© 2012 Autodesk

Study on effect of CRIMS data on warpage simulation and possibility of using supplement CRIMS data

Speaker Name: Venkatesh Aungadu KuppuswamySpeaker Title : Senior Staff Materials Engineer, Motorola Solutions Inc, Plantation, FL

© 2012 Autodesk

Content

• 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. PVT3. Thermal

conductivity4. 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

Moldflow withobserved parameters

Compare predicted with actual

With CRIMS+

Without CRIMS

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Overview of the Experiment Factors that Affect Warpage

Warpage

Material Cooling Channels Part Design

GatingProcessing

Packing Press.

Fill Time, Speed

Melt Temp.

Type

% Filler

Filler Properties

Shrinkage

Size, Location

Flow Rate

Fluid Used

Temperature

Size

Location

Number

Wall Thickness

Size

Shape

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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 UnfilledAmorphous 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

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Part, Material and

Process Selection

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Overview of Experiment

1) Battery Cover (Flat shaped part)

2) Battery housing (Box shaped part)

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Overview of the Experiment

3) Football housing

(Box shaped with bosses and ribs)

4) Speaker Bracket

(Thick and thin combination with weld line)

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Overview of the Experiment

5) Seal Frame

(Long flow front with 8 flow front)

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Overview of the Experiment

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

  Unfilled Filled

Crystalline Delrin 500 ( POM) Valox 420 **( PET+GF)

Amorphous Cycoloy 1200(PC+ABS)

and Lexan 141 R (PC)

IXEF 1032(polyarylamide + GF) and Grivory GV-5H ( PA+GF)

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Moldflow Simulation Results

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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

Relative change in Warpage (with and without CRIMS) from Moldflow simulations

54321

0 . 9

0 . 8

0 . 7

0 . 6

0 . 5

0 . 4

0 . 3

0 . 2

0 . 1

0 . 0

P a r t

(C

RI

MS

- n

o C

RI

MS

)/

no

C

RI

MS

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

Mu

lti-

vari

ch

art

© 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

54321

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Part

(CRIM

S- no C

RIM

S)/

no C

RIM

S

12345

Material

Responses used are delta/ no-crims

Multi-vari chart for relative change in Warpage from Moldflow simulations

As part design complexity increases, predicted impact of CRIMS data increases

© 2012 Autodesk

CommentsWhen 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

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Measurement Technique

0.866

0.347

0.38

0.627

0.059

1.88

0.151

0.304

1.025

0.067

-0.063

0.774

0.747

•Equivalent points were measured on five samples for each part using an optical Smartscope•Averaged values are shown below:

© 2012 Autodesk

Warpage of Battery CoverNo CRIMS CRIMS Actual

1.880.866

0.38

CRIMS shows better prediction in Part 1

Max:1.151Max:1.079

Improvement in Prediction = 17 %

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Warpage of Battery HousingNo CRIMS CRIMS Actual

Max:1.1Max:0.6930.8970.7340.3850.475

1.0250.774

CRIMS shows better prediction in Part 2Improvement in Prediction = 33 %

1.0250.774

© 2012 Autodesk

Warpage of Football Housing No CRIMS CRIMS

Max:0.4989Max:.37000.2353

-0.2318

0.4247

-0.4506

0.32 0.4446

Delta = 1.6097Delta = 0.46 Delta = 0 .87

CRIMS shows better prediction in Part 3

Actual

Improvement in Prediction = 28 %

© 2012 Autodesk

Warpage of Speaker Bracket No CRIMS CRIMS Actual

Max:0.2793Max:0.2543

-0.0114

0.00220.0604

-0.0194

0.07980.2472

0.1305

0.10910.1320

CAD dimension thickness = 6.0 mm

CRIMS shows better prediction in Part 4

Improvement in Prediction = 8%

© 2012 Autodesk

Delta is 0 .13

Warpage of Seal Frame No CRIMS CRIMS

Max: 0.2530

Max:0.3735Max:0.3630

-0.3060

0.3581

-0.3457

0.3718

Delta is 0 .71

3D-0.2479

0.2473

Delta is 0 .48

Delta is 0 .65

Simulation with any method does not show proper prediction for Part 5

Actual

© 2012 Autodesk

Delta is 0 .13

Warpage of Seal Frame with runnerNo CRIMS CRIMS

-0.2184

0.2329

-0.2621

0.2782

Delta is 0 .53

3D-0.1579

0.1772

Delta is 0 .32

Delta is 0 .44

Actual

Simulation with any method does not shows proper prediction in Part 5

© 2012 Autodesk

Results and Discussion

© 2012 Autodesk

Regression Analysis

1.81.61.41.21.00.80.60.40.20.0

1.2

1.0

0.8

0.6

0.4

0.2

0.0

Actual

Y-D

ata

No CrimsCrims

Variable

Scatterplot of No Crims, Crims vs Actual

Ideal Condition

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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 isNo Crims = 0.116 + 0.333 ActualS = 0.226823 R-Sq = 39.3% R-Sq(adj) = 35.5%The regression equation isCrims = 0.209 + 0.573 ActualS = 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

delta crimsdelta no crims

1.25

1.00

0.75

0.50

0.25

0.00

-0.25

-0.50

Data

Boxplot of delta no crims, delta crims

Ideal Condition

© 2012 Autodesk

Probability of Good PredictionOne-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

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What is the Defect?

Inability to use CRIMS simulation process due to lack of sufficient CRIMS data in

material library

36

© 2012 Autodesk

Lexan EXL 1414Lexan EXL 1433T

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

• 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 compositionFiller contentMFIMechanical propertiesManufacturer( same is always better)

© 2012 Autodesk 39

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)

Pilot Batch Experimentation

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Tools Used• Autodesk Moldflow Insight 2010- R2• One sample t test• Test for Normality • Multivari chart• Anova

Autodesk Moldflow Plastics Insight 2010- R2

40

Part Design

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Smart Scope with Laser Option

Part being measured on smart scope

Smart scope with routine ( Screen Shot)

41

10 material were molded and measured for warpage with “Motorola Solution-supplemented CRIMS values”

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Box Plot of ‘Deltas’ of Original Cross Part

42

Delta = Actual warpage – Simulated Values

Found significant outliers on warpage observation on some of actual parts, which reflected in delta calculation

Ideal Condition

Supplemented is CRIMS Substituted

© 2012 Autodesk

Change in Part Design

Proposed part design at beginning of Project

NFL housing part used in warpage measurement, as part design was structurally good.

Part design for project was changed as warpage observed had outlier on ‘cross part design’

43

© 2012 Autodesk

Normality Plot of Raw Data with new Part Design

Normality plot of raw data

No CRIMS (NC) Normality test p-value = 0.0183D Normality test p-value = 0.296Supplement (Sup) Normality test p-value = 0.436

44

Please note:Value above 0.05 means normal data

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Box Plot and Test of equal Variance – New part

45

Test and CI for Two Variances: abs-del-nocrims, abs-del-Sup  

Statistics

Variable N StDev Varianceabs-del-nocrims 9 0.132 0.017abs-del-Sup 9 0.053 0.003

Ratio of standard deviations = 2.500Ratio of variances = 6.250

95% Confidence Intervals

CI forDistribution CI for StDev Varianceof Data Ratio RatioNormal (1.187, 5.264) (1.410, 27.706)Continuous (0.478, 6.584) (0.229, 43.347)

TestMethod DF1 DF2 Statistic P-ValueF Test (normal) 8 8 6.25 0.018Levene's Test (any continuous) 1 16 2.35 0.145Looking at the standard deviation of No CRIMS

shows that the data has unacceptability high variability, hence we are discarding no CRIMS method.

Levene test did not detect difference.

© 2012 Autodesk

Test of Variance between CRIMS and 3D for new part design

46

Test and CI for Two Variances: abs-del3D, abs-del-Sup  Method Null hypothesis Sigma(abs-del3D) / Sigma(abs-del-Sup) = 1Alternative hypothesis Sigma(abs-del3D) / Sigma(abs-del-Sup) not = 1Significance level Alpha = 0.05

 Tests  TestMethod DF1 DF2 Statistic P-ValueF Test (normal) 8 8 1.99 0.350Levene's Test (any continuous) 1 16 0.70 0.416 

This shows that we can compare 3D and CRIMS P-Value is great than 0.05, hence 3D and sup-CRIMS are identical

Ab

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lta o

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pp

lem

en

ted

CR

IMS

© 2012 Autodesk

Anova to compare 3D and CRIMS for new part design

47

One-way ANOVA: abs-del3D, abs-del-Sup  Source DF SS MS F PFactor 1 0.01192 0.01192 2.86 0.110Error 16 0.06674 0.00417Total 17 0.07865 S = 0.06458 R-Sq = 15.15% R-Sq(adj) = 9.85%

Grouping Information Using Tukey Method  N Mean Groupingabs-del3D 9 0.14369 Aabs-del-Sup 9 0.09223 A Means that do not share a letter are significantly different

ANOVA analysis shows no statistical difference between 3D and supplemented-CRIMS

Abs-del3D : absolute delta of 3DAbs-del-Sup : absolute delta of supplemented CRIMS

© 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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