ansys, inc. proprietary © 2004 ansys, inc

ANSYS, Inc. Proprietary© 2004 ANSYS, Inc.

Robust Design9.0

Robust Design9.0

Ray Browell, ANSYS Inc.Ray Browell, ANSYS Inc.


Why Robust Design?

“Lockheed Martin used to spend an average of 200 work-hours trying to get a part that covers the landing gear to fit. For years employees had brainstorming sessions, which resulted in seemingly logical solutions. None worked. The statistical discipline of Six Sigma discovered a part that deviated by one-thousandth of an inch. Now corrected, the company saves $14,000 a jet.”1

1: Firms aim for Six Sigma efficiency; [FIRST Edition] Del Jones. USA TODAY. McLean, Va.: Jul 21, 1998. pg. 01.B1: Firms aim for Six Sigma efficiency; [FIRST Edition] Del Jones. USA TODAY. McLean, Va.: Jul 21, 1998. pg. 01.B


Why Robust Design?

“It will keep the company (Allied Signal) from having to build an $85 million plant to fill increasing demand for caprolactam used to make nylon, a total savings of $30 - $40 million a year.”1

Raytheon figures it spends 25% of each sales dollar fixing problems when it operates at four sigma, a lower level of efficiency. But if it raises its quality and efficiency to Six Sigma, it would reduce spending on fixes to 1%.”1

1: Firms aim for Six Sigma efficiency; [FIRST Edition] Del Jones. USA TODAY. McLean, Va.: Jul 21, 1998. pg. 01.B1: Firms aim for Six Sigma efficiency; [FIRST Edition] Del Jones. USA TODAY. McLean, Va.: Jul 21, 1998. pg. 01.B


Why Robust Design?

“The reason to do DFSS is ultimately financial. It generates shareholder value based on delivering customer value in the marketplace. Products developed under the discipline and rigor of a DFSS-enabled product development process will generate measurable value against quantitative business goals and customer requirements. DFSS helps fulfill the voice of the business by fulfilling the voice of the customer.”2

2: Design for Six Sigma in Technology and Product Development, C.M. Creveling, J. L. Slutsky, and D. Antis, Jr.2: Design for Six Sigma in Technology and Product Development, C.M. Creveling, J. L. Slutsky, and D. Antis, Jr.


–Background of Robust Design• What is Robust Design, DFSS, …?• Design for Quality• Robust Design in Engineering Analysis• Illustration Example• Sources of Uncertainty• Effects of Uncertainty• Compare Deterministic and Probabilistic Approach• Enabling Technologies

–Demonstration• Overview of Application Example• Demo

–Questions

Robust Design Overview


Background of Robust Design What is Robust Design, DFSS, etc.?

• Uncertainty AnalysisQuantify the effect of uncertainties on the performance of a product (mean value, standard deviation, etc.)

• Reliability AnalysisQuantify the reliability (failure probability, defects per million)

• Robust Design or Design For Six Sigma (DFSS)Optimize the design such that it is insensitive to unavoidable uncertainties (e.g. material,loads,…)

• Reliability-based OptimizationOptimize the design such that reliability is maximized or failure probability (defects per million) is minimized

Robust Design is often synonymous to “Design for Six Sigma” or “Reliability-based Optimization”

Robust Design is often synonymous to “Design for Six Sigma” or “Reliability-based Optimization”


Background of Robust Design Design for Quality

Six Sigma Quality = Only 3.4 out of 1’000’000 parts fail

Six Sigma Quality is inherently a probabilistic statement

Gaussian Distribution

-6 -4 -2 0 2 4 6

Sigma-Value

Area =

Failure Probability

Product is ...

Bad Good

LSL USL

Product is ...

Good Bad LSL = Lower

Specification Limit

USL = Upper Specification Limit

P.S.: Gaussian distribution is not realistic, but does convey the idea correctly


Background of Robust Design Design for QualitySix Sigma = Optimize manufacturing processes such

that they automatically produce parts conforming with six sigma qualityquality

Design For Six Sigma = Optimize the design such that the parts conform with six sigma qualityquality, i.e. qualityquality and reliability are explicit optimization goals

Design for Six Sigma:• Achieve “Designed-In”

quality as opposed to letting customers find out about quality problems

• Make informed decision that are critical to quality early in the development process0.1

1

10

100

1000

Research Design DevelopmentPrototypeTests

Production

Product Development Phases

Re

l. C

os

t o

f D

es

ign

Ch

an

ge

0%

20%

40%

60%

80%

100%

Design For Six Sigma Six Sigma

De

gre

e o

f F

red

om

to

aff

ec

t th

e P

rod

uc

t L

ife

tim

e C

os

ts


FROM:Reactive Quality

Management

• Extensive Design Rework• Assess Performance by

“build-test-build-test-…”• Fix performance/quality

problems after manufacturing

• Quality is “Tested-In”

TO:Predictive Quality

Management

• Controlled Design Parameters

• Estimate likelihood/rate of performance problems in design & development

• Address quality problems in design & development

• Designed for robust performance and quality

• Quality is “Designed-In”

Background of Robust Design Design for Quality

Robust Design is a Paradigm Shift …


Purpose of Robust Design

InputInputInputInput ANSYSANSYSANSYSANSYS OutputOutputOutputOutput

Material PropertiesGeometryBoundary Conditions

DeformationStresses / StrainsFatigue, Creep,...

It’s a reality that input parameters are subjected to scatter => automatically the

output parameters are uncertain as well!!

Background of Robust Design Robust Design in Engineering Analysis


Questions answered with Robust Design:

• How large is the scatter of the output parameters?• What is the probability that output parameters do not fulfill design

criteria (failure probability – defects per million)?• How much does the scatter of the input parameters contribute to the

scatter of the output (sensitivities – critical-to-quality)?

Background of Robust Design Robust Design in Engineering Analysis

ANSYS ANSYS DesignXplorerDesignXplorer

ANSYS ANSYS DesignXplorerDesignXplorer

Purpose of Robust Design


Property SD/Mean %

Metallic materiales, yield 15

Carbon fiber composites, rupture 17

Metallic shells, buckling strength 14

Junction by screws, rivet, welding 8

Bond insert, axial load 12

Honeycomb, tension 16

Honeycomb, shear, compression 10

Honeycomb, face wrinkling 8

Launch vehicle , thrust 5

Transient loads 50

Thermal loads 7.5

Deployment shock 10

Acoustic loads 40

Vibration loads 20Source: Klein, Schueller et.al. Probabilistic Approach to Structural Factors of Safety in Aerospace.

Proc. CNES Spacecraft Structures and Mechanical Testing Conf., Paris 1994

Background of Robust Design Sources of Uncertainty


CFD

FEMCAD

FEMGeometry

Materials,Bound.-Cond.,

Loads, ...

Materials,Bound.-Cond., ...

Materials,Bound.-Cond.,

Loads, ...

LCF

Materials

± 0.1-10%

±5-50%

±5-100%

±30-60%

±??%

±5-100%

Thermal Analysis

Structural Analysis

Background of Robust Design Effects of Uncertainty


Influence of Young’s Modulus and Thermal Expansion Coefficient on thermal stresses:

thermal = E · ·T

Deterministic Approach:

Mean = EMean · Mean · T Mean = typically used results

Probabilistic Approach:

Probability that ( thermal >= 105% Mean) ( thermal >= 110% Mean)

‘E’ scatters ±5% 16% (~1 out of 6) 2.3% (~1 out of 40)

‘E’ and ‘‘ scatter ±5% 25% (~1 out of 4) 8% (~1 out of 12)

‘E’, ‘‘ & ‘T’ scatter ±5% 28% (~1 out of 4) 13% (~1 out of 8)

Background of Robust Design Effects of Uncertainty


Turbine What-If Analysis Series

Background of Robust Design Compare Deterministic/Probabilistic


Background of Robust Design Enabling Technology: Parameterization

• Robust Design for all parameters including:

– APDL Parameters

/syp,parabatch.exe,'testpb.rsx','testpb.cdb','location',%value%,'testpb_mod.cdb'

/inp,testpb_mod,cdb ! Input the modified geometry

Paramesh db Initial mesh

Parameter name

Parameter value

Output mesh

Import Output mesh

CAD Parameters (Workbench)CAD Parameters (Workbench) APDL ParametersAPDL Parameters

ParaMesh ParametersParaMesh Parameters


Background of Robust Design Enabling Technology: DesignXplorer

DesignXplorer manages the parameters and the uncertainties

DesignXplorer manages the parameters and the uncertainties


CAD Geometry FEM MeshFEM Boundary

Conditions

Robust Design Demonstration Overview of Application Example


Results for Maximum Principal StressPressure Side Suction Side

Peak Value s

Tang. Leaning

AxialLeaning

Dove TailWidth

MaterialDensity

(Gaussian)

Fillet Radius(Lognormal)

Mass

Design Variables and Uncertainties

Imbalance: (p – s)2 Avg.Stress: 0.5(p + s)

Peak Value p

Robust Design Demonstration Overview of Application Example


Robust Design DemonstrationTurbine Blade Workshop

Robust Design Demonstration Demonstration


DesignXplorer Family9.0

DesignXplorer Family9.0

Ray Browell, ANSYS Inc.Ray Browell, ANSYS Inc.


• DesignXplorer & DesignXplorer VT– Robust Design

• GUI Structure• Parameterize DFSS Results• Optimize DFSS results

– New Trade-Off Study– Genetic Algorithm for Sample Generation

• Variational Technology (DesignXplorer VT)– Support of Discrete Variables in Workbench– RSX File Viewing– Additional Contact Support– Frequency dependent material properties– Support inertial load parameters– 2D Analysis

DX Family 9.0 New Features


DX Family 9.0 New Features Robust Design - GUI Structure

DFSS Charts and Table PagesMeasures of robustness

CDF Plot Y-Axis can be scaled as Gaussian, Log-Normal, Weibull, Exponential

CDF Plot Y-Axis can be scaled as Gaussian, Log-Normal, Weibull, Exponential

Statistics Available

Customize Tables (add, delete)

Sigma-Level in Tables


New“Robust Design”

View

New DFSS Parameters showing upin Parameter

View

DX Family 9.0 New Features Parameterize DFSS Results


DX Family 9.0 New Features Optimize DFSS results

1)

2)

2) Design Variables: Useable for Robust Design Optimization

1) Random Variables: Uncontrollable – used to obtain DFSS results


Same optimization functionalityas for GDS

DX Family 9.0 New Features Optimize DFSS results


DX Family 9.0 New Features Trade-Off Studies

Mouse-OverResults

Conflicting goals lie along the Pareto Front, Tradeoffs

Studies occur here

Both 2D and 3D Tradeoff Plots are available

Both 2D and 3D Tradeoff Plots are available


Mouse-Over

Results

Pareto Frontfor Conflicting

Goals

Infeasible Points in Pareto Front

InfeasibleInfeasibleFeasibleFeasible

DX Family 9.0 New Features Trade-Off Studies


Choice of Basic (Screening), which is pseudo-random sampling method typically done first, or Advanced (Genetic) Algorithm which is typically done second

Choice of Basic (Screening), which is pseudo-random sampling method typically done first, or Advanced (Genetic) Algorithm which is typically done second

DX Family 9.0 New Features Genetic Algorithm Sample Generation


Advanced sample optionsAdvanced sample options

DX Family 9.0 New Features Genetic Algorithm Sample Generation

Screening SamplesScreening Samples Advanced SamplesAdvanced Samples


DesignXplorer VT 9.0 Support of Discrete Variables in Workbench

• Variational Technology is much faster than DOE for discrete parameters

• Supports:– Spot Welds– Solid Bodies– Sheet Bodies– Line Bodies– Parts

Time for a 30 minute base solve

0.001

0.1

10

1000

100000

1E+07

1E+09

1E+11

1E+13

1E+15

0 5 10 15 20 25 30 35 40 45 50

Num ber of Boolean Param eters

Time (

Days)

DOE

DXVT

1 Day

1 Year

1 Decade

1 Century

1 Millennium


• Efficient Postprocessing– Multi-objective Boolean

optimizer based on Bayesian sampling faster optimization of discrete parameters

– Boolean scatter chart representing the solution points of all the parameter combinations of the selected parameters.




6 Supports

None Suppressed

6 Supports

None Suppressed

6 Supports

4 Suppressed

6 Supports

4 Suppressed


• Allows user to view Variational Technology results from a variety of sources including– DesignXplorer VT

(of course)– ANSYS using VT

DesignXplorer VT 9.0 RSX File Viewing

Hoover model solved with VT within the ANSYS EnvironmentHoover model solved with VT within the ANSYS Environment


DesignXplorer VT 9.0 Support for Face-to-Edge Contact


DesignXplorer VT 9.0 Support for Edge-to-Edge Contact


• For harmonic analyses, VT supports frequency dependant modulus and damping

DesignXplorer VT 9.0 Support of Frequency Dependent Properties

Modulus of Elasticity vs. Frequency

1.0E+07

1.2E+07

1.4E+07

1.6E+07

1.8E+07

2.0E+07

2.2E+07

2.4E+07

2.6E+07

2.8E+07

3.0E+07

0 100 200 300 400 500 600 700 800

Frequency (Hz)

Mo

du

lus

of

Ela

stic

ity

Imaginary Modulus Damping Ratio vs. Frequency

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

0 100 200 300 400 500 600 700 800

Frequency (Hz)

Ima

ng

ina

ry M

od

ulu

s D

am

pin

g R

ati

o

Frequency Response

0.0001

0.001

0.01

0.1

1

10

0 100 200 300 400 500 600 700 800

Frequency (Hz)

Y D

isp

lac

em

en

tVariable E

E for 0 Hz

E for 800 Hz


DesignXplorer VT 9.0 Inertial Load Paramenters & 2D Analysis

• Support Inertial Load Parameters– Acceleration (Magnitude and Components)– Rotational Velocity (Magnitude and Components)– Rotational Acceleration (Magnitude and

Components)

• Allows Variational Technology analysis of 2D Simulation studies to include:– Axisymmetric– Plane Strain– Plane Stress


DesignXplorer and DesignXplorer VT

• Thank you!• Questions?

– Additional Questions:

Ray Browell(724) [email protected]

– Additional Information:

http://www.ansys.com/

ansys, inc. proprietary © 2004 ansys, inc

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