Towards Controllability in Polymer Processing David Kazmer, PE, PhD Louisiana State University April...

Towards Controllability inPolymer Processing

David Kazmer, PE, PhD

Louisiana State UniversityApril 4th, 2008

Introduction ● Flow Control ● Temperature Control ● Injection Compression ● Future

Introduction Flow Control Temperature Control Injection Compression Future Work

Agenda

http://www.uml.edu/

1989

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1998

1999

2000

2001

2002

2003

2004

2005

Applications Engineer Intern, GE Plastics

Mechanical Engineer, GE R&D

Applications Engineer, GE Plastics

Development Engineer, GE Plastics

Tech. Programs Manager, GE Plastics

Group Leader, Moldflow IPC

Advisor, Dynisco Instruments

Director of R&D, Dynisco

BS, Mechanical Engineering

MS, Mechanical Engineering

‘Future Professor of Manufacturing’Stanford University

PhD, Mechanical Engineering

Assistant Prof., UMass Amherst

Associate Prof., UMass Amherst

Associate Prof., UMass Lowell

Professor, UMass Lowell

Kazmer Bio


http://www.uml.edu/

http://www.uml.edu/

Unresolved Control Issues

Definition: A system is controllable if every output is connected to a control input.

Definition: A system is observable if its modes can be deduced from sensed outputs.

Polymer processing is neither! Process states & quality are largely unknown

& uncontrolled… trade-offs must be made


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The Molding Process


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Machine states can be sensed and somewhat controlled

However, there are few degrees of freedom Unable to change pressure & temperature

distribution in cavity Common trade-off:

Retool the moldor Accept sub-optimal

part quality

Flow Control


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Conventional Molding

L 1

L 3

L 2

Design of Experiments All dimensions are coupled

to machine changes No independent controllability

RPM

0.60

0.40

0.20

0.00

-0.20

Pres Vel Temp

Key:

L3

L1L2

Main

Eff

ects

Plo

t (%

in

/in

)


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What if mold behavior could be changed during the molding process?

Dynamic Feed


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Dynamic Feed


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Dynamic Feed

Results Reduced machine dependency Improved process flexibility &

controllability

RPM

0.60

0.40

0.20

0.00

-0.20

Pres Vel TempMain

Eff

ects

Plo

t (%

in

/in

)

P4P1 P2 P3

L3

L1L2

L 1

L 3

L 2


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New Valve Design

Self-regulating valve Two significant forces:

Top: control force Bottom: pressure force

Forces must balance Pin position governed by dynamic

equilibrium Melt pressure is proportional to control

force via intensification factor, I100

2

2

annulus

cylinder

annulus

cylinder

R

R

A

AI


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Flow/Control Analysis


-80

-60

-40

-20

0

20

40

60

80

0 5 10 15 20 25 30

Flow rate (cc/s) @ nominal pin position

Fo

rce

(N

)

Fpressure

Fshear

Fresultant

Results indicate2% open looperror typical

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Valve Deployment

Advantages Multi-axis melt control without

cavity pressure transducers! Injection molding & extrusion

Compact & low actuation forces All the consistency & flexibility

of Dynamic Feed ½ the cost Lower complexity with

pneumatic or electric actuators Disadvantages: patents


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Thermal Control Motivation: Control

Eliminate solidified layer during mold filling Manufacture thinner & larger products Improve part properties (gloss, strength)


x

P

T300 C

100 C

Non-isothermal

Isothermal

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Approach #1: Pulsed Cooling

Process Heat with oil Fill the mold Cool with water

Comments Long cycle time Very high energy cost Lenses & cockpit canopies


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Approach #2: Managed Heat Transfer

Process Polymer melt (red)

heats mold shell (pink) Insulator (blue) slows

heat transfer Comments

Energy efficient Limited control CDs & DVDs


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Approach #3: MHT with Gas Pre-Heat

Process Composite mold

to reduce heat transfer Pre-heat surface with

hot air Run coolant colder

to compensate for cycle time Comments

Validated at UMass Amherst Found minimal pressure

& flow control benefits

Injection MoldingMachine

Air Compressor

Inline ElectricResistive Heater

MovingMold HalfStationary

Mold HalfMold Cavity

Preheat Air

SprueBushing

Nozzle

Mold Base

Thermal Resistive Layer

Preheat Outer Layer

Sprue Busing

Preheat Air

Mold Cavity


Air Compressor




Preheat Air

SprueBushing

Nozzle


Air CompressorAir Compressor




Preheat Air

SprueBushing

Nozzle

Mold Base


Preheat Outer Layer

Sprue Busing

Preheat Air

Mold Cavity

Mold Base


Preheat Outer Layer

Sprue Busing

Preheat Air

Mold Cavity

0 10 20 30 40

Tem

per

atu

re (

C)

350

300

250

200

150

100

50

0

Pre-Heat ProfileCoolant TemperatureMold:Polymer Interface

0 10 20 30 40

Tem

per

atu

re (

C)

350

300

250

200

150

100

50

0

Pre-Heat ProfileCoolant TemperatureMold:Polymer Interface


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Approach #4: Thin Film Resistive Heaters

Process: Insulator and thin film heater

deposited on mold surface

Mold layer temperaturecontrolled

Coolant runat lower temperatureto reduce cycle time


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Thin Film Heaters


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Thin Film Heaters Thin film

heaters havevery highpower density

Excellentdynamicand absoluteresponse

0

100

200

300

400

500

600

0 50 100 150 200 250

TCX Pow er (Voltage)

Est

imat

ed M

old

Sur

face

Tem

pera

ture

(F

)

Isothermal

Conventional

Heated

Heater Voltage (V)

Mol

d S

urfa

ce T

empe

ratu

re (

F)


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Thin Film Heaters

0

100

200

300

400

500

600

0 50 100 150 200 250

Heater Power (V)

Flo

w L

engt

h (

mm

)

Heated

Conventional

Increasing themold walltemperature: Reduces or

eliminatesthe solidifiedlayer

Allows theplastic to travelfurther as measured by theflow length


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Thermal Control Even though thermal control was

achieved, Long filling times were required for viscous

flow of melt in cavity Excessive flashing

occurs due toelimination ofsolidified layer

These are BIGpractical issues


MOLDED SAMPLES

Thermal Control Conventional

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Injection Compression

How does this apply to micro/nano molding? What we’ve learned is that flow & thermal control

is expensive & limited This motivates a new process design:

Convey the bulk of the melt on the macro scale Solidified layer & pressures are not an issue

Rely on heat of polymer & local heating control toform micro & nano features

Gas entrapment & part ejection remain practical unresolved issues


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Injection Compression Process

Partly open mold Inject polymer Profile clamp

force to close mold

Adjust ThicknessChange Element Properties

Restore Old Profiles

Y

Calculate Pressure

Calculate Cavity Force

Cavity Force=Clamp Force?

Calculate Temperature

Move on to Next Time Step

N

Force


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Optical Media Molding

Injection-compression molding (coining) CDs & DVDs


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Birefringence Models

Constitutive model for flow induced stress (Wagner, M. H. et al)

dIIhtMTPt

t )(),()()(),( 121

CIσ

m

i

t

iT

i iea

g

dt

tdGtM

1

)()()()(

)()(

)3exp()1()3exp(),( 2*

1*

21 InmInmIIh

100

01)(

0)()(1

)(

22

1

t

tt

Ct


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Birefringence Models (Cont.)

2/

2/)(

d

d zrz dznn • Path difference (retardation):

tt t

rz ddtdthTtM11

2

])[}{3(),( ''

tt t

zzrr ddtdthTtMN11

2 2''1 ])[}{3(),(

00

01

if

if

dtCn

t

)()(

• Shear stress:

• First normal stress difference:

• Integral stress-optical rule

(birefringence constitutive model):rzrz nN cebirefirnen alfor vertic4 22

1

rnN ncebirefringe plane-infor 2


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Numerical Algorithm

• Incremental formulation for the integral equations:

m

i jn

nj

t

iT

in deme

a

G njinn

1

2

11

))((/))((1,13 ))((11

1

m

i jn

nj

t

iT

in deme

a

GN njin

n

1

2

1

21

))((/))((1,1 ))((11

1

nnn

jiij

nnij

nnn

jiij

nnjinnjinnjin emeGeeemeG

/

,13/

1,131/

1,131111

nnij

nnnn

jiij

nnij

nnn

jiij

nnjinnjinnjin emeGNeeNemeGN

21,131

2/,1

/1,1

21

/1,1 21111

nnn 11 nnn 11

• Solved by FDM in time domain:

demea

Gn

nj

t

tiT

iijn

njinn

n

))(( 1))((/))((

1,1311

1

demea

GN n

nj

t

tiT

iijn

njinn

n

21

))((/))((1,1 ))((11

1

deme

a

G njinn n

j

t

iT

in

))((/))((

0

mm 1 mm 12


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Simulation of Internal Stressand Post-Molding Deformation

Thermal stress/warpage In-mold: FDM (Baaijens, F. P. T. et al)

dhp σIσ

th dtrTtrp

0)(

1)(

3

1

εσ

deg dtm

i

t

id iεσ /)()(

10

2

Twu D)()(),( rzruzru drrwdr /)()(

)()( rwrw

– Out-of-mold: FEA (plate bending)


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Finite Element Discretization

Kirchhoff thin-plate elements

Elements (Divided into m layers)

Inner Edge

1 2

3

n

r1

r2 rn


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Finite Element Formulation

2

2

2

1

1

1

2222

22

)32()(6

)341()(61

)62()21(61

)64()21(61

w

u

w

u

r

z

rs

z

rr

z

rs

z

r

s

z

s

z

ss

z

s

z

srr

• Strain-displacement relationship

• Stress-strain relationship

2

1iii uBε

hεHσ

2/

2/

2

1

2d

d

r

r

T

V

Te rdrdzdV HBBHBBk

dzrdrdVd

d

r

r

TT

V

TTe

2/

2/

2

1

)(2)( hBfNhBfNR

rrrrrr

ab

ba

• Element stiffness matrix and element right-hand-side vector

RDK


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In-plane Birefringence Validation

-20

-10

0

10

20

30

40

50

60

70

80

23 28 33 38 43 48 53 58

Radius (mm)

Pa

th D

iffe

ren

ce (

nm

)

Exp.Sim.--TotalSim.--FlowSim.--Cooling

z

r

t

z

r

t


Simulation results arehighly dependent onlow temperaturemelt rheology

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1E-8

1E-6

1E-4

1E-2

1E+0

1E+2

1E+4

1E+6

1E+8

80 100 120 140 160 180 200 220 240 260 280 300

Temperature (oC)

aT

Exp.

Fitted

Tg

Melt Relaxation Modeling

WLF model fit by data at 150-280oC Truncated at at 140, 135, 130,

125oC• For T<Tref

• For T>Tref

cref

cref

TTb

TTb

Ted

eada

))((

))(( )1()log(

cref

cref

TTb

TTb

Ted

eada

))((

))(( )1()log(


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0

20

40

60

80

100

120

0 10 20 30 40 50

Packing Pressure (kgf/cm2)

Ver

tica

l D

isp

lace

men

t (m

icro

met

er)

Exp.

Sim.

Injection Compression

Provides higher data density & lower costs

Optical media simulation used for Process development and optimization Development of new polymeric materials

0

20

40

60

80

100

120

95 100 105 110 115 120

Mold Temperature (oC)

Ver

tica

l D

isp

lace

men

t (m

icro

met

er)

Exp.

Sim.

0

20

40

60

80

100

120

295 300 305 310 315 320 325

Melt Temperature (oC)

Ver

tica

l Dis

pla

cem

en

t (m

icro

met

er)

Exp.

Sim.


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Current Work: Nano Self-Assembly

Assist design & optimization of nano-production processes Nano features to self-assembly according to

surface template Morphology development in composite

polymeric systems is a function of: Contractive behavior of polymer(s) to minimize

free energy density (phase separation) Expansive behavior of polymer(s) to diffuse

into other material(s) Boundary conditions to locally drive

morphology via surface functionalization of template


http://www.uml.edu/

Template Assisted Morphology Development

Attraction to polymer A

Attraction to polymer B

Neutral to both A & B

Attraction Factor:0.04A/B:40/60=1.6e-5

4096Steps: 4 32 256

http://www.uml.edu/

# Vars R2R2

adj

Mallows CP F

ill T

ime

Pac

k T

ime

Rec

over

y T

ime

Coo

l Tim

e

Cyc

le T

ime

Scr

ew D

ispl

acem

ent F

illin

g

Scr

ew D

ispl

acem

ent P

acki

ng

Scr

ew D

ispl

acem

ent C

oolin

g

Fill

Spe

ed

Vel

ocity

at T

rans

fer

Pac

king

Vel

ocity

Vel

ocity

dur

ing

Rec

over

y

Max

Fill

Pre

ssur

e

Avg

InjP

ress

ure

Fill

ing

Hol

d P

ress

ure

Bac

k P

ress

ure

Inje

ctio

n E

nerg

y

Rec

over

y E

nerg

y

Mel

t Vis

c du

ring

fillin

g

Mel

t Vis

c du

ring

pack

ing

Avg

Noz

zle

Tem

pera

ture

Avg

Met

erin

g T

empe

ratu

re

Avg

Fee

d T

empe

ratu

re

Avg

Coo

lant

Tem

pera

ture

Cus

hion

Sho

t Siz

e

1 38.5 37.8 151.51 37.0 36.3 157.32 70.3 69.6 30.72 61.5 60.6 64.73 77.3 76.5 5.63 76.1 75.3 10.24 77.8 76.8 5.74 77.7 76.7 6.15 78.7 77.4 4.35 78.7 77.4 4.46 79.5 78.0 3.26 79.3 77.8 4.17 79.8 78.0 4.27 79.6 77.9 4.78 80.2 78.2 4.48 80.2 78.2 4.5

Current Work: Quality Control

Statistical analysis indicates need for orthogonal process state information


http://www.uml.edu/

Current Work: Sensing

Developing five way in-mold “smart” sensor Infrared melt temperature, Melt pressure, Melt velocity, Melt viscosity, Part shrinkage

Each already validatedindependently… fiveyears to realization


Operation Notes: Plastic part pushes on sensor head Aluminum sleeve provides compliant deflection Steel rod on contact provides greater stiffness PZT ring outputs charge, Q, with stress, Deflection, , back calculated from joint rod and sleeve compliance.

Q

Q

High deflection regime for shrinkage measurement

Low deflection regime for pressure measurement

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Acknowledgements Multiple NSF & other grants LSU faculty:

Sungook Park, Michael C. Murphy, Dimitris Nikitopoulos, Steve Soper, & others

UMass PhD Students, especially Bingfeng Fan & Steve Johnston


http://www.uml.edu/

Towards Controllability in Polymer Processing David Kazmer, PE, PhD Louisiana State University April...

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