysis due to Understanding of Particle Shape:
Length, Width, Average Diameter
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Shape analysis
area of the particle
perimeter of the particle
circle with same area as particle
diameter of circle of
same area
2
4P
ASPHT
max
min
Fe
c
xx
lw
lb
b/l0.4 0.5 0.6 0.7 0.80
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Q3 [%]
Pharma-Product-1-30kPa-bonne-forme-_xc_min_009.rdfPharma-Product-1-30kPa_Vitesse-Adaption_xc_min_008.rdflactose-30kPa_xFemax_003.rdfPharma-Product-2-460_xc_min_008.rdf
SPHT0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90
10
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Q3 [%]
Pharma-Product-1-30kPa-bonne-forme-_xc_min_009.rdfPharma-Product-1-30kPa_Vitesse-Adaption_xc_min_008.rdflactose-30kPa_xFemax_003.rdfPharma-Product-2-460_xc_min_008.rdf
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Statistical sledgehammerCAMSIZER easily measures tens and hundreds of thousands of particles
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What we’ll talk about
• Review of common sieving challenges
• CAMSIZER technology
• Simple, intelligent sieve correlation
© 2015 HORIBA, Ltd. All rights reserved. 35
x [mm]0.2 0.4 0.6 10
10
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Q3 [%]
Sample A_BZ_0.2%_xc_min_001.rdfSample A_.ref
CAMSIZER Sieving
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Comparison to results from sieve analysis
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Particles can slip through a mesh although it is not expected!
Comparison to results from sieve analysis
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“Width”, measured with CAMSIZER xc min (red)Results from sieving (* black)
xc min
CAMSIZER size distribution is wider than thedistribution from sieve analysis
… this effect is caused by how a sieve will pass coarser particles than you think!
Comparison to results from sieve analysis
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x [µm]200 400 600 8000
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Q3 [%]
RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref
x [µm]200 400 600 8000
10
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Q3 [%]
RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref
Elementary fitting function
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xc_min [mm]1.0 1.5 2.0 2.5 3.00
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Q3
One fitting file works for multiple samples!
Digital Imaging Sieving
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Requirements for correlation
Reliable sieve dataCustomers may have un-calibrated test sieves and / or sieve shakers. Bad
sieving practice such as overloaded sieve pans also affect the accuracy of sieving. Test analyses need to be closely monitored according to ISO 3310.
Good sampling
Good CAMSIZER measurementsMeasurements are only good if it is (1) repeatable and (2) reproducible.
xc min particle size model should be used for fitting files.
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DankeБольшое спасибо
Grazie
اُشْكر
Σας ευχαριστούμε
감사합니다
Obrigado
谢谢
ขอบคุณครับ
ありがとうございました
ध यवाद
நன்ற
Cảm ơn
Dziękuję
Tack ska ni ha
Thank you
Merci
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Ian TreviranusProduct Line Manager