Siemens Digital Industries Software - Virtual Manufacturing...
Transcript of Siemens Digital Industries Software - Virtual Manufacturing...
Virtual Manufacturing EmpowersDigital Product Development
Case Study E-Coat SimulationFrank Pfluger Klaus Wechsler
Abstract
Recent progress in simulation methods for the manufacturing industry has reduced theneed for expensive test hardware which could be gratis used in manufacturing. Usingmanufacturing simulation tools starting at the design stage helps to optimize productdevelopment and corresponding manufacturing systems. Whenever there is a need foran early design input in order to ensure quality and manufacturing costs - virtualmanufacturing methods will have a profitable chance.
For the case study E-Coat simulation STAR-CCM provides an improved workflow fromCAD-data and meshing to E-coat deposition as well as modeling of fill and drainbehaviors in vehicle paint shops. Simulation results provide the design engineer withanswers to questions such as ´is the E-Coat providing corrosion protection in all thecavities´? or ´is there a corrosion risk based on air bubbles or paint ponds´?
The combination of an implemented fast algorithm with the chance of describingcustomer developed material properties by Field Functions allows best fit to complexchemical material behavior. Customized material development is kept insidecustomers. Based on process knowledge we are also providing multiple simulationsupport.An overview of future manufacturing simulation topics will be given.
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Virtual Manufacturing is a Consequence ofHardware Reduced Digital Product Development
Doing it in a physical way takes too long.Whenever there is a need for an early design input in order to ensurequality and manufacturing costs:Virtual Manufacturing methods will have a profitable chance.
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The E-Coat Deposition Process ProvidesCorrosion Protection in all Cavities
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Overview of the E-Coat Simulation Steps
BIW-Meshing( for ex. Wrapper,Boolean Unite)
E-Coat Dip-Tank(Paint Thickness onsurfaces and cavities)
Dipping in:(Air Bubbles,Pressure Distribution)
Dipping Out(Puddles, Drainage -Time, Pressure Distr.)
Data Freeze ofDigital ProductDevelopment
Suggestions for Design OptimizationGoal: Corrosion protective E-Coat thickness, minimized
air bubbles and puddles in all parts and cavities….)
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E-Coat Modeling: Deposition of charge carrying paint polymers.Increasing resistance gives a chance for deposition inside cavities
Electrolyte
BIW=Cathode
Paint material:..solids (pigments, resin/binder,.),solvent (de-ionized water) and co-solvents(glycol ether..)Conductivity is mainly based on theresin fraction but sensitive to carryoverof conductive pre treatment materialsfrom previous dipping steps ..
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Electro Static Paint
E-Coat
E-Coat Modeling: ..a small Chemical Plant..
Anode
- Anode:Anolyte Circulation with influenceon pH and film re-dissolution.
- Dip Tank:Mixture of old (aged) and new materialas well as recirculation from Rinse Tank.Needs permanent agitation and precisetemperature control.
- Pretreatment:Carryovers affect conductivity.
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Input Parameters of StandardDeposition Model
Range of Values formcalibration measurements
cP: Coulomb efficiency 2-4·10-5 kg/As
ρP: Paint layer density 1200-1800 kg/m³
rP: Paint layer resistivity 2-5·106 Ωm
q0: Minimum Accumulated ´Activation Charge ´whichis necessary to start deposition in standard material)There is no deposition as long as q<q0
300-400 As/m²
σliquid: Bath (Electrolyte) conductivity 0.14-0.22 S/m
Equations of the STAR-CCM+ StandardElectro-Deposition Model
PPLPL
minnP
PPL rdt
dh
dt
dRjj
ρc
dt
dh
dtnjqwithqqif0
qqifnjj 00
0min
dtjqwithqqif0
qqifjj n
0
0nmin
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ℎ Paint layer thickness in m
Paint layer resistance in Ωm2
Specific electric current in A/m2
ℎ Paint layer thickness in m
Paint layer resistance in Ωm2
Specific electric current in A/m2( ) Electric Potential at top of paint layerin V
Example of Enhanced (Customized) Electro-Deposition ModelUsing Field Functions for Detailed Calibration Measurements
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PPLPL
minnP
PPL rdt
dh
dt
dRjj
ρc
dt
dh
dtjJwithJJif0
JJifjj 2
n2
20
2
20
2n
min
Input Parameters of Enhanced DepositionModel: - Variable Coulomb Efficiency Cp
- Deposition Starts if J2 > J02
Cp(t) = f( ( ), (t))(fb, C2u, C1u, C0u = based on detailedcalibration measurements)
cP: Coulomb efficiency (1-exp(- ))*(fb*exp(- /h0))+(-C2U*U²+C1U*U+C0U)
ρP: Paint layer density 1200-1800 kg/m³
rP: Paint layer resistivity 2-5·106 Ωm
J02: Minimum Accumulated ´Activation Work ` (which is
necessary to start deposition.There is no deposition as long as J2 < J0
2A2s/m4
σliquid: Bath (Electrolyte) conductivity 0.14-0.22 S/m
Calibration of E-Coat Simulation Parameters:(1) Using Existing Real Parts (if CAD Data are Available)
Where can these data be found:- Sometimes paint shop regularly opens
parts for quality assurance- Durability and other testing departments
might have opened partsCalibration:- Mesh real part and tank and adjust the
parameters of the deposition model until´best parameter fit´ is reached.
- Use conductivity and paint layer densityfrom direct measurement/supplier.
E-Coat Thickness (µm)
Provides a fast pragmatic calibration withfocus to final (corrosion relevant) thickness
x = measurementx
x
x
Inner:x = 18 µm
Outside:x = 25 µm
Hidden:x = 8 µm
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Calibration of E-Coat Simulation Parameters:(2) Using Calibration Tubes Fixed to an Existing Part
Preparation:- Tubes are fixed to a part being coated- Tubes are opened and measured inside
Calibration:- CAD model of tubes should be addedto CAD model of part being simulated ata similar position.
- adjust the parameters of the depositionmodel until ´best fit´ of tubes is reached.
Provides a pragmatic calibration withstandardized test geometry
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x = measurement
Calibration of E-Coat Simulation Parameters:(3) Lab Measurements with Test Box and Plain sheets
Box is closedon bottomand side.Top is aboveelectrolyte level
100V 200V
Calibration of E-Coat Simulation Parameters:(3) Lab Measurements with Test Box (Medium Throw Power)
Measurement
Measurement
100V 200V
Calibration of E-Coat Simulation Parameters(3) Lab Measurements with Test Box (Good Throw Power)
Measurement
Measurement
Application of STAR-CCM+ E-Coat Simulation:Thickness Building over Time
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Page 16Video
Application of STAR-CCM+ E-Coat Simulation:Visualization of Thickness in Cavities
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Application of STAR-CCM+ E-coat Simulation:Example of Good Throw Power
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Application of STAR-CCM+ E-coat Simulation:Example of Medium Throw Power
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Application of STAR-CCM+ E-coat Simulation:Example of Poor Throw Power
Good
PoorMedium
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Application of STAR-CCM+ E-coat Simulation:Comparison of different Throw Power Capabilities
Good
PoorMedium
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Application of STAR-CCM+ E-coat Simulation:Comparison of different Throw Power Capabilities
Geometrical Variationwill be necessary
Holes have influence on E-Coat thicknessBigger Diameter or more holes improve corrosion protection
Application of STAR-CCM+ E-coat Simulation:Evaluation of Gemetrical Variation (for better Corrosion Protection)
Simulation of Dipping in: (1sec=1h on 32 CPU, 8 Cores/CPU)
Remaining Air Bubbles Avoid E-Coat Film Building
(Red = Trapped Air Bubbles)
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Simulation of Dipping in (1sec=1h on 32 CPU, 8 Cores/CPU)
Remaining Air Bubbles Avoid E-Coat Film Building
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Simulation of Dipping in: (1sec=1h on 32 CPU, 8 Cores/CPU)
Visualization of Trapped Air
Video
Simulation of Dipping in (1sec=1h on 32 CPU, 8 Cores/CPU)
Remaining Air Bubbles Avoid E-Coat Film Building
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Simulation of Dipping in:Positioning of additional Bleeding Holes
Final Position in E-coating shouldbe without air bubbles.Simulation gives information forpositioning of bleeding holes.
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Simulation of Dipping in:Quick optimization check by adding holes and continuing simulation
(Red = Trapped Air Bubbles)
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Holes added at t = 25s
Simulation of Dipping out:(Remaining Ponds Contaminate Next Dipping Process Step)
Video
(Blue = Trapped Dipping Liquid)
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Simulation of Dipping out:(1sec=1h on 32 CPU, 8 Cores/CPU)
(Remaining Ponds Contaminate Next Dipping Process Step)
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Simulation of Dipping out: (1sec=1h on 32 CPU, 8 Cores/CPU)
Calculation of Drainage Time
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Simulation of Dipping out:Quick optimization check by adding holes and continuing simulation:
(Blue = Residual ponds)
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Simulation of Dipping out:Quick optimization check by adding holes and continuing simulation:
(Blue = Residual ponds)
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Holes added at t = 20s
Details of Dipping out Simulation:Remaining Ponds Contaminate next Dipping Process Step
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Virtual Manufacturing
Market ReadyPilotExploration
Prospects
Clients
IndustryAwareness
E-Coat Simulationto Improve
Corrosion Protection
E-Coat Simulationto Improve
Corrosion Protection
Flow Fronts inFiber Reinforced Plastic
Manufacturing(SMC)
Flow Fronts inFiber Reinforced Plastic
Manufacturing(SMC)
AdditiveManufacturing (AM)
AdditiveManufacturing (AM)
Corrosion Test ChamberSimulation (Multiphysics
without Chemical Reactions)
Corrosion Test ChamberSimulation (Multiphysics
without Chemical Reactions)