Speaker Name: Venkatesh Aungadu Kuppuswamy

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Presentation transcript:

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

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

What is CRIMS CRIMS = Corrected Residual In-Mold Stress Moldflow Simulation uses the following material parameters: Viscosity PVT Thermal conductivity Specific heat capacity 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  

Overview of the Experiment

Overview of the Experiment Moldflow DOE Look for significant D With CRIMS + Without CRIMS Molding trials Perform measurement Moldflow with observed parameters Compare predicted with actual

Factors that Affect Warpage Overview of the Experiment Factors that Affect Warpage Warpage Material Cooling Channels Part Design Gating Processing Packing Press. Fill Time, Speed Melt Temp. Type % Filler Filler Properties Shrinkage Size, Location Flow Rate Fluid Used Temperature Size Location Number Wall Thickness Shape

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

Part, Material and Process Selection

Overview of Experiment 1) Battery Cover (Flat shaped part) 2) Battery housing (Box shaped part)

Overview of the Experiment 3) Football housing (Box shaped with bosses and ribs) 4) Speaker Bracket (Thick and thin combination with weld line)

Overview of the Experiment 5) Seal Frame (Long flow front with 8 flow front)

Overview of the Experiment   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) 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

Moldflow Simulation Results

Max deflection predicted Simulation Results Relative change in = Warpage Max deflection predicted With CRIMS Without CRIMS

Simulation Results Multi-vari chart 5 4 3 2 1 . 9 8 7 6 P a r t ( C R I M S - n o ) / d i v u l V e f Multi-vari chart Relative change in Warpage (with and without CRIMS) from Moldflow simulations

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 Speaker Bracket Ixef-1032 60 % Seal Frame Cycoloy C1200 Selected for Molding and CAV

Simulation Results As part design complexity increases, predicted impact of CRIMS data increases Multi-vari chart for relative change in Warpage from Moldflow simulations

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.

Comparing Actual and Simulation

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 0.774 1.88 1.025 -0.063 0.38 0.059 0.304 0.627 0.067 0.347 0.151

Warpage of Battery Cover No CRIMS CRIMS Actual Max:1.079 Max:1.151 1.88 0.866 0.38 CRIMS shows better prediction in Part 1 Improvement in Prediction = 17 %

Warpage of Battery Housing No CRIMS CRIMS Actual Max:1.1 Max:0.693 1.025 0.774 0.475 0.385 0.734 0.897 1.025 0.774 CRIMS shows better prediction in Part 2 Improvement in Prediction = 33 %

Warpage of Football Housing CRIMS No CRIMS Actual Max:0.4989 Max:.3700 0.2353 0.32 0.4446 0.4247 -0.2318 -0.4506 Delta = 0.46 Delta = 0 .87 Delta = 1.6097 CRIMS shows better prediction in Part 3 Improvement in Prediction = 28 %

Warpage of Speaker Bracket CRIMS Actual No CRIMS Max:0.2543 Max:0.2793 0.1320 0.0604 0.2472 0.0798 0.1091 0.0022 0.1305 -0.0114 -0.0194 CAD dimension thickness = 6.0 mm CRIMS shows better prediction in Part 4 Improvement in Prediction = 8%

Warpage of Seal Frame No CRIMS CRIMS Actual Max:0.3630 Max:0.3735 -0.3060 -0.3457 0.3581 0.3718 Delta is 0 .65 Max: 0.2530 Delta is 0 .13 Delta is 0 .71 -0.2479 3D Simulation with any method does not show proper prediction for Part 5 0.2473 Delta is 0 .48

Warpage of Seal Frame with runner No CRIMS CRIMS Actual -0.2184 -0.2621 0.2329 0.2782 Delta is 0 .44 Delta is 0 .13 Delta is 0 .53 -0.1579 3D Simulation with any method does not shows proper prediction in Part 5 0.1772 Delta is 0 .32

Results and Discussion

Regression Analysis Ideal Condition

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% 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

Box Plot Ideal Condition

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 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

Conclusions

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

Acknowledgments Marian Petrescu Steve Spanoudis Tim Dunford Ben Nagaraj Chris Sandieson Dave Reiff

Part 2 of paper start here

What is the Defect? Inability to use CRIMS simulation process due to lack of sufficient CRIMS data in material library

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

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)

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)

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

Smart Scope with Laser Option 10 material were molded and measured for warpage with “Motorola Solution-supplemented CRIMS values” Smart scope with routine ( Screen Shot) Part being measured on smart scope

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

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.

Normality Plot of Raw Data with new Part Design 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

Box Plot and Test of equal Variance – New part Test and CI for Two Variances: abs-del-nocrims, abs-del-Sup   Statistics Variable N StDev Variance abs-del-nocrims 9 0.132 0.017 abs-del-Sup 9 0.053 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) 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 Looking 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.

Test of Variance between CRIMS and 3D for new part design Abs-del-Sup : absolute delta of supplemented CRIMS Abs-del3D : absolute delta of 3D 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 DF1 DF2 Statistic P-Value F Test (normal) 8 8 1.99 0.350 Levene'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

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

Box plot for new part design Abs-del-nocrims: absolute delta of noCRIMS (Original) Abs-del3D : absolute delta of 3D Abs-del-Sup : absolute delta of supplemented CRIMS Note :Ideal response is zero From above data it is clear that the original method is less precise than proposed method. This confirms with results from project1: CRIMS methods is 29% more accurate than no-CRIMS

Conclusion Supplemented CRIMS data’s warpage and show similar values as 3D No-CRIMS warpage method showed inaccurate warpage

Autodesk, AutoCAD* [*if/when mentioned in the pertinent material, followed by an alphabetical list of all other trademarks mentioned in the material] are registered trademarks or trademarks of Autodesk, Inc., and/or its subsidiaries and/or affiliates in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders. Autodesk reserves the right to alter product and services offerings, and specifications and pricing at any time without notice, and is not responsible for typographical or graphical errors that may appear in this document. © 2012 Autodesk, Inc. All rights reserved.