systems realization laboratory information economics in design chris paredis the systems realization...

Systems Realization Laboratory

Information Economicsin Design

Chris Paredis

The Systems Realization Laboratory

PLM Center of Excellence

G.W. Woodruff School of Mechanical Engineering

Georgia Institute of Technology

www.srl.gatech.edu www.marc.gatech.edu/plm


What is Information Economics?

Economics• Study of the production, distribution and consumption of goods and services,

and the management of these processes

• Study of how people choose to allocate scarce resources to satisfy competing uses or wants

• A study of choice

Design• Transformation of information from requirements to product description

Information Economics in Design• Which information should be created to support design decisions?• What is the value of information? What is the cost of information?• How can one generate more valuable information at a lower cost?


Foundations of Information Economics

Some history• Daniel Bernoulli (1738) – Expected utility

• Knight (1921) – Risk and uncertainty in economics

• von Neumann & Morgenstern (1944) – Utility theory

• Marschak (1950s) – Economics of organization and information

• Renewed interest in the context of Information Systems (1990s)

Value of information = the difference in the expected value of a decision made with or without considering the information

| 0( ) [ [ ( , ) ( , )]]y x y yV E E x a x a I

message from an information source state from a state space

yx

IX

decision actionpayoff

a


Overview of Presentation Context

• What is Information Economics?• Information and Knowledge in Product Development

Examples of Information Economics in the SRLRelated to Information• How should one represent information and uncertainty?• How should one use uncertain information to make decisions?• How should one compute with uncertain information?• Which information should one gather?• Which models should one use?Related to Knowledge• How should one represent knowledge, models?• How should one manage knowledge, models?• How should one design the design process?


Product Development: A Decision-Based Perspective

Concept

Development Design

Production

& Testing

Sales &

Distribution

Maintenance

& Support

Portfolio

Planning

Decisions

Evaluate Alternatives

GenerateAlternatives

Select Alternative

KnowledgeInformation

GenericDecisionProcess


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Information-Driven Product Development

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DesignersSuppliers

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Manufacturing

AnalystsImplicit

Not Computer- interpretable

Not Interoperable

Coarse-grainedPDM

CAD1CAD2

FEM

ProcessPlanning

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A Process Perspective

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Process = Order in which Relationships are Applied

Product Perspective

Process Perspective

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Product Lifecycle Management Framework

Infrastructure: Security Notification Communication VisualizationInfrastructure: Security Notification Communication Visualization

ProcessPerspective

Requirements Definition

Product Portfolio Planning

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Maintenance & Support

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Knowledge

Information

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ExecutionPerspective

GRIDAnalystsAnalystsDesignersDesigners

SuppliersSuppliers ManufacturingManufacturing

CAD

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CADFEM

ProcessPlanning

PDM

Product Perspective

Information

Knowledge

Information

Knowledge

Information

Knowledge

Information

Knowledge

Information

Knowledge

Knowledge& InformationRepositories


Research Issues

We need to develop a deeper understanding ofthe structure of the PLM information graph• Which concepts & relationships? Ontologies

• How to represent information and knowledge? uncertainty, context, …

• How to reconcile multiple ontologies? interoperability

• Reusable patterns? Knowledge Repositories

We need methods for managing the PLM information graph(creating, sharing, modifying,…)• Which tools to create and modify info? maps to stakeholders

• In which order to build the graph? concurrent engineering How to coordinate among multiple stakeholders? How to maintain consistency? How to propagate changes?

• How to maintain, retrieve and apply reusable knowledge templates?


Research Issues

We need an IT infrastructure for distributed computation and collaboration support• How to integrate multiple simulation, analysis, and optimization tools in a

distributed fashion? Interoperability, security, load balancing, …

• How to provide geographically distributed decision makers with relevant information – in real-time?

Overall ThemeHow can one design better at a lower cost?

Guiding PrincipleMaximize net value of decisions about both product and process

Increase the value – Decrease the cost


How should one represent information and uncertainty?(Jason Aughenbaugh, Scott Duncan)

Aleatory uncertainty• Inherently random – irreducible

• Best represented as probability distribution

• Examples: Manufacturing variability

Epistemic uncertainty• Due to a lack of knowledge

• Best represented as interval

• Examples: Error due to model approximation Future design decisions

Choose the representation that results in best design decisions

x1

x2

q1

q2

u1

u2

u3

u4

PDF/PMF

value[ ]u5


Combines probability distributions and intervals

P-box: Upper and Lower bound on all plausible CDF's

Generalization of both intervals and probability distributions

Probability Bounds Analysis – P-boxes(introduced by Ferson and Ginzberg, 1996)

Interval [0,1]

-1 0 1 20

0.5

1

x

-3 -2 -1 0 1 2 3 40

0.5

1

t

Normal( [0,1],1)-10 0 10

0

0.5

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n3

n2 n1

n

To judge the value of the representation, one needs to relate it to decisions


How should one make decision with P-boxes?(Jason Aughenbaugh, Steve Rekuc)

Expected Utility = Interval !!• Maps to set-based design

• Eliminate only the dominated designs

Acknowledging ignorance results in better decisions !

Characterize difference in performance

• Many sources of uncertainty are 'shared'

• Taking dependence into account reduces uncertainty in the difference in performance

Diff in Expected Utility

DV

UB

LB

DV

Expected Utility

UB

LB

Conservative Solution

Make better decisions with the same information


Which information to gather or models to use?(Jay Ling)

If epistemic uncertainty is too large to make a decision• Gather more information

• Perform additional simulations (model = information source)

Perform the action that yields the most bang for your buck

Satisficing solution• When making a better decision

costs more than it is worth

• Optimal in terms of Information Economics

DV

Expected Utility

UB

LB

DV

Expected Utility

Gather additional information most efficiently


How should one representing uncertain knowledge?(Rich Malak)

Strain

Stress

0

σUB

Strain

Stress

0

σUB

,modelstate Domain LB UB modelxfy )( with

ApplicabilityDomain

Epistemic Uncertainty

Goal: Enable sharing and reuse of models – Amortize costs


Reusable and Composable Models(Manas Bajaj, Greg Mocko, Nsikan Udoyen)

Common associations between geometry and analyses/ simulations

Common patterns between CAD description and simulation models

Recurring Pattern

Mass

Material

Has Behavior

Has FormMotor Form

Has Shape

Has Material

Geometry

Has Mass Parameter

Has Energy PortPort

MassEquation

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Information Graph

ReusablePatterns?

Enable reuse of models – Amortize costs


Port-Based Abstraction – Knowledge Templates

Port• Location of intended interaction

• Exchange of energy, material, signal

Abstraction becomes container for associated models

RotorPort

Stator Port

ElectricalConnector

Model 1

Behavioral Models

Model 1Model 1

CAD Models Cost Models

…

Store knowledge in modular, reusable templates – Amortize costs


Goals

Preferences

Variables

Parameters

Constraints

Response

Objective

Analysis

Driver

Goals

Preferences

Variables

Parameters

Constraints

Response

Objective

Analysis

Driver

Pressure Vessel Spring

Reusable, Declarative Decision Templates(Marco Fernandez, Jitesh Panchal)


Summary

Information Economics

A framework for making decisions about design Applies to many of the problems we are working on in SRL Can serve as a guide for new research directions

• Which information costs dominate? How can we reduce the costs?

• How can we improve value?

Questions? Comments?

systems realization laboratory information economics in design chris paredis the systems realization...

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