LIST - Polymer Processing Seminar · LIST - Polymer Processing Seminar. 3 p3 SC-Consultants :...
Transcript of LIST - Polymer Processing Seminar · LIST - Polymer Processing Seminar. 3 p3 SC-Consultants :...
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Control the process to control the Product
LIST - Polymer Processing Seminar
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Control the process to control the Product
Introduction to Twin screw process simulation
how does it work ...
LIST - Polymer Processing Seminar
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3p3
SC-Consultants : industrial processes simulation
3 main activities
Software developmentConsultingStrategic Initiatives (R&D)
Strong R&D partnership
Bonn UniversityCEMEFFraunhofer ICT
1StrategicInitiatives
Services
Software
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4p4
SC-Consultants background
Mechanics impact on the process
Extrusion Mixing
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5p5
Ludovic® software
Corotating twin screw extruder simulation
Generic applicationAll packagedProcess-driven resultsFast overview
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6p6
What is modeling ?
Reproducing a physical phenomena by a model
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7p7
Software environment
What is simulation ?
Reproducing a physical phenomena by a model
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8p8
Software environment
What is simulation ?
Reproducing a physical phenomena by a model
Input
Computation
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9p9
Software environment
What is simulation ?
Reproducing a physical phenomena by a model
Input
Computation
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10p10
The interest of modeling – different focuses
1 Simulation
For checking1 set of operating conditions
Process parameter 2e.g. : throughput (kg/h)
Process parameter 1e.g. : screw speed (rpm)
Increasing Operating Domain analysis
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11p11
The interest of modeling – different focuses
1 Simulation
For checking1 set of operating conditions
Comparison of simulations
For optimizingFew sets of data
Increasing Operating Domain analysis
Process parameter 2e.g. : throughput (kg/h)
Process parameter 1e.g. : screw speed (rpm)
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12p12
The interest of modeling – different focuses
1 Simulation
For checking1 set of operating conditions
Comparison of simulations
For optimizingFew sets of data
1 DoE / QbD
For anticipatingHundred of SimulationsCovering a functioning domainExample : new formulation
Increasing Operating Domain analysis
Process parameter 2e.g. : throughput (kg/h)
Process parameter 1e.g. : screw speed (rpm)
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Control the process to control the Product
3Twin Screw simulation
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14p14
The polymer process in TSE
Material + additives + energies = Compounds
Mechanical energy
Shear RatePressureSelf heatingViscosity evolution...
145°C
Conduction energy
Temperature +/-MeltingViscosity evolution...
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15p15
TSE – playing with process parameters
Torque (%) SME (kWh/t) T°C P (bar)
Throughput(kg/h)
ResidenceTime(s)
Screw Speed(rpm)
rpm rpm rpm rpm rpm
Kg/h Kg/h Kg/h Kg/h Kg/h
%
% kWh/t
kWh/t
°C
°C
Bar
Bar
s
s
With Ludovic® : going further than rules of thumb
Example of common process parameters impact
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16p16
Why TSE Simulation
Controlling the thermo-mechanical history from the material to the product
Getting the material sensitivityGetting the process trendsCutting down the trials
Materials + Process/Energies = PRODUCT
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17p17
Controlling the process
Hands on the energy balance
Checking the machine capabilitiesChecking the mixing efficiency of the process
37%Conduction Energy
56%Dissipated Energy
2% Melting Energy
5% Solid transport Energy
Mean residence time................................ = 37.8 sDissipated Energy (viscous dissipation - screw).... = 118 kWh/tSpecific energy (solid transport - screw).......... = 10 kWh/tMelting Energy (screw)............................. = 3 kWh/tDissipated Energy (viscous dissipation - die)...... = 0 kWh/tTotal Conduction Energy (Screw+Die).............. = -77 kWh/tTotal product Energy............................... = 54 kWh/tTotal extruder Energy (abs. value of conduction). = 208 kWh/tPower engine....................................... = 3 kWTorque / Shaft..................................... = 63 N.mSME................................................ = 131 kWh/t
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18p18
Controlling the Product
Thermo-mechanical evolution
Displayed along the screw profileDescribes the material history
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Control the process to control the Product
44 Leistritz Experiments
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20p20
Experiments vs Simulations
Background
During a workshop at Axel'one platform (1)Goal : showing the reliability of the Ludovic® results
The Configuration
Leistritz ZSE 18 MAXX 44DPP (H7020) + CaCo3
(1) https://www.axel-one.com/ppi-plateforme-procedes-innovants
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21p21
The ZSE 18 – the screw profile
The functional areas
Conveying zone Melting zoneMixing zone
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22p22
Torque Comparison
CaCo3
Torque (%)
300rpm 600rpm 900rpm
Experiments
Simulations
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23p23
Pressure
CaCo3
Pressure (Bar)
300rpm 600rpm 900rpm
Experiments
SimulationsMeasurements performed at the screw head
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24p24
Temperature Comparison
CaCo3
Temperature (°C)
300rpm 600rpm 900rpm
Experiments
SimulationsMeasurements performed at the die exit with a sensor
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Control the process to control the Product
Performing a scale upFrom ZSE18 to
ZSE35iMAXX machine
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26p26
The targets
From a ZSE 18 mm
To a ZSE 35iMAXX
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p27
Scale upMethodology
1.
2.
3.
Lab scale preparation
Industrial scale definitionScrew designBest Trends
Industrial scale OPTIMIZATION
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p28
1. Scale up – from the lab scaleStep by step
1. Define the best configuration in ZSE18 between :
2 materials PP + 10% CaCo3
PP + 50% CaCo3
Rotation speed [300;600;900] RPM
Throughput = 4 kg/h
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p29
1. Scale up – from the lab scaleZSE18 scale : temperature profile at 600 RPM
For 600 RPM : Temperature : 230°C – 280°CThe temperature of product PP + 50% CarCo3 is too high
50%
10%
280°C
230°C
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p30
1. Scale up – from the lab scaleStep by step
1. Best configuration in ZSE18 :
Material : PP + 10% CaCo3Identified optimized process parameters at lab scale :
RPM = 600 tr/min
Q = 4 kg/h
T°barrel
= 200°C
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p31
2. Scale up – to the industrial lineBuild the ZSE35 configuration
?ZSE35 48D
ZSE18 44D
Melting zone
Conveying zone
Mixing zone
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p32
2. Scale up – to the industrial lineBuild the industrial configuration
ZSE35
ZSE18
ZSE35
ZSE35
P1
P2
P3
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p33
2. Scale up – to the industrial lineDefine the process parameters (RPM, Q, T°) (estimation)
Constraints on Products characteristics :
Temperature : max 260°CSME ~ 260 kWh/t, > 200 kWh/tResidence time : as close as possibleMaximize throughput
Constraints on extruder for ZSE35:
Torque max (per shaft) : 694 NmMotor Power (kW max) : 91,8Screw speed max : 1200 rpm
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p34
2. Scale up – to the industrial lineDefine the process parameters (RPM, Q, T°) (estimation)
600 RPM
Regulation temperature = 200°C
Throughput estimation :
Qind=Q lab(D ind
Dlab)
3
Qind=4(3518
)3
~ 30 (kg/h)
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p35
2. Scale up – to the industrial lineLab scale vs industrial scale - Temperature
T° limit
P1
P2
P3
ZSE18
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p36
2. Scale up – to the industrial lineLab scale vs industrial scale – cumulated strain
P1
P2
P3
ZSE18
● Cumulated strain is a quantitative mixing index for compounding
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p37
2. Scale up – to the industrial lineLab scale vs industrial scale – dissipated energy
P1P2
P3
ZSE18
● Dissipated energy is a quantitative mixing index for coumpounding
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p38
2. Scale up – to the industrial lineZSE18 vs industrial scale - SME
● The SME in industrial scale for P1 & P2 is lower than the lab scale but still ok according to criterionThe SME for P3 is larger than lab scale, so criterion respected
ZSE18 ZSE35P1
ZSE35P2
ZSE35P3
240260 235 350
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p39
2. Scale up – to the industrial lineZSE18 vs industrial scale - RTD
● The residence time distribution is quite close from the ZSE18 scale for P1 & P2. RTD is a little bit longer for P3.
P1 P3
P2
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p40
P1 P2 P3
Temperature
SME
RTD
Cumulated strain
Dissipated energy
3. Scale up – process optimization
● Selection of P3 to optimize process parameters using DoE
Which industrial configuration for optimization ?
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p41
3. Scale up – process optimizationWhich industrial configuration for optimization ?
Regarding the results comparison between ZSE18 and the 3 proposed configurations at scale ZSE35 :
P1 provides a good SME & RTD close to ZSE18 one. T°C profile is a little bit high but still acceptable. Cumulated strain too low P2 provides a good SME. Mean residence time is close to ZSE18 one but the distribution is quite different. T°C profile is a little bit high but still acceptable. Cumulated strain too low P3 provides a high SME & RTD a little bit too long comparing to ZSE18 one. T°C profile is a little bit too high but still acceptable. Good cumulated strain
Selection of P3 to optimize process parameters using DoE
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p42
3. Scale up – process optimizationZSE35 optimization
DoE settings up
Process parametersThroughput : [20;100] kg/h / 17 steps
RPM : [500;1000 RPM] / 11 steps
Observed Results RTD
SME
Dissipated energy
Cumulated strainTorqueTemperature max
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p43
3. Scale up – process optimizationZSE35 optimization
Selected case (steady zone)
Rotation speed tr/min = 1000
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p44
3. Scale up – process optimizationZSE35 optimization – comparison with ZSE18
T° limit
ZSE18
ZSE35
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p45
3. Scale up – process optimizationZSE35 optimization – comparison with ZSE18
ZSE18
600 rpm – 30kg/h
ZSE35
650 rpm - 55kg/h
Same target in terms of SME
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p46
3. Scale up – process optimization
SME > 200 kWh/t : criterion is respected
ZSE35 optimization – comparison with ZSE18
ZSE18
600 rpm – 30kg/h
ZSE35
650 rpm - 95kg/h
Industrial conditions : increasing the throughput
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p47
Scale up - ConclusionFrom ZSE18 to ZSE35 scale
Identification of the key targets
Easiness in the screw profile translation
Screening the functioning domain
Optimizing the conditions
In a virtual way !!
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p48
Ludovic® – driving the process efficiency
Experiments constraints
Experiments costsMeasures difficultyMechanics knowledgeTime consuming
Ludovic® answers
Virtual trialsModels for inputReadable resultsOnly a few minutes
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p49
Going further with Ludovic®
Twin Screw Course (TSC)
On March 21-22, 2018On the French Riveira (Sophia Antipolis)2 day course on Twin Screw mechanisms and simulation
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50p50
Thanks for your attention
Http://www.scconsultants.comHttp://www.mixingsimulation.technology
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Control the process to control the Product
5Ludovic® functioningThe modelThe advantages
5
Going Further
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52p52
The model
Flat geometry modeling
Screw partition in computation domainsC-Chamber areasRobust modelFast computation
C-chamber scheme for a conveying element
Flattened geometry for a two-flight screw
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53p53
Dedicated to corotating TSE
Dedicated environment
Customizable screw elementsProducts library3 Tabs technology for simulation definition
1 32Screw Design Product selection Parameters
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Control the process to control the Product
5Ludovic® solutionsQuick adaptationFast ROIIncluding support
6
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Ludovic® benefits
Speeding up the time to market !
Saving 30% timeSaving 50% materials and trialsControlling the processOptimizing the product
6 trials
● 3 days (prep. + trials + cleaning)● 2 persons● 200 kg material
● Total human cost : ~4 200,00€● Material cost : 400,00€
90 simulations
● 3 hours (prep. + trials + cleaning)● 1 person● 0 kg material
● Total human cost : 300,00€● Material cost : 0,00€
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For more details
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References
http://www.scconsultants.com
http://www.mixingsimulation.technology
http://support.scconsultants.com
Http://www.cemef.mines-paristech.fr
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Sciences Computers Consultants(Headquarters)
10 rue du plateau des GlièresF-42000 Saint Etienne+33 (0)4 77 49 75 80
Sciences Computers Consultants Inc.(Sales office North America)1455 rue Drummond, Suite B
Montréal H3G 1W3+1 514 687 4708
Http://www.scconsultants.comHttp://www.mixingsimulation.technology