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
Systems Realization Laboratory
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?
Systems Realization Laboratory
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
Systems Realization Laboratory
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?
Systems Realization Laboratory
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
Systems Realization Laboratory
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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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Systems Realization Laboratory
A Process Perspective
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Process = Order in which Relationships are Applied
Product Perspective
Process Perspective
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Systems Realization Laboratory
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
Knowledge
Information
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
Systems Realization Laboratory
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?
Systems Realization Laboratory
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
Systems Realization Laboratory
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?
Systems Realization Laboratory
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
Systems Realization Laboratory
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
1
n3
n2 n1
n
To judge the value of the representation, one needs to relate it to decisions
Systems Realization Laboratory
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
Systems Realization Laboratory
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
Systems Realization Laboratory
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?
Systems Realization Laboratory
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
Systems Realization Laboratory
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
Systems Realization Laboratory
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
Systems Realization Laboratory
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)
Systems Realization Laboratory
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?
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