1 Systems Realization Laboratory Modeling Simulation-Based Design Processes via Reusable Decision Centric Templates 3-P Information Model for Simulation-Based

1

Systems Realization Laboratory

Modeling Simulation-Based Design Processes via Reusable Decision Centric Templates

3-P Information Model for Simulation-Based Multiscale Design Processes

Marco Gero FernándezJitesh H. Panchal

Janet K. AllenFarrokh Mistree

Christiaan J.J. Paredis

-----------------------------------------------------PDE 2005 Workshop

Atlanta22 April, 2005

Systems Realization LaboratoryGeorgia Institute of Technology, Atlanta

2


Presentation Outline

Modular Template Based Approach for

Process Modeling

3-P Information Model for Integrating Process, Product and Problem

Proposed Design Process Modeling Strategy

Frame of Reference

Closing Remarks

3


Product Lifecycle Management (PLM)

“…strategic approach to creating and managing a company's product-related intellectual capital from initial conception to retirement”

- IBM

PLM

Marketing/SalesCollaboration

Customer Requirements

DesignConceptDevelopment

Production& Testing

Maintenance& Support

PortfolioPlanning

Design Collaboration

Manufacturing Collaboration

Services Collaboration

Customer Feedback

Partners Other Enterprise Locations

Suppliers

Market Planning

Design Definition

Design Change Management

Component Management

PLM Collaborative Foundation

Cu

sto

mer

s

Cu

sto

mer

s

Sales & Distribution

B2B integration

Courtesy Stas Tarchalski, IBM Product Lifecycle Management

4


What is PLM?

PLM InfrastructurePLM Infrastructure

CAD

RequirementsManagement

Process Planning

Analysis

MarketAnalysis

GridComputing

Distributed Design Framework

PDM System

CRM

Knowledge Based Engineering

…

Environmental Impact

Assessment

PLM

Marketing/SalesCollaboration

Customer Requirements

DesignConceptDevelopment

Production& Testing

Maintenance& Support

PortfolioPlanning

Design Collaboration

Manufacturing Collaboration

Services Collaboration

Customer Feedback

Partners Other Enterprise Locations

Suppliers

Market Planning

Design Definition

Design Change Management

Component Management

PLM Collaborative Foundation

Cu

sto

mer

s

Cu

sto

mer

s

Sales & Distribution

B2B integration

Decisions

VisionVision – Management of product related intellectual capital

PDEPLM TodayPLM Today

PLM PLM VisionVision

5

Systems Realization Laboratory PLM InfrastructurePLM Infrastructure

CAD


Process Planning

Analysis

MarketAnalysis

GridComputing


PDM System

CRM


…

Environmental Impact

Assessment

PDE

Product Related Intellectual Capital

Process Information Product Information

Entities,Relationships

Activities,Sequence

6


Elements of Product Data Exchange Discussed in this Workshop

• Standards for Product Information Representation, Product Data Exchange

– CAD Data Translation– STEP, EXPRESS– SysML– Common Data Schema

• Design-Analysis Integration– COBs– Abstract Model (Simmetrix)

• Knowledge Archival– Macro-parametric approach– Knowledge modeling standards

• Engineering Frameworks– Federated Product Models– Domain Integration

What’s Missing?‘Why’

‘What’ and ‘How’ Data is Exchanged

Product Related Intellectual Capital =

Product Knowledge+

???

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Product Data Exchange Throughout the Design Process

Decision 1Information

Stage A Decision 2Information

Stage B

Information Stage C

T2 T3InformationState 0 Information

State 1Information

State 2

T1 InformationState 3

T2 T3Information

State 4Information

State 5

T1 InformationState 6

DesigningRequirements Product SpecificationsProduct Related Intellectual Capital

= Product Knowledge

+Tools

(for creation, management and dissemination of knowledge)

+???

8

Systems Realization Laboratory PLM InfrastructurePLM Infrastructure

CAD


Process Planning

Analysis

MarketAnalysis

GridComputing


PDM System

CRM


…

Environmental Impact Assessment

PLM InfrastructurePLM Infrastructure

CADCAD

RequirementsManagementRequirementsManagement

Process PlanningProcess Planning

AnalysisAnalysis

MarketAnalysisMarket

AnalysisGrid

ComputingGrid

ComputingDistributed Design

FrameworkDistributed Design

Framework

PDM System

PDM System

CRMCRM



……



Process Information Product Information

Entities,Relationships

Activities,Sequence

What’s Missing Today?

Product Related Intellectual Capital =

Product Knowledge+

Tools +

Process KnowledgeProcess Knowledge(for creation, management and dissemination of knowledge)

9


Analysis, Design &

Decision Support

Tools

System

Ecosystem

Product

Component

Assembly

Material

Integ

ratio

n of Knowled

ge, Lea

rning &

Tools

Seamles

sly A

long Multi

ple Dim

ensio

ns & Sca

les

Analysis, Design &

Decision Support

Tools

System

Ecosystem

Product

Component

Assembly

Material

System

Ecosystem

Product

Component

Assembly

Material

System

Ecosystem

Product

Component

Assembly

Material

Integ

ratio

n of Knowled

ge, Lea

rning &

Tools

Seamles

sly A

long Multi

ple Dim

ensio

ns & Sca

les

Example Problem Domain: Multiscale Design

Courtesy: Prof. Bert Bras

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Design of Multiscale Materials

Quantum Mechanics

Molecular Dynamics

MesoscaleMonte Carlo

ContinuumPDE

Reduced Order Models

Time Scale

Length Scale

Angstroms Meters

Electrons AtomsGrains/

DomainsFilms &

ReactorsSystems

Li,Hanagud

ZhouMcDowell

Hanagud,Zhou

Batra,McDowell

Quantum Mechanics

Molecular Dynamics


ContinuumPDE


Time Scale

Length Scale

Angstroms Meters


DomainsFilms &

ReactorsSystems

Quantum Mechanics

Molecular Dynamics


ContinuumPDE


Time Scale

Length Scale

Angstroms Meters


DomainsFilms &

ReactorsSystems

Li,Hanagud

ZhouMcDowell

Hanagud,Zhou

Batra,McDowell

11


Product Knowledge Captured in Models for Simulation of Material Behavior

Shock simulationsof discrete reactive powder

metal mixtures

First principles simulationof lattices; Hugoniot

relations

High strain rate experiments

Hugoniot

Effective continuumModels for RPMMs

Simple continuum modelsThermo-mechanical, with T-CAsymmetry, Mohr-Coulomb

Continuum nonequilibriummixture models

Projectile level simulations

Response surfacesfor reaction initiation

and constitutivebehavior

Projectile/RPMM Couplings

Electronic structuremodeling of

Transition states

MD potentials for pressure- and

shear dependent initiation of reaction

Continuum models forReaction initiation:

Mohr-Coulomb with criticaltemperature

Reaction Initiation


metal mixtures

10-10 m

10-8 m

10-6 m

10-4 m

10-2 m

100 m

12


Simulation Based Design Processes for Materials

Select Material Constituents

Determine Relative Volume Fraction of Each Constituent

Determine Material Morphology (Spatial Particle Distribution)

Constituent Material Properties(Equation of State)

Mixture Properties(Structural, Energetic)

Determine Projectile Dimensions Projectile

Properties

Determine Impact Velocity, Angle of Attack

Behavior on Impact


metal mixtures

First principles simulationof lattices; Hugoniot

relations

High strain rateexperiments

Hugoniot

Effective continuumModels for RPMMs

Simple continuum modelsThermo-mechanical, with T-CAsymmetry, Mohr-Coulomb

Continuum nonequilibriummixture models

Projectile level simulations

Response surfacesfor reaction initiation

and constitutivebehavior

Projectile/RPMM Couplings

Electronic structuremodeling of

Transition states

MD potentials for pressure- and

shear dependent initiation of reaction

Continuum models forReaction initiation:

Mohr-Coulomb with criticaltemperature

Reaction Initiation


metal mixtures

10-10 m

10-8 m

10-6 m

10-4 m

10-2 m

100 m

10-10 m

10-8 m

10-6 m

10-4 m

10-2 m

100 m

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Capturing Information About the Product is Necessary

NOT SUFFICIENT

What’s missing?

Decisions and Process Knowledge

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Currently Functionality for Process Capture

Levels of Abstraction in Processes

1. Computing Resources Management Level

2. Analysis Execution Level

3. Design Methodology Level

4. Inter-Organizational Design Level

5-… Levels

N. BP*Level

*BP: Business Processes

Applications

HyperWorks®

Panchal, J. H., Vrinat, M., Brown, D.H., “Design and Simulation Frameworks: Critical Issues”, Report for Collaborative Product Development Associates , October 2004.

Abstraction and Reusability of Processes is Limited at Computational Level

15


Currently Available Design Process Models

View of Design Process Modeling

Effort

Modeling, analysis objective

Basic units of a process

Activity based IDEF Organizational decisions Activities, information

Activity/Task based DSM Organizational decisions, risk, complexity, probability of rework, iterations, etc.

Tasks

Functional Evolution Shimomura Capture design process, designers’ intentions, trace design processes

Functional realization, functional operation, functional evaluation

Evolution of product states

Ullman Process representation Abstraction, refinement, decomposition, patching combination, combination

Knowledge Manipulation (ASE)

Maimon Development of a mathematical theory

Artifact space, specs, Analysis, synthesis

Knowledge manipulation Maher Development of knowledge based systems

Decomposition, case based reasoning, transformation

Task Based Gorti Development of engineering knowledge base

Goal, plan, specification, decision and context

Decision Based Design DSP Technique

Modeling, analyzing, debugging, finding inconsistencies in a process

Phases, events, decisions, tasks, information

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Drawbacks of Current Process Models

View of Design Process Modeling

Effort



Activity based IDEF Organizational decisions Activities, information

Activity/Task based DSM Organizational decisions, risk, complexity, probability of rework, iterations, etc.

Tasks

Functional Evolution Shimomura Capture design process, designers’ intentions, trace design processes



Ullman Process representation Abstraction, refinement, decomposition, patching combination, combination


Maimon Development of a mathematical theory


Knowledge manipulation Maher Development of knowledge based systems


Task Based Gorti Development of engineering knowledge base


Decision Based Design DSP Technique



• Other building blocks of design processes (transformations) are not defined and formalized

• Does not provide information about the manner in which the product evolves

• Reuse of design processes is not supported beyond symbolic level

• Do not provide computational models of design processes

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Decision Based Design

Task Based

Knowledge manipulation



Functional Evolution

Activity/Task based

Activity based

View of Design



DSP Technique


Development of engineering knowledge base

Gorti


Development of knowledge based systems

Maher


Development of a mathematical theory

Maimon

Abstraction, refinement, decomposition, patching combination, combination

Process representationUllman


Capture design process, designers’ intentions, trace design processes

Shimomura

TasksOrganizational decisions, risk, complexity, probability of rework, iterations, etc.

DSM

Activities, informationOrganizational decisionsIDEF

Process Modeling

Effort



Decision Based Design

Task Based

Knowledge manipulation



Functional Evolution

Activity/Task based

Activity based

View of Design



DSP Technique


Development of engineering knowledge base

Gorti


Development of knowledge based systems

Maher


Development of a mathematical theory

Maimon

Abstraction, refinement, decomposition, patching combination, combination

Process representationUllman


Capture design process, designers’ intentions, trace design processes

Shimomura

TasksOrganizational decisions, risk, complexity, probability of rework, iterations, etc.

DSM

Activities, informationOrganizational decisionsIDEF

Process Modeling

Effort



Requirements for Reusable Design Process Modeling

• Reusability of processes across products and problem formulations

• Separation of problem (context) related information from product/process specific information

• Composability of sub processes through modularity• Applicability at computational level• Insight into product evolution• Support for human decision making• Formalization of information transformations in design

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Proposed Strategy


Process Modeling



Frame of Reference

Closing Remarks

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Hierarchical Modeling of Design Process Templates

Inc

rea

sin

g L

ev

el

of

Ab

str

ac

tio

n

Design Process BuildingBlocks (DPBBs)

RCEM

PPCEMComponent

Design

MultifunctionalDesign

Multi-scale Design

Design Processes

Gear Box Design

LCA Design

MEMS Design

Mapping DecompositionComposition

AggregationConcretization

Abstraction

Basic Design Transformations (BDTs)

Hierarchical Modeling

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Reusability of Design Processes Through ModularityModularity

Computational models that can serve as process building blocks Storable and Reusable Analyzable Executable Standardized

Hierarchical, object-oriented Modular Configurable Well-defined inputs and outputs Generic, domain independent Decision-centric

Process Building Blocks Processes

Adapted from: Scott Cowan’s presentation

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Our Design Process Model

DesigningInformation State

AInformation State

B

T2 T3InformationState 0 Information

State 1Information

State 2Information

State 3

InformationState 4

T1 T4

Design Process: Network of Transformations of Information

Ti = Transformation of information from one state to another[Information State 1] = [T1] [Information State 0][Information State 2] = [T2] [Information State 1][Information State 3] = [T3] [Information State 2][Information State 4] = [T4] [Information State 3]

[Information State 4] = [T4] [T3] [T2] [T1] [Information State 0]

Design Equation

[Information State 2] = [Transformation] [Information State 1]

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InformationState 0 Information

State 1Information

State 2Information

State 3

InformationState 4

T2 T3 T4T1

Design Process View for Hierarchical Processes

Scope

Pro

ce

ss

De

tail

Single designer

MultipleOrganizations

SingleOrganization

DesignTeam

MultipleTeams

Inter-organizational

interactions

Interactions between teams

Designvariables

Managerial level design process

Designer level design process

Hie

rarc

hy

of

Pro

ce

ss

es

Time

Hypothesis: There is a standard set of

transformations common to these levels


State 6Information

State 7Information

State 8

InformationState 9

T6 T3 T8T5


State 11Information

State 12Information

State 13

InformationState 14

T10 T11 T12T9

Stage 1

Stage 2

Stage 3

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Modeling Design Processes via Information Transformations

Synthesis

Mapping

Interfaces

Decomposition

Decisions

Composition

Abstraction

Selection

Generic cDSPCompromise

TransformationInformation Updated Information

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Goals

Preferences

Variables

Parameters

Constraints

Objective

Analysis

Driver

ResponsecDSP

Desig

n Req

uirem

ents

Desig

n Spe

cific

atio

ns

Desig

n Req

uirem

ents

Desig

n Spe

cific

atio

ns

The cDSP as an Executable, Modular, Re-usable Information Transformation

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Goals

Preferences

Variables

Parameters

Constraints

Response

Objective

Analysis

Driver

Printed Wiring Board Analogy for

Modular Design Process ElementsModular Design Process Elements

PreferencesPreferencesPreferencesPreferencesPreferences

GoalsGoalsGoalsGoalsGoalsParametersParametersParametersParametersParameters

VariablesVariablesVariablesVariablesVariables

ConstraintsConstraintsConstraintsConstraintsConstraintsDriverDriverDriverDriverDriver

ObjectiveObjectiveObjectiveObjectiveObjective

ResponseResponseResponseResponseResponse

AnalysisAnalysisAnalysisAnalysisAnalysis

PreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferencesPreferences

GoalsGoalsGoalsGoalsGoalsGoalsGoalsGoalsGoalsGoalsGoalsGoalsGoalsGoalsGoals

ParametersParametersParametersParametersParametersParametersParametersParametersParametersParametersParametersParametersParametersParametersParameters

VariablesVariablesVariablesVariablesVariablesVariablesVariablesVariablesVariablesVariablesVariablesVariablesVariablesVariablesVariables

ConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraintsConstraints

DriverDriverDriverDriverDriverDriverDriverDriverDriverDriverDriverDriverDriverDriverDriver

ObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjectiveObjective

ResponseResponseResponseResponseResponseResponseResponseResponseResponseResponseResponseResponseResponseResponseResponse

AnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysisAnalysis

(J. Panchal, M. Fernández, C. Paredis and F. Mistree, "Reusable Design Processes via Modular, Executable, Decision-Centric Templates" AIAA-MAO, 2004)

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Goals

Preferences

Variables

Parameters

Constraints

Response

Objective

Analysis

Driver

Goals

Preferences

Variables

Parameters

Constraints

Response

Objective

Analysis

Driver

Pressure Vessel Spring

Example of Reusable Decision Template

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Generic Decision Template

Goals

Preferences

Variables

Parameters

Constraints

Response

Objective

Analysis

Driver

Instantiated Decision Template

Goals

Preferences

Variables

Parameters

Constraints

Response

Objective

Analysis

Driver

“Modular” Re-Usability of Decision Template

Modularity of Processes Represented as Templates

28


Proposed Strategy


Process Modeling



Frame of Reference

Closing Remarks

29


GoalsGoals

PreferencesPreferences

VariablesVariables

ParametersParameters

ConstraintsConstraints

ResponseResponse

ObjectiveObjective

AnalysisAnalysis

DriverDriver

Stiffness, Volume

Outputs

Wire Diameter, Coil Diameter, Shear Modulus, Number of Coils

Volume, WeightRadius, Length, Thickness, Density, Strength, Pressure

Outputs

Design Variable Values – Radius, Length, Thickness

Objective Function Value - Z



Optimization Algorithm – Exhaustive Search, SQP, etc.


InputsInputs

Maximize Stiffness

Minimize Volume

Maximize Volume

Minimize

Weight

Stiffness Weighting Factor = 0.5

Volume Weighting Factor = 0.5


Weight Weighting Factor = 0.5

Stiffness Target = lbf/in

Volume Target = in^3

Volume Target = 500000 m^3

Weight Target = 300 kg

Applied Force, Coil Diameter, Shear Modulus

Density, Strength, Pressure

Number of Coils, Wire DiameterRadius, Length, Thickness

Minimum Deflection:

Maximum Solid Height:

Stress:

Thickness:

Radius:

Length:

SpringPressure VesselcDSP “Chips”

Stiffness, Volume

Outputs

Wire Diameter, Coil Diameter, Shear Modulus, Number of Coils

Volume, WeightRadius, Length, Thickness, Density, Strength, Pressure

Outputs







InputsInputs

Maximize Stiffness

Minimize Volume

Maximize Volume

Minimize

Weight

Stiffness Weighting Factor = 0.5



Weight Weighting Factor = 0.5

Stiffness Target = lbf/in

Volume Target = in^3

Volume Target = 500000 m^3

Weight Target = 300 kg

Applied Force, Coil Diameter, Shear Modulus

Density, Strength, Pressure

Number of Coils, Wire DiameterRadius, Length, Thickness

Minimum Deflection:

Maximum Solid Height:

Stress:

Thickness:

Radius:

Length:

SpringPressure VesselcDSP “Chips”

3 2 3 24 4( , , )

3 3W R T L R T R T L R R L

3 24( , )

3V R L R R L

4

38

d Gk

D N

2 212

4V Dd N

3

4

81.1

FD N

d G

0.5H N d

0t

PRS

T

5 0T R 40 0R T

2 2 150 0L R T

Implementation and Proof of Concept

30


Current Implementation of Processes in Simulation Integration Applications (e.g., ModelCenter/FIPER)

Screenshot from ModelCenter

31


Our Reusable Process Implementation(separation of declarative and procedural information)

32


XML Template(Problem Definition)

XML Template(Analysis)

Product Information Level(Declarative Product Level)

Model Center/FIPERProblem Definition

(Java Beans)Analysis

(Java Beans)

Process Level(Declarative Process Level)

Pressure Vessel Analysis(Visual basic)

W = f (L, R, T, density) V = g (L, R, T)

Spring Analysis(Visual Basic)

V = f (d, D, N, …)K = g (d, D, N, …)

Pressure Vessel ProblemDesign Variables: R, L, T

Spring ProblemDesign Variables: d, N

Execution Level(Procedural Level)

Implementation Details of Template Based Design Process Modeling

33


XML Templates in Current Implementation of Template Based Design Process Model

34


Proof-of-Concept Implementation in ModelCenter

Declarative Decision Representation Executable Procedures

Util

izat

ion

of In

form

atio

n in

Gen

eric

Pro

cess

XML Definition of Decision

XML Definition of Variables

XML Definition of Preferences

XML Definition of Constraints

XML Definition of Analysis

XML Definition of Driver

XML Definition of Response

35


Proposed 3-P Information Model

Pro

blem

Product

Abstract Information Models

Pro

blem

Pro

blem

Pro

blem

Pro

blem

Instantiations of Problem

Process

Process

Process

Process

Instantiations of Process

ProductProduct

ProductProduct

Instantiations of Product

Pro

blem

Process

36


Proposed 3-P Information Model

Abstract Information Models

Pro

blem

Pro

blem

Pro

blem

Pro

blem

Instantiations of Problem

Process

Process

Process

Instantiations of Process

ProductProduct

ProductProduct

Instantiations of Product

Process

Pro

blem

ProductP

robl

emP

rocess

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Components of 3P - Problem Information Model (Schema)

DesignSpace

-vDesignVariables : Vector

DesignVariable

-bVariableIsReal : boolean-dCurrentValue : double-dLow erBound : double-dUpperBound : double-sVarName : String

Constraint

-Parser : Parser-sLHS : String-sName : String-RelationType : String-sRHS : String-vVariables : Vector-vVariableValues : Vector

Goal

-dCurrentValue : double-dDeviation_OverAchievement : double-dDeviation_UnderAchievement : double-dTargetValue : double-goalName : String-iMonotonicity : int

Preference

InEqualityConstraint EqualityConstraint

DecisionProblem

ResponseSpace

-vResponseVariables : Vector

DiscreteDesignVariable

-SetOfValues[] : Real

RealDesignVariable

-Low erBound : Real-UpperBound : Real

ProblemConstraints

-vConstraints : Vector

ArchimedeanPreference

-vGoals : Vector-w eight_OverAchievement : double-w eight_UnderAchievement : double

PreemptivePreference

UtilityBasedPreference

ResponseVariable

-dCurrentValue : double-sVarName : String

DiscreteResponseVariable

-SetOfValues[] : Real

RealResponseVariable

-Value : Real

Attribute

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Components of 3P - Product Information Model (Schema)

Product

Entity

-vAttributes : Vector-vEntities : Vector-vRelationships : Vector

Relationship

-Parser : Parser-sMathematicalExpression : String-sValueToBeEvaluated : String-vVariables : Vector-vVariableValues : Vector

ExternalRelationships

FormAttribute BehaviorAttribute

EntityInherentRelationshipsAttribute

Behavior Form

Behaviora lM odel

39


Components of 3P - Process Information Model (Schema)

Process

InterfaceBasicProcessElement

-Inputs : Class-Outputs : Class

CompositeProcessElement

ProcessGraph

Inputs Outputs

Attribute

MappingMechanism

Input-OutputMappingExecutionSequence

40


Combinations of Problem-Product-Process

Problem Product Process

Pressure Vessel

Datacenter

Multiscale Materials

cDSP – Archimedean Formulation

cDSP – Preemptive/Utility Based Formulation

One Decision vs. MultipleDecisions for Sub-Systems

Set Based Design Process

RCEM-Using DOE and Surrogate Models

Direct Code Execution

cDSP – Archimedean Formulation, DCIs, Type-I,

II, III, IV Robust Design

Traditional Optimization

Using Patterns P1 orP2 or P3 for interaction

between models

41


Characteristics and Capabilities of 3-P Information Model

• Separate information related to Problems, Products and Processes

• Different combinations of Problems, Products, and Processes declarations can be combined together to generate a computationally executable process

• Allows reusability of process knowledge across problems and products

• Allows composability of sub-processes

3-P Information Model

42


Proposed Strategy


Process Modeling



Frame of Reference

Closing Remarks

43


Vision: Hierarchical Design Chains

2nd tierdesigners

1st tierdesigners

3rd tierdesigners

Design Info

Design Info

Design Chain

Aircraft Engine

Aircraft

ExamplesLCA

Processes

T

T

T

T

44


Across the Other Value Chains…

Marketing Chain Sales Chain

Information Flow

Collaboration

Adapted from SCOR model

45


Acknowledgements

We gratefully acknowledge support from National Science Foundation grants DMI-0085136 and DMI-0100123 Air Force Office of Scientific Research grant F49620-03-1-0348. Marco Gero Fernández is supported by a National Science

Foundation IGERT Fellowship through the TI:GER Program at the Georgia Tech College of Management (NSF IGERT-0221600) and a President’s Fellowship from the Georgia Institute of Technology.

Documents

1 Systems Realization Laboratory Modeling Simulation-Based Design Processes via Reusable Decision Centric Templates 3-P Information Model for Simulation-Based