Study on effect of CRIMS data on warpage
simulation and possibility of using supplement
CRIMS data
Speaker Name: Venkatesh Aungadu Kuppuswamy
Speaker Title : Senior Staff Materials Engineer, Motorola Solutions Inc, Plantation, FL
© 2012 Autodesk
Content
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What is CRIMS?
Overview of the Experiment
Part, Material and Process Selection
Moldflow Simulation Results
Injection Molding Study
Comparing Actual and Simulation Data
Conclusions
Acknowledgements
© 2012 Autodesk
What is CRIMS
CRIMS = Corrected Residual In-Mold Stress
Moldflow Simulation uses the following material parameters:
1. Viscosity
2. PVT
3. Thermal
conductivity
4. Specific heat
capacity
5. Shrinkage (CRIMS)
•A1, A2 and A3 coefficients modify the parallel shrinkage
A4, A5 & A6 modify perpendicular shrinkage
• A1, A2, A4 and A5 are scaling factors, where as A3 and A6 are
shrinkage values
© 2012 Autodesk
Overview
of the
Experiment
© 2012 Autodesk
Overview of the
Experiment
Moldflow DOE
Look for significant D
Molding trials
Perform measurement
With CRIMS
+
Without CRIMS
Moldflow with
observed parameters
Compare predicted
with actual
© 2012 Autodesk
Overview of the Experiment
Factors that Affect Warpage
Cooling Channels
Material
Type
Part Design
Wall Thickness
Size, Location
% Filler
Size
Flow Rate
Filler Properties
Shape
Fluid Used
Shrinkage
Temperature
Warpage
Packing Press.
Size
Fill Time, Speed
Melt Temp.
Processing
Location
Number
Gating
© 2012 Autodesk
Overview of the Experiment
Item
Descriptions
Part Complexity
1) Battery Cover , 2) Battery Housing , 3) Foot Ball Housing 4)
Speaker Bracket, and 5) Seal Frame
Material
Crystalline filled and Unfilled
Amorphous filled and Unfilled
[ 1) Lexan 141R, 2) Cycoloy C1200, 3) Ixef 1032, 4) Grivory GV5H,
and 5) Delrin 500 P]
Packing Pressure 60 % , 80 % and 100% of fill pressure
© 2012 Autodesk
Part, Material
and
Process Selection
© 2012 Autodesk
Overview of Experiment
1) Battery Cover (Flat
shaped part)
2) Battery housing (Box
shaped part)
© 2012 Autodesk
Overview of the Experiment
3) Football housing
4) Speaker Bracket
(Box shaped with bosses and ribs)
(Thick and thin combination with weld
line)
© 2012 Autodesk
Overview of the Experiment
5) Seal Frame
(Long flow front with 8 flow front)
© 2012 Autodesk
Overview of the Experiment
Unfilled
Crystalline
Amorphous
Filled
Delrin 500 ( POM)
Valox 420 **( PET+GF)
IXEF 1032(polyarylamide
+ GF) and Grivory GVCycoloy 1200(PC+ABS) 5H ( PA+GF)
and Lexan 141 R (PC)

DOE was done in simulation to reduce molding operation
 5 parts x 5 materials x 3 process conditions x 2 options for
shrinkage data = 150 simulation runs
 ** = Additional material evaluated
© 2012 Autodesk
Moldflow Simulation Results
© 2012 Autodesk
Simulation Results
Relative
change in =
Warpage
Max deflection
predicted
With CRIMS
Max deflection
predicted
Without CRIMS
Max deflection
predicted
Without CRIMS
© 2012 Autodesk
Simulation Results
I n d i v i d u a l
V a l u e
P l o t
o f
( C R
I M
S -
n o
C R
I M
S ) / n o
C R
I M
S
0 . 9
C R IM S ) / n o
( C R IM S - n o
Multi-vari chart
C R IM S
0 . 8
0 . 7
0 . 6
0 . 5
0 . 4
0 . 3
0 . 2
0 . 1
0 . 0
1
2
3
P a
4
5
r t
Relative change in Warpage (with and without CRIMS) from Moldflow simulations
© 2012 Autodesk
Dot Plot to Select Molding Trial
Part
Material
Packing Pressure
Battery Cover
Grivory GV-5H
80 %
Battery Housing
Ixef- 1032
100 %
Football Housing
Delrin 500P
100 %
Speaker Bracket
Ixef-1032
60 %
Seal Frame
Cycoloy C1200
100 %
Selected for Molding and CAV
© 2012 Autodesk
Simulation Results
Responses used are delta/no-crims
(CRIMS- no CRIMS)/no CRIMS
0.7
Material
1
2
3
4
5
0.6
0.5
0.4
0.3
0.2
0.1
0.0
1
2
3
Part
4
5
As part
design
complexity
increases,
predicted
impact of
CRIMS data
increases
Multi-vari chart for relative change in Warpage from
Moldflow simulations
© 2012 Autodesk
Comments
 When
macros were used to create multiple
Moldflow study files, check to see the log file
to verify the simulation process settings are
represented from process setting.
 In Moldflow, after analysis, create a new
anchor plane to translate all warpage values
into positive co-ordinates.
© 2012 Autodesk
Comparing Actual and
Simulation
© 2012 Autodesk
Measurement Technique
•Equivalent points were measured on five samples for
each part using an optical Smartscope
•Averaged values are shown below:
0.747
0.866
1.88
0.38
0.059
0.347
0.627
0.774
-0.063
0.067
1.025
0.304
0.151
© 2012 Autodesk
Warpage of Battery Cover
No CRIMS
Max:1.079
CRIMS
Actual
Max:1.151
0.866
1.88
0.38
CRIMS shows better prediction in Part 1
Improvement in Prediction = 17 %
© 2012 Autodesk
Warpage of Battery Housing
No CRIMS
CRIMS
Max:1.1
Max:0.693
0.475
0.385
Actual
0.734
0.897
0.774
0.774
1.025
1.025
CRIMS shows better prediction in Part 2
Improvement in Prediction = 33 %
© 2012 Autodesk
Warpage of Football Housing
CRIMS
No CRIMS
Max:.3700
0.2353
0.32
-0.2318
Delta = 0.46
Max:0.4989
0.4247
Actual
0.4446
-0.4506
Delta = 0 .87
Delta = 1.6097
CRIMS shows better prediction in Part 3
Improvement in Prediction = 28 %
© 2012 Autodesk
Warpage of Speaker Bracket
No CRIMS
Max:0.2543
CRIMS
Max:0.2793
0.0604
0.2472
0.0022
-0.0114
Actual
0.1320
0.0798
0.1091
0.1305
-0.0194
CAD dimension thickness = 6.0 mm
CRIMS shows better prediction in
Part 4
Improvement in Prediction = 8%
© 2012 Autodesk
Warpage of Seal Frame
No CRIMS
CRIMS
Max:0.3735
Max:0.3630
-0.3060
-0.3457
0.3581
Delta is 0 .65
Actual
0.3718
Delta is 0 .71
Max: 0.2530
Delta is 0 .13
-0.2479
3D
0.2473
Delta is 0 .48
Simulation with any
method does not show
proper prediction for
Part 5
© 2012 Autodesk
Warpage of Seal Frame with runner
No CRIMS
CRIMS
-0.2184
Actual
-0.2621
0.2329
0.2782
Delta is 0 .44
Delta is 0 .53
3D
Delta is 0 .13
-0.1579
0.1772
Delta is 0 .32
Simulation with any method
does not shows proper
prediction in Part 5
© 2012 Autodesk
Results and
Discussion
© 2012 Autodesk
Regression Analysis
Scatterplot of No Crims, Crims vs Actual
1.2
Variable
No C rims
C rims
1.0
Y-Data
0.8
0.6
0.4
0.2
Ideal Condition
0.0
0.0
0.2
0.4
0.6
1.0
0.8
A ctual
1.2
1.4
1.6
1.8
© 2012 Autodesk
Regression Analysis
In an ideal situation, where prediction and actual warpage are same the
slope = 1
Slope of No-CRIMS = 0.33 and Slope of CRIMS = 0.57
The regression equation is
No Crims = 0.116 + 0.333 Actual
S = 0.226823 R-Sq = 39.3% R-Sq(adj) = 35.5%
The regression equation is
Crims = 0.209 + 0.573 Actual
S = 0.185396 R-Sq = 74.2% R-Sq(adj) = 72.6%
Higher the R-Sq values better the curve was fitted
© 2012 Autodesk
Box Plot
Boxplot of delta no crims, delta crims
1.25
Ideal Condition
1.00
0.75
Data
0.50
0.25
0.00
-0.25
-0.50
delta no crims
delta crims
© 2012 Autodesk
Probability of Good Prediction
One-Sample T: delta no crims
Test of mu = 0 vs not = 0
Variable
N Mean StDev SE Mean
95% CI
T
P
delta no crims 18 0.3003 0.4177 0.0985 (0.0926, 0.5080) 3.05 0.007
One-Sample T: delta crims
Test of mu = 0 vs not = 0
Variable
N Mean StDev SE Mean
95% CI
T
P
delta crims 18 0.0566 0.2897 0.0683 (-0.0874, 0.2007) 0.83 0.41824
There is a 40% higher probability of getting accurate
predictions by using CRIMS
© 2012 Autodesk
Conclusions
© 2012 Autodesk
Conclusions
By using CRIMS data for warpage simulation
 We can achieve 24 % improvement in warpage prediction
 We can reduce tooling iterations to correct for part warpage
 We can achieve substantial cost savings
© 2012 Autodesk
Acknowledgments

Marian Petrescu
 Steve Spanoudis
 Tim Dunford
 Ben Nagaraj
 Chris Sandieson
 Dave Reiff
© 2012 Autodesk
Part 2 of paper
start here
© 2012 Autodesk
What is the Defect?
Inability to use CRIMS simulation process
due to lack of sufficient CRIMS data in
material library
36
© 2012 Autodesk
Current Status of Moldflow Material Data Base
• MSI uses approximately 70 plastics materials
• Remaining materials have no CRIMS data
• Only “some“ materials have CRIMS data
Lexan EXL 1433T
Lexan EXL 1414
• Cost for CRIMS data testing is expensive.
• Testing time per batch of 4 materials is 6-8 weeks
37
© 2012 Autodesk
Pilot Batch Experimentation

Select 10 grades to test the experimentation method
 While looking for comparable material, we used the following
parameters
Material composition
Filler content
MFI
Mechanical properties
Manufacturer( same is always better)
© 2012 Autodesk
Pilot Batch Experimentation
Cycolac - C1200 (ABS +PC)
Altuglas V825 ( PMMA)
Lexan EXL 1414 ( PC)
Makrolon 2805 (PC)
LNP Thermocomp DF004 (PC 20% GF)
LNP Thermocomp DF006 (PC 30% GF)
Lexan 920 (PC)
Bayblend FR3010 (ABS +PC)
Bayblend T45 (ABS +PC)
Xylex x7300 (PC+PET)
39
© 2012 Autodesk
Part Design
Autodesk Moldflow Plastics Insight 2010- R2
Tools Used
• Autodesk Moldflow Insight 2010- R2
• One sample t test
• Test for Normality
• Multivari chart
• Anova
40
© 2012 Autodesk
Smart Scope with Laser Option
10 material were molded
and measured for warpage
with “Motorola Solutionsupplemented CRIMS
values”
Smart scope with routine ( Screen Shot)
Part being measured on smart scope
41
© 2012 Autodesk
Box Plot of ‘Deltas’ of Original Cross Part
Ideal
Condition
Supplemented is
CRIMS
Substituted
Delta = Actual warpage – Simulated Values
Found significant outliers on warpage observation on some of
actual parts, which reflected in delta calculation
42
© 2012 Autodesk
Change in Part Design
Proposed part design at
beginning of Project
Part design for project was changed as
warpage observed had outlier on ‘cross
part design’
NFL housing part used in warpage
measurement, as part design was
structurally good.
43
© 2012 Autodesk
Normality Plot of Raw Data with new Part Design
Normality plot of raw data
No CRIMS (NC) Normality test p-value = 0.018
3D Normality test p-value = 0.296
Supplement (Sup) Normality test p-value = 0.436
Please note:Value above
0.05 means normal data
44
© 2012 Autodesk
Box Plot and Test of equal Variance – New part
Test and CI for Two Variances: abs-del-nocrims, abs-del-Sup
Statistics
Variable
N
abs-del-nocrims 9
abs-del-Sup
9
StDev
0.132
0.053
Variance
0.017
0.003
Ratio of standard deviations = 2.500
Ratio of variances = 6.250
95% Confidence Intervals
CI for
Distribution CI for StDev
Variance
of Data
Ratio
Ratio
Normal
(1.187, 5.264) (1.410, 27.706)
Continuous (0.478, 6.584) (0.229, 43.347)
Looking at the standard deviation of No CRIMS
shows that the data has unacceptability high
variability, hence we are discarding no CRIMS
method.
Test
Method
DF1 DF2 Statistic P-Value
F Test (normal)
8 8
6.25 0.018
Levene's Test (any continuous) 1 16
2.35 0.145
Levene test did not detect difference.
45
© 2012 Autodesk
Test and CI for Two Variances: abs-del3D, abs-del-Sup
Method
Null hypothesis
Sigma(abs-del3D) / Sigma(abs-del-Sup) = 1
Alternative hypothesis Sigma(abs-del3D) / Sigma(abs-del-Sup) not = 1
Significance level
Alpha = 0.05
Tests
Test
Method
F Test (normal)
Levene's Test (any continuous)
This shows that we can compare 3D and CRIMS
DF1 DF2
8
8
1
16
Statistic P-Value
1.99
0.350
0.70
0.416
Abs-del3D : absolute delta of 3D
Abs-del-Sup : absolute delta of supplemented CRIMS
Test of Variance between CRIMS and 3D for new part design
P-Value is great than 0.05, hence 3D
and sup-CRIMS are identical
46
© 2012 Autodesk
Anova to compare 3D and CRIMS for new part design
One-way ANOVA: abs-del3D, abs-del-Sup
Source DF
SS
MS F
P
Factor 1 0.01192 0.01192 2.86 0.110
Error 16 0.06674 0.00417
Total 17 0.07865
S = 0.06458 R-Sq = 15.15% R-Sq(adj) = 9.85%
Grouping Information Using Tukey Method
N Mean Grouping
abs-del3D 9 0.14369 A
abs-del-Sup 9 0.09223 A
Means that do not share a letter are significantly different
Abs-del3D : absolute delta of 3D
Abs-del-Sup : absolute delta of supplemented CRIMS
ANOVA analysis shows no statistical difference between
3D and supplemented-CRIMS
47
© 2012 Autodesk
Conclusion
•Supplemented CRIMS data’s warpage and show similar values
as 3D
•No-CRIMS warpage method showed inaccurate warpage
© 2012 Autodesk
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© 2012 Autodesk