Sampling, Sieving, Imaging, Correlating the Data Between ... · If sieve analysis is used for...

Sampling, Sieving, Imaging, &

Correlating the Data Between the Two

Presenters:Kyle James – Verder Scientific Inc.

Gert Beckmann – Retsch Technology

Areas of DiscussionTOPICS

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1.) Sample Acquisition: Sampling Methodology & Techniques

2.) Sieve Analysis: Principles / Techniques / Concerns

3.) Dynamic Image Analysis: Methodology / Technique / Correlation

Quality Control / R&DApplications

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Defined product properties

Detected product properties

Agreement

Certain properties are to be achieved when products are manufactured.These depend on the particle size and the particle distribution.

Particle size/distribution = product property

Particle Sizing ExampleWhy it Matters

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Example: CoffeeThe particle size determines important taste properties

Too coarsely ground coffee: the brewing process is accelerated and gives a watery cup of coffee

Too finely ground coffee: too many aromatics, acids and bittering agents are dissolved, the filter could be blocked

Sample Acquistion

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The bigger the particle size, the more difficult it is to attain the representative part sample

Sampling Process

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Transports(belt,container, train and truck)

Accumulation(filling, feeding)

Sample Amount

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Qmin = 0.07 * dmax / ρ

Qmin = mass of a single sample [dm3]

dmax = maximum particle size [mm]

0.07 = factor [kg/mm]

ρ = bulk density [kg/dm3]

Minimum volume (Qmin) of a single samplewith grain sizes (dmax) < 120 mm

DIN 51701 part 2 - Sampling of solid fuels -

Standard Deviations of Various Sample Divisions Methods

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qualitative variation

Sample divider PT 100

Random sampling

Sample splitter

Cone and quartering

qualitative variation0 1 2 3 4 5 6 7 8 9 10 %

Coning and Quartering

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Stream of material

Single sample

Sample Extractor Chute

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Sample Extractor Bucket

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Stream of material

Single sample

Sample Extractor

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Stream of material

Single sample

Sample Dividers from Retsch

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Sample Splitters

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Rotary Tube Divider PT 200

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Laboratory Sample Divider PT 100

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4 accurate particle size analyses= 4 different results!

Importance of sample divisionSample division

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xc_min [mm]0.5 1.0 1.5 2.0 2.5 3.00

10

20

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50

60

70

80

90

Q3 [%]

randomsampling

sample material: standard sand

*,* = nominal values of standard sand

xc_min [mm]0.5 1.0 1.5 2.0 2.5 3.0 3.50

10

20

30

40

50

60

70

80

90

Q3 [%]


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sample splitter




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xc_min [mm]0.5 1.0 1.5 2.0 2.5 3.00

10

20

30

40

50

60

70

80

90

Q3 [%]

rotating sample divider

PT 100

4 accurate particle size analyses= 4 similar results!



Sieveability of particlesSieving

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Free flowing particles

Van-der-Waals forces

Fluid bridges

Electrostatic Forces

Agglomerated particles

+ -

Sieving aidsSieving

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• Aerosil

• talcum powder

• aluminum oxide

solid

• wet sieving

• degreasing:

benzinealcohols

liquid

• chain rings

• brushes

• cubes

• rubber balls

• agate balls

• steatite balls

mechanical

Test sievesthat comply with standards Test sieves

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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

w

w

Ø d

Ø d

Tolerance for mean value (Y):The mean value of the mesh widthmust not differ from thenominal value w by more than thetolerance ± Y.

Technical requirements & testingaccording to ISO 3310

100 200 300 40040 50 60 70 80 90particle size x[µm]

10

20

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40

50

60

70

80

90

Q3 [%]

10

20

30

40

50

60

70

80

90

Q3 [%]

44%

+Y 66,4

36%

-Y 59,6

Importance of mesh widthConsequences of tolerances Test sieves

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63 µmtolerance ± Y = 3,4 µm

40%

Real Mesh WidthReal Mesh

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x [µm] 200 400 600 800 1000 1200 0

10

20

30

40

50

60

70

80

90 Passing [%]

Sample-1__xc_min_002.rdf Sieving-upper-range-S1.ref

Excellent correlation

when using the real mesh opening sizes

Influence of Mesh WidthMesh measurements

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1400µm 1400µm 1429.5µm

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:

Mesh sizes warp Mesh sizes weft

Calibrationcertificate

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Nomial mesh width

Tolerances

Number ofmeasured apertures

Mean mesh width

Standard deviation σ

Wire diameter

Sample AmountSieve Analysis

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4 mm2 mm1 mm

500 µm250 µm125 µm

63 µm45 µm

collecting pan

Sieving Methods forparticle size determination Basics

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Horizontal sievingVibratory sieving Air jet sievingTap sieving

dry wet

vibratory

horizontal

tap

air jet

AS 200 jet AS 200 tap AS 200 AS 300 AS 400 AS 450 control

Selection of amplitudeVibratory sieve shakers

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0

10

20

30

40

50

60

70

80

90

100

Q3(

x) /

%

10 50 100 500 1000 5000Particle size / µm

Quartz,sieving time: 5 min.

AMP- 2 mmAMP- 0.5 mmAMP- 1.2 mm

Statistical resonanceVibratory sieve shakers

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T = periodic time of sieve bottom vibration

particle

sieve bottom

t

A

T T

Sieve analysis procedureProcess

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Potential Concerns & IssuesSampling & Sieving

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1.) Sampling problems:Sampling Technique (pouring and “spooning“)Material Behavior & Composition

2.) Sieving problems: Sieve OverloadSieving Technique / Technology UsedNominal Size Real Mesh SizeMaterial Behavior & Composition

3.) Scale Problems:Low Resolution (0.1g of sample)Not Sensitive Enough (sieves vs actual)

Digital Imaging SievingImage Analysis

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x [µm]200 400 600 8000

10

20

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80

90

Q3 [%]

RT669_3993_Z_LB_05%_xc_min_001.rdfRT669_RT_3993.ref

Particle SizeMorphology

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xcmin

xc min

“width”

A

A‘ = Ax a

rea

“diameter overprojection surface”

xarea“length”

xFe max

xFemax

CAMSIZER results are

compatible with

sieve analysis

Digital Image ProcessingComparison

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x [mm]0.1 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Q3

Tinovetin-B-CA584A_BZ_xc_min_002.rdfSyngenta-1mm-2min-Sieb.ref

--- width measurement

-*- Sieving

comparisonCAMSIZER-measurement xc min (red)and sieving * (black)

xc min

Ellipsoid ParticlesComparison

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x [mm]1.0 1.25 1.5 1.75 2.00

10

20

30

40

50

60

70

80

Q3 [%]

rice

xcmin

A‘ = A

x are

a

A

Red CAMSIZER curve of particle width gives excellent correlation

at the black sieve points

Lenticular ParticlesComparison

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x [mm]0.2 0.4 0.6 10

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50

60

70

80

Q3 [%]

Sample A_BZ_0.2%_xc_min_001.rdfSample A_.ref

Digital Imaging SievingLenticular Particles

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x [mm]0.2 0.4 0.6 10

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50

60

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80

Q3 [%]

Sample A_BZ_0.2%_xc_min_001.rdfSample A_.ref

Digital Imaging SievingCubes / Angular

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x [µm]200 400 600 8000

10

20

30

40

50

60

70

80

90

Q3 [%]


Angular ParticlesShell Limestone

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xc_min [mm]0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.80

10

20

30

40

50

60

70

80

90

Q3 [%]

Muschelkalk_xc_min_001.rdfRT3204_Muschelkalk_Sieb.ref

*Sieve Analysis -CAMSIZER

Digital Imaging SievingAngular

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x [µm]200 400 600 8000

10

20

30

40

50

60

70

80

90

Q3 [%]


x [µm]200 400 600 8000

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20

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80

90

Q3 [%]


angular particles without fitting

CAMSIZER-measurement xc min (red)sieve analysis * (black)

angular particles with Q3-fitting

Digital Imaging SievingDistribution

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Two samples with different width of distributionbut …

… with similar shape

(= same product type)

Limitations of Old ProceduresOld vs New

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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

CAMSIZER Elementary – Fittingxc_min [mm]1.0 1.5 2.0 2.5 3.0

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Q3

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

Old fittingmethods

Digital Imaging SievingElementary Fitting

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Single class:Taken from the sieve stackand measured in CAMSIZER

For creating a CAMSIZER Elementary

fitting file use the more narrow sample

(green)

Elementary fitting with single (narrow) sieve class.It can be the sieve with the highest amount, one above or one below

Digital Imaging SievingElementary Fitting

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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

Elementary - Fitting

New elementary fitting with single (narrow) sieve class and entire distribution

{

Measurement of Single ClassSingle Size

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xc_min [mm]1.0 1.5 2.0 2.5 3.0 3.50

10

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50

60

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80

Q3 [%]

Try to geta single sieve class

as narrow as possiblein the middle

of the distributionof the sample


49© Retsch GmbH

Try to get a singlesieve class as narrowas possible ~ in the

middle of thedistribution of the

sample

Try to get a sample ofyour product as

narrow as possible

Try to get a sample ofyour product as

narrow as possible

Try to get a single sieve classas narrow as possible

in the middle of the distributionof the sample

Shell LimestoneExample

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xc_min [mm]0.4 0.6 0.8 1.0 1.2 1.40

10

20

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50

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80

90

Q3 [%]

Muschelkalk_xc_min_001.rdfRT3204_Muschelkalk_Sieb.ref

Multimodal DistributionExample

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x [mm]0.2 0.4 0.6 0.8 1.0 1.2 1.40

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90

Q3 [%]

SU_Demo02-05_Standaard_BZ_LB_Gl15_03%_xc_min_001.rdfStandaard.ref

x [mm]0.2 0.4 0.6 0.8 1.0 1.20

10

20

30

40

50

60

70

80

90

Q3 [%]

SU_Demo02-05_Mix_BZ_LB_Gl15_03%_xc_min_001.rdfMix-Opzak-and-stMG4502.ref

Excellent sievecorrelation evenwith bimodal or

multimodal distributions

SummaryCorrelation Wrap-Up

53© Retsch GmbH

CAMSIZER® Elementary Fitting:• For samples with similar shape• Fitting of different width of distribution possible

(even multimodal distributions)• Applications: Sand, Sugar, Fertilizer, Minerals, Plastics,

Foodstuffs ... and many more• Creating a CAMSIZER® correlation method

only takes 20 minutescompared to 3 hours with competitive instruments

Samples with varying particle shape, e.g. abrasiveswill need different fitting files or CAMSIZER Meta-Fitting®

Thank you for yourattention !

Sampling, Sieving, Imaging, Correlating the Data Between ... · If sieve analysis is used for...

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