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Moldex3D, Structural Analysis, and HyperStudy Integrated in HyperWorks Platform Anthony Yang Moldex3D

Moldex3D, Structural Analysis, and HyperStudy Integrated … · 9 global offices, local support from Michigan ... • Orientation tensor can be output to composite modeling software

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Moldex3D, Structural Analysis, and HyperStudy

Integrated in HyperWorks Platform

Anthony Yang

Moldex3D

CoreTech System and Moldex3D

The world’s largest injection molding CAE ISV

80% experienced engineering professionals

50% of employees involved in R&D activities

9 global offices, local support from Michigan

1,200+ global customers

6,000+ industrial projects validation

1,200+ Global Customers in various industry

Moldex3D leads the way of Technology development

2003: 1st complete 3D CAE for plastic molding(Solid)

2005: 1st SMP/DMP 3D CAE for plastic molding

2007: propriety automatic 3D meshing (eDesign)

2009: exclusive compatibility with multiple 3D CAD

How Moldex3D Can Help? Aesthetics and dimensional concerns

Weld line, air trap, flow mark

Flow balance and part weight

shrinkage and warpage control

Fiber orientation

Being more competitive

Cycle time reduction by removing

hot & cold spots

Mold structure optimization

Reduce mold trial & tooling cost

Reaching Lean Production

Injection conditions optimization

Clamping force reduction

Machine selection

Moldex3D Flow Analysis

Moldex3D-Flow predicts melt front, weld line, air trap,

short shot and process window…

Moldex3D Packing Analysis

7

Moldex3D-Pack simulates the density variation and melt

flow due to material compressibility

Moldex3D Cooling Analysis

• Moldex3D-Cool simulates mold temperature, cooling efficiency, hot spot,

cooling time …

Moldex3D Warpage Analysis

Moldex3D-Warp simulates the part warpage due to volumetric shrinkage

and further help to control these defects before mold is built

Moldex3D Fiber Analysis

10

Moldex3D-Fiber simulates the 3D fiber orientation and calculates the

process-induced anisotropic properties

MCM Analysis in Moldex3D

Moldex3D-MCM simulates the Multi-Component Molding, Insert molding

and over molding process.

Exclusive Moldex3D Features

Quick True 3D Analysis in Minutes:

13

Run

Simulation

Create

Cooling System Meshing

Create Runner

Set Melt Etrn Import STL

Automatic 3D hybrid meshing capability

eDesign:

Intelligent Gate Wizard

eDesign:

Intelligent Runner Wizard

Accuracy - by running FULL 3D analysis

High temperature resolution in runners

eDesign:

Intelligent Cooling System Wizard

Support the ALL cooling

system in 3D

SMP/DMP Parallel Computing with excellent

acceleration ratio

19

Moldex3D R9.1 Solid-Flow Parallel Computing Performance on an Intel Core i7 Cluster - Speed Up Ratio

1.00

2.01

4.00

6.98

10.40

1.00

1.89

3.65

6.81

10.92

1.00

7.64

11.75

0.00 4.00 8.00 12.00 16.00

1 Core (1 CPU)

2 Cores (2 CPUs)

4 Cores (4 CPUs)

8 Cores (4 CPUs)

16 Cores (4 CPUs)

Speep Up Ratio

Car Grill (elements: 713,558, R9.1 Solid-Flow Enhanced)16-cavity Lens (elements: 1,066,448, R9.1 Solid-Flow Standard)Tray (elements: 1,422,416, R9.1 Solid-Flow Standard)

Benchmark Hardware - One BoxClusterNX (www.boxcluster.com)

- 4-node PC cluster

- one Intel Core i7 940 CPU on each node

- 12 GB DDR3 RAM on each node

- Gigabit network

Moldex3D Application Examples

20

BASF – New material development for automotive

bumper

Füllverhalten bei 50% Füllung

Füllverhalten bei 75% Füllung

Moldex3D:Danfoss

22

Improve design from one

material molding into two

color molding

Reduce cycle time of the

molding by 43%. Shorten

time to the market.

Reduce material cost by

11% via product geometry

optimization

Moldex3D User: Connector Case

23

The area

suggested to

be cored out

Warpage improved by 20% after

thickness cored out

Moldex3D User: Unilever

24

Temperature difference :45oC ->15oC

Cooling time reduced by 25% (from 5 to 3 sec)

Save 4 million sec

FEA Integration Analysis

What can Moldex3D-FEA Interface to Abaqus do?

• To consider the process-induced variation during the processes

– Mesh output

• Original / deformed mesh

• Mesh mapping

– Material properties output

• Anisotropic properties

• Fiber Orientation tensor

– Result output

• Thermal/Residual stress

• Temperature (Part/Mold)

• Pressure history (Part/Mold)

Moldex3D-FEA Interface-Anisotropic material

properties

• Based on the fiber orientation and proper micro-mechanics models,

Moldex3D-FEA Interface can output

– Stiffness matrix

– Thermal expansion coefficient

27

Moldex3D-FEA Interface Orientation tensor (for

Digimat)

• Orientation tensor can be output to composite modeling software

(Digimat) to perform more accurate micro mechanical properties

calculation

Moldex3D-FEA Interface-Material Reduction

• Material Reduction

– Moldex3-FEA Interface can reduce the anisotropy scale by homogenizing the

similar anisotropic properties so as to improve the computational efficiency

29

Total material number from

76,150 to 1,866

Total material number from

3,392 to 668

Technology Link of FEA Interface

Flow Pack Cool Warp

Moldex3D Simulation Ejection Application

Warpage

Structure

Analysis

Mold Deform

Core-Shift

Paddle-Shift

Modal Analysis

Drop Test

Impact

FEA-MSC

Marc

FEA-

ANSYS

FEA-

ABAQUS

FEA-MSC

Nastran

FEA

LS-DYNA

FEA-NX

Nastran

FEA-

RADIOSS

Structural

Moldex3D-FEA Interface-Interface to Abaqus

1. Click FEA

Interface Icon

2. Select Abaqus Solver

4. Select output

data

5. Export .inp file

3. Select output meshtype

Tensile Bar - Wend Line strength reduction

32

Weld Line Location

Fiber Orientation around the weld line

33

Weld Line Location

Major Modulus

34

Tensile Bar – Stress 30MPa Load Applied

35

Yield at 80 Mpa

Yield at 80 Mpa

79 MPa

47 MPa

30 MPa Load

30 MPa Load

0-80 MPa Range displayed

Thrust Pedal – Filling Animation

36

Thrust Pedal – Fiber Orientation

37

Thrust Pedal – Major Modulus

38

Thrust Pedal – Minor Modulus

39

Thrust Pedal – Model Setup

40

Apply a force on the Pedal

Fix the pin slot

Thrust Pedal – Displacement & Stress

200lbf (900 N) Force Applied

41

Displacement Stress

0-50 mm range 0-100 MPa range

isotropic

anisotropic

Integration between Moldex3D and

HyperStudy

Improving Part Quality for Injection

Molding

Introduction: Moldex3D and HyperStudy

• Moldex3D

• Moldex3D is the world leading CAE product for the plastics injection molding

industry

• HyperStudy

• HyperStudy is software to perform Design of Experiments (DOE), optimization,

and stochastic studies in a CAE environment

• HyperStudy is a member of the HyperWorks suite of software products

• Benefits of Moldex3D and HyperStudy Integration

• Users can employ HyperStudy to perform a series of Moldex3D analyses

systematically for improving part qualities

• Process conditions can be optimized automatically

• Moldex3D supports all study types for HyperStudy

Workflow between Moldex3D and HyperStudy

Do Study setup, DOE setup and

others setups Copy new design factor file and

call Moldex3D as the solver

through script function

Output response factor

Finish all runs and obtain optimal results

Create an initial run and perform a preliminary analysis

Integrating Moldex3D and HyperStudy:

DOE Study

Case Study

• An injection molded part from a speed meter shows potential warpage

problem from preliminary Moldex3D analyses.

• Dimension: 400 x 126 x 76 mm

• The target is to reduce warpage through optimizing process conditions

with HyperStudy and Moldex3D using DOE study.

Design of Experiments Conditions

• DOE Class: 9-run Fractional Factorial

• Initial Design Variables

• Filling Time: 2 sec

• Melt Temperature: 230˚C

• Mold Temperature: 70˚C

• Packing Pressure Profile %: 75%

• Design Variables

• Number of Variables: 4

• Filling Time: 1.7, 2, 2.3 sec (3 levels)

• Melt Temperature: 220, 240˚C (2 levels)

• Mold Temperature: 65, 75˚C (2 levels)

• Packing Pressure Profile %: 70, 75, 80 % (3 levels)

• Response Variable

• Standard deviation for total displacement (mm)

• In other words, the target is to have as uniform displacement as possible

DOE Study: Create a DOE Study

Select DOE Class

Detail setting of the Study setup is shown in appendix

DOE Study: Controlled Variables

• Define Design Variables:

Select Design variables

Setup Design variable

bounds and level values

DOE Study: DOE Run Table

Design of Experiments: Run Results

Run Summary

Main Effects

This chart indicates the melt

temperature and packing

pressure profile are the most

sensitive factors

DOE Optimal Results

• HyperStudy DOE study will lead to minimum standard deviation (SD) for Total

Displacement. It implies that the part deformation will become more uniform in

general.

Variables Initial Results DOE Results

Design Variables

Filling Time (sec) 2 2.3

Melt Temperature (˚C) 230 220

Mold Temperature (˚C) 70 65

Packing Pressure Profile (%) 75 80

Response Variable SD for Total Displacement (mm) 0.354 0.262

Initial Results DOE Results

Integrating Moldex3D and HyperStudy:

Optimization Study

Create an Optimization Study

• The same optimization target can be achieved by employing an

Optimization Study. For example: Adaptive Response Surface Method

(ARSM)

Select Optimization Engine

Other optimization engines available in

HyperStudy are

Optimization Study: Define Design Variables

• Define Design Variables:

• Filling Time (Range: 1.7, 2.3 sec)

• Melt Temperature (Range: 220, 240˚C)

• Mold Temperature (Range: 65, 75˚C)

• Packing Pressure Profile % (Range: 70, 80 %)

Settings for Objectives

• Objectives:

• Goal: Minimum Standard Deviation (SD) for Total Displacement

• Maximum Iterations: 20

• Absolute Convergence: 0.001

• Relative Convergence: 1.0%

Optimal Results

History Plot

History Table

Optimized design factors

Optimal Results

• Recommended optimal results will lead to the minimum standard deviation (SD)

for Total Displacement. It means that the part deformation will become more

uniform in general.

Variables Initial Run Optimal Run

Design Variables

Filling Time (sec) 2 2.3

Melt Temperature (˚C) 230 220

Mold Temperature (˚C) 70 65

Packing Pressure Profile( %) 75 80

Response Variable SD for Total Displacement (mm) 0.354 0.262

Initial Results Optimal Results

Summary

Comparison

Variables Initial Results DOE Results Optimal Results

Design Variables

Filling Time (sec) 2 2.3 2.3

Melt Temperature (˚C) 230 220 220

Mold Temperature (˚C) 70 65 65

Packing Pressure Profile( %) 75 80 80

Response Variable SD for Total Displacement (mm) 0.354 0.262 0.262

Warpage Improvement

{[0.354-(Other results)]/0.354}*100% 0% 26% 26%

Initial results DOE/Optimal results

Upper and lower limit values fixed to initial results

Conclusion

• The integration between Moldex3D and HyperStudy helps users to find out the

optimal process conditions for injection molding systemically.

• Both DOE Study and Optimal Study can reduce maximum displacement from 1.4

mm (initial design) to 1.0 mm (optimal design), which is a 27% improvement.

• According to the DOE Study results, melt temperature is the most important and

filling time is the least important factor for warpage of this case.

• Both DOE Study and Optimization Study can reduce warpage by 26%. However,

please note it’s likely to find different optimization studies lead to slightly

different optimized results.