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Molded Electronic Package Warpage Predictive Modelling Methodologies
Ong, Kang Eu
Wei Keat Loh
Intel Technology SdnBhd
Malaysia
Chih Chung Hsu
Jenn An Wang
CoreTech System (Moldex3D)
Taiwan
Ron W. Kulterman
Flex Ltd, Austin Tx.
USA
Haley Fu
iNEMI
Shanghai
iNEMI: Warpage Characteristics of Organic Packages, Phase 4
iNEMI Technology Roadmap 2013
•Identify package warpage as key challenge
Phase 1 (2011-13)
•Literature survey
•Establish metrology correlation between sites and increase awareness
•Reaching out to industry for component donation
•(Forming & Storming)
Phase 2 (2013-2014)
•Establish current technology package dynamic warpage (POP, PBGA, FCBGA)
•Measurement protocol (effect of “As Is”, “Bake” and Moisture Exposure Time (MET)) and sample size needed.
•(Norming)
Phase 3 (2015-2016)
•Continue establishing technology package dynamic warpage (all kind)
•Dynamic warpage measurement metrology assessment.
•(Performing)
Phase 4 (2016-2017)
•Continue establishing technology package dynamic warpage of new package technology (all kinds)
•Leverage previous effort to study the impact of Low Temperature Solder on dynamic warpage requirement
•Collaborate with simulation software to derive modeling approach in better predict the dynamic warpage
Project Scopes in Phase 4 SOW
• Characterize emerging electronic packaging technology dynamic warpage behavior to develop a better understanding of the current development of package construction and material development as listed in Table I.
• Silicon Interposer and Embedded Silicon Bridge with different package stiffeners and constructions for Heterogeneous Packaging Solution
• Next generation of POP packages that leverages wafer level process for package construction which include Panel and Wafer level molding. These also include the use of new fiber reinforced mold material for warpage control.
• System In Package/Multi Chip Package (BGA) with different configuration and layout.
• Embedded Package (embedded silicon, actives and passives)
Characterization of latest packaging technology
• To assess the impact of lower temperature solder on package warpage for those packages collected in Phase 2 and 3.
• To establish the risk level based on package technology with respect to warpage only.
Assess the impact of Low Temperature Solder (LTS) on package dynamic warpage requirement
• Establish modeling optimization approach and tools requirement to enable higher accuracy prediction technique
• Compare modeling with experiment data and identify potential gaps for further development in FEA technique
Assessment the use FEA in optimizing package warpage
3
Content
• Introduction
• Implementation details
• Results and discussions
• Conclusions
4
Disclaimer: The work here covers some feasibility study which collaborated
with iNEMI and we are not endorsing any software in particular.
Introduction: Multi-physics in Assembly Process
Incoming Materials
•Package Design –manufacturing variation
•Substrate warpage variation
•Die Warpage
•Raw materials (different material characteristics)
Electronic Package Assembly
•Process Steps
•Temperature exposure
•Time effect (Visco and creep)
•Mechanical loading
SMT Assembly
•Reflow Temperature/Transient Thermal exposure and distribution
•Mechanical interaction
•Board level SJR
•Yield
Chip Attach
•Mass Reflow
•TCB
•Non-Conductive Paste or Film
Encapsulation & Molding
•Underfill
•Injection or Compression Molding
•Molded Underfill
Lid Attach (if applicable)
•Mechanical loading
•Adhesive
•Thermal Interface Material
Ball Attach
•Mechanical loading
•Reflow temperature
Test and Final Inspection
•Mechanical loading
•Coplanarity/Warpage
Predicting electronic package warpage and managing dynamic warpage still remain as a heavy
lifting effort and difficult for industrial.
A practical warpage prediction model is critical to drive more advance package design and risk
management.
Introduction: Current Modeling Approach is it Adequate?
Create FEA Geometry,
Meshing and apply constraint
boundaries condition
and include incoming variations
Apply linear and visco-elasticity
material constitutive
properties and include different
processing steps of how materials are
added to the construction of the
package
Compute the model from the initial stress free
condition
How to account for the individual
residual stresses of the components during assembly
Post processing to extract predicted package warpage
for risk assessment with account for process, material
and incoming variation.
6
• There are a lot of work done in different scope and assumption and with different level of
success.
• Focus here include the study of the impact of
• visco-elastic constitutive property
• with time-temperature superposition (TTS) were included with a two steps shift
factor model of Arrhenius and WLF functions.
• include the chemical shrinkage (Pressure Volume Temperature Cure PVTC)
implementation. PVTC function is not widely included in general FEA tools. Some
researches found out that the pressure-volume-temperature-cure (PVTC) can
influence the amount of warpage of the package.
Bi-material model: Modeling implementation approach
• An arbitrary bi-material model evaluation was conducted to compare the material
model of linear elastic, visco-elastic, time-temperature superposition shift factor and
chemical shrinkage.
• Commercially available modeling software considered here were based on the
Moldex3D R17 and a general FEA tool called FEA-A.
• Stress analysis was computed for post mold cure induced shrinkage and followed by
time dependent thermal exposure loading to capture the evolution of warpage or
deformation.
• PVTC model is engaged to approximate the dynamic shrinkage based on transient
molding condition to predict the package behavior.
7
Materials Mold Silicon
Modulus (MPa) 18190 1172800
CTE (ppm)14.5 (T < 443 K)
53.6 (T≧443 K)2.3
Bi-material model geometry Bi-material mesh part Bi-material material properties
Mesh
1000um global size
2 elements across thickness
Total 1600 elements
Stress-strain constitutive properties
• Stress-strain constitutive properties coupled with non-linear
function of time, temperature and other field dependent variables
like cure conversion rate.
8
=
)--C( CureThermal =
)UU(2
1 T+=
TCTEhermal =T
( )( )
( )( ) klijjkiljlikijkl
tEtEC
211
)(
12
)(
−+++
+==C
Stress strain relationship
Stress equilibrium equation Stiffness tensor
Thermal induced strain
Visco-elastic constitutive behavior
• The visco-elastic properties of epoxy molding compound are in the
form of Prony series with time-temperature shift factor.
• A Prony series (also known as Generalized Maxwell model) can be
expressed as follows:
6.0E+08
2.1E+10
4.1E+10
6.1E+10
8.1E+10
1.0E+11
1.2E+11
25 50 75 100 125 150 175 200
Sh
ear M
od
uls
u
(dyn
e/c
m2)
Temperature (℃)
t = 0.1 s
t = 1 s
t = 10 s
6.0E+08
2.1E+10
4.1E+10
6.1E+10
8.1E+10
1.0E+11
1.2E+11
1.0E-10 1.0E-02 1.0E+06 1.0E+14 1.0E+22
Sh
ear M
od
uls
u (
dyn
e/c
m2)
Time (s)
T = 30 ℃
T = 60 ℃
T = 150 ℃
))(
exp(GG(t)0
1aT
tG
i
i
n
i
−+= =
))(
exp(KKK(t)0
1aT
t
i
i
n
i
−+= =
)(Taa T=Shift factorShear modulus
Bulk modulus
Visco-elastic TTS
• There are two models to describe the time-temperature
superposition (TTS):
– Arrhenius type equation
– WLF equation
• Most FEA tools can only considered one kind of TTS model.
Subroutine needed if TTS is impacted by Tref .
• Tref was 423 K (150C) in this case.
10
1.0E-10
1.0E-06
1.0E-02
1.0E+02
1.0E+06
1.0E+10
25 50 75 100 125 150 175 200
Sh
ift
Facto
r a
T
Temperature (℃)
Moldex3D
WLF
User Subroutine
( )referenceT
TTC
TTCa TT log
02
01 −+
−−=WLF equation
ref
0
T TT ))T
1-
T
1(
R
H(
=TaArrhenius type equation
C1=17.44, C2=51.6
∆HT: chemistry activation energy
R : gas constant
Curing Kinetics Mold Material Properties
11
• The combined model to investigate the curing kinetics of the given
mold because of its ability to accurately predict the experimental
data. The combined model can be expressed as follows:
( )( )nmkkdt
d
−+= 121
−=
RT
EAk 1
11 exp
−=
RT
EAk 2
22 exp
Conversion rate
A1, A2, E1, E2, m, n are model parameters
Modeling for chemical shrinkage without curing percentage effect
12
Pseudo-CTE shrinkage approach
Equivalent curing shrinkage CTE
Effective curing shrinkage CTE as function of Tg and
Filler %
Tan, Lin, et al. "Study of viscoelastic effect of EMC on FBGA block warpage by FEA simulation." 2013
14th International Conference on Electronic Packaging Technology. IEEE, 2013.
Modeling for chemical shrinkage with curing percentage effect
13
Mixing law based on CTEraw vs CTErubbery stage
PVTC - Pressure Volume Temperature Cure
approaches
Nawab, Yasir, et al. "Determination and modelling of the cure shrinkage of epoxy vinylester resin and
associated composites by considering thermal gradients." Composites Science and Technology 73
(2012): 81-87.
Hong, Li-Ching, and Sheng-Jye Hwang. "Study of warpage due to PVTC relation of EMC in IC
packaging." IEEE Transactions on Components and Packaging Technologies 27.2 (2004): 291-295.
Two domain modified Tait model
Chemical Shrinkage through PVTC with curing percentage effect
• The two domain modified Tait model is used to formulate the
specified volume of resin as below (Moldex3D implementation):
( )( )
0894.0,
if
if ,
,exp
exp
if
if ,
,
1ln1
1)1(
11
5
65
43
43
21
21
0
0/
=−=
+=
−
−=
+
+=
+−=
+−=
CbTT
PbbT
TT
TT
Tbb
TbbB
TT
TT
Tbb
TbbV
B
pCVV
VVV
t
t
t
LL
SS
t
t
LL
SS
uncuredcured
cureduncured
Conversion rate
Boundary conditions & steps
• Transient Coupled Temp-Displacement Analysis
– 2 steps; 100s each
– Convective heat transfer with 20 W/m2/K coefficient
– 5 faces (top horizontal + 4 vertical faces)
– Initial temp. 448 K / 175 ℃– Step 1 ambient temp. 298 K / 25℃– Step 2 ambient temp. 533 K / 260 ℃
Ambient temperature Temperature on chip top center node
Bi-material: Linear elastic and visco-elastic effects – no chemical shrinkage considered
16
Z displacement on top center node
• At lower temperature, the model deformed into concave shape because of the higher
contraction of the mold.
• For visco-elastic material model without the TTS, the z-displacement reduced significantly
compared to linear elastic.
• The difference is due to the modulus relaxation and stress relaxation which counters the
thermal strain.
-150
-100
-50
0
50
100
150
200
250
0 50 100 150 200
Z d
isp
lac
em
en
t (μ
m)
Time (s)
Moldex3D linear elastic
FEA-A linear elastic
Moldex3D VE-no TTS
FEA-A VE-no TTS
Visco-elastic effect
Visco elastic
(VE)
Linear elastic
Bi-material: Visco-elastic with/without TTS – no chemical shrinkage considered
17
• The concave warpage increases to -80um while convex warpage
reduces to 19.32um.
• As the temperature reduce, the modulus increases and hence the
warpage magnitude increases towards the linear elastic case.
Z displacement on top center nodeVisco-elastic with TTS
-100
-80
-60
-40
-20
0
20
40
60
80
0 50 100 150 200
Z d
isp
lac
em
en
t (μ
m)
Time (s)
Moldex3D VE-no TTS
FEA-A VE-no TTS
Moldex3D VE-TTS
FEA-A VE-TTS Visco elastic
(VE) with TTS
Visco elastic
(VE) without
TTS
Bi-material: Effects of PVTC based chemical shrinkage
18
Z displacement on top center node
• Including chemical shrinkage (1% or 2%) increase the bi-material z displacement during
the cool down.
• During the first 100 second, no significant difference in the z-displacement due to the
conversion rate only increased by 1%.
• The heating cycle speeds up the chemical reactions to reach the 100% conversion rate.
Temperature and conversion
-140
-120
-100
-80
-60
-40
-20
0
20
40
0 50 100 150 200
Z d
isp
lacem
en
t (μ
m)
Time (s)
VE-TTS
VE-TTS with 2% chemicalshrinkage
VE-TTS with 1% chemicalshrinkage
70
80
90
100
110
270
320
370
420
470
520
570
0 50 100 150 200
Co
nvers
ion
(%
)
Tem
peratu
re (K
)
Time (s)
Temperature (K)
Conversion %
Conclusions
1. The use of bi-material system in this paper demonstrates the impact of
transient thermal structural analysis coupled with the effect of the visco-
elastic, time-temperature superposition (TTS) and the pressure-volume-
temperature-cure (PVTC) material model implementation.
2. The structural and thermal solutions are consistent or closely match
between a general FEA and Moldex3D for both linear and non-linear
elastic cases.
3. The visco-elastic implementation on the bi-material model captures the
reduction of z-displacement compared to linear model.
4. The TTS principle which interpolated the material properties based on
time and temperature field must be taken into consideration for the
actual assembly process history.
5. PVTC should not be neglected as the predicted value can be highly
influenced by conversion percentage of the mold.
6. The logical step for this industrial project is to validate the effect seen on
the visco-elastic behavior and the chemical shrinkage impact and
evaluate all these different approaches
19
0.515
0.520
0.525
0.530
0.535
0.540
0.545
0.550
0.555
25 50 75 100 125 150 175 200 225 250 275 300
Sp
ecif
ic v
olu
me
(cm
3/g
)
Temperature (∘C)
Cured state, 0.1MPa
Uncured state (1.0%), 0.1MPa
Uncured state (2.0%), 0.1MPa
△V (2.0%), 260oC
△V (1.0%),
260oC
Two additional chemical shrinkage
values of 1% and 2%