KDI: Networked Engineering A Joint Research Initiative of CMU-Drexel-USC William C. Regli Assistant...
-
date post
21-Dec-2015 -
Category
Documents
-
view
217 -
download
0
Transcript of KDI: Networked Engineering A Joint Research Initiative of CMU-Drexel-USC William C. Regli Assistant...
KDI: Networked Engineering
A Joint Research Initiative ofCMU-Drexel-USC
William C. Regli
Assistant Professor and Director
Geometric and Intelligent Computing Laboratory
Department of Mathematics and Computer Science
Drexel University
http://gicl.mcs.drexel.edu
KDI:NE Project Goals
To develop, integrate and evaluate information systems for distributed and collaborative design and manufacturing.
Project Overview
• NSF Grant: CISE/IIS-9873005 Drexel University
• Program: NSF Knowledge and DistributedIntelligence (KDI) Initiative
• Amount: $1.2M• Duration: October 1998 -- October 2001
One of 40 projects selected in 1998 (of 697 proposed)
Principal Investigators
• Carnegie Mellon University– Pradeep Khosla– Ramayya Krishnan
• University of Southern California– Berok Khoshnevis – Stephen Lu
• Drexel University– Thomas Hewett– William Regli
Industry and Gov’t Partners
• AT&T Labs, Internet Platforms• National Institute of
Standards and Technology• Structural Dynamics
Research Corporation (SDRC)• Delaware Valley Industrial
Resource Center (DVIRC)• Bridgeport Machine Tools• Ford Motor Company
KDI: Networked Engineering
• Communication of Information– within an office– across virtual organizations– to suppliers and customers
• Access to Services– human expertise– software agents
• Collaboration & Negotiation– among different disciplines and departments
InformationInformation
ServicesServices
CollaborationCollaboration
KDI:NE Research Objectives
• Design Repositories– Engineering knowledge-bases to leverage legacy knowledge
• Composable Simulation– CAD enhanced with engineering analysis and behavior models
• Collaborative Negotiation– Conflict management strategies for design
• Usability Evaluation– Assess computational support for collaborative design
• Networked Engineering Studios– Integrate Internet, collaboration, and CAD tools
Design Repositories
Goals:Record, archive and manage design information as it is created during distributed design activities.
Approach:– Message model for distributed design– Process archival methodologies to populate design knowledge-bases– Retrieval strategies for design knowledge-bases
Impact:– Enables variational design– Access and reuse of legacy data and information– Platform for networked collaboration on and knowledge sharing about design
problems
Related Project: NSF CAREER Award CISE/IIS-9733545
)θF(θG(θθθ,VθθM ,))()( s
Engineering Digital Libraries
… contain CAD models, assemblies, plans, revisions, S-B-F models, project information and workflows, design rationale...
Research Objectives
• Integrated engineering knowledge-bases and engineering digital libraries
• Intelligent decision support tools for design
• Techniques to leverage legacy knowledge
Current Results and Accomplishments:
• Graph-based structures for knowledge modeling
• Geometric search algorithms
• Collaborative/Conceptual interfaces
• Internet-Based Design Repository
National Design Repository
http://www.parts.nist.gov
http://repos.mcs.drexel.edu
• Enables national and international participation
• Links in related resources
• To be coupled with intelligent search
and retrieve tools
Involved Drexel/GICLResearch Personnel
• Dr. William C. Regli (MCS)• Dr. Thomas Hewett (PSA)• Dr. Wei Sun (Mech. Eng.)• Dr. Jon Sevy (GICL Asoc. Dir.)• Mr. Gaylord Holder• GRAs
– Vincent Cicirello (MS, 1999)– Xiaochun Hu (PhD)– Max Peysakhov (MS, 2000)– Xiaoli Qin (MS, 1999)– Vera Zaychik (MS, 2000)
• NSF REUs– Lisa Anthony– Dmitry Genzel – J. Elvis John– David McWherter– Yuriy Shapirshteyn– Joshua Wharton
• Part-Time & Workstudy– Binh Le– Victoria Charles
Current Status
• Deploying Repository site• Initial implementation of
– Conceptual query interface– Structure matcher
• Data acquisition – CAD data (w/ SDRC, PTC, NIST)– Process/Assembly Plans (w/ Bridgeport and CMU)
• Integrated with fabrication services– GICL’s Bridgeport 4-axis machining center
Future Work
• Integrate Repository with K-base system
• Approximation algorithms for
– structure matching
– distance measurement
• Enhanced design graph representation
• Experimentation and testing of conceptual design/query interface
• Adaptable query interface for Internet agents
• Integrated cost estimation, planning, and manufacturing network services
Composable SimulationGoals:
Create simulations of mechatronic systems by composing mechanical CAD models, electrical models and information technology.
Approach:– Automatically create product-level simulations– CAD enhanced with analysis and behavior models– Hierarchical distributed simulation architecture– CORBA-based implementation
Impact:– Allow reuse of simulation models– Significantly reduce the time to build simulators– Increase fidelity of simulations
Scenario: Conceptual Design...
Pitch Motor
MechanicalSystem
)θF(θG(θθθ,VθθM ,))()( s
smmm bJ
smmm bJ
)( pmss K
)( ymss K
PID
PID
Coupling
Coupling
Yaw Motor
Reference
Reference
Yaw
Pitch
m
p
y
mControlSignal
ControlSignal
p
y
s
s
… to Model SimulationDesign concept CAD and
Virtual prototyping
Model synthesis
Mod
el s
ynth
esis
and
refin
emen
t
Automatically generatedynamic model and simulation software.
Proto
type
refin
emen
t
Dynamics
Pitch motor
Control
Control
Ref.
Ref.
Yawmotor
ComponentModels
ComponentModels
Simulation softwarearchitecture
Simulation softwarearchitecture
SimulationprocessesSimulationprocesses
InformationAgents
InformationAgents
Linpack
Odepack
Matlab
Dymola
ACIS
ConceptualDesign
ConceptualDesign
System Overview
Novel Features
• Creation of simulation software by combining individual simulation processes
• Inclusion of information agents in simulation process
• Provision of distributed environment
• Automatic model refinement
Component Models
• Object-Oriented Modeling Paradigm – reuse of models
• Design Repository used to select CAD components– incorporates ADAMS or DADS
• Information Agents– control system algorithms– environment definition
Software Architecture• Analyze conceptual graph to create
simulation processes– distributed objects– retrieve CAD information via ACIS
• Build simulator architecture– synchronization mechanisms– communication protocols
• Execute simulation
Collaborative Negotiation
Goal:Develop systematic methods to establish optimal strategies to guide design team interactions and to manage design conflicts raised from these interactions.
• Approach:– Game-theoretic modeling of collaborative design activities– Establishment of conflict management strategies for mechatronic design
problems
• Impact:– Theoretical foundations for new software tools to support collaboration and
negotiation activities– Techniques for trade-off analysis in mechatronic systems design
• Related Projects:– DARPA/CMU CODES– CMU DecisionNet
Outline• The problem context
– enterprise-wide decision support for military logistics planning
• The approach– use an e-commerce metaphor to create a virtual repository
of decision support resources
• The research challenges– metadata (what kinds, representation..)– the search and discovery problem
Overview of DecisionNet• Architecture
– Providers/developers of decision support objects
• register with broker
• provide metadata
– Broker(s)
• compiles metadata into a catalog
• supports search to respond to consumer queries with varying degrees sophistication
• returns executable plans (an ordered collection of services)
– Users
• use broker to search and retrieve resources/computational plans
• use broker to execute resources to solve problem
• computational objects in the repository
Networked Engineering Studios
Goal:Deploy testbed of Design Studios that integrate Internet technologies and collaboration/multimedia tools with proactive CAD systems and inter-networked engineering and fabrication services.
• Approach:– Leverage vBNS, COTS software and strong industry collaboration
– Merge collaborative work tools with tools for design, manufacturing, negotiation and Product Data Management (PDM)
• Impact:– Interdisciplinary learning/work environment: CS/EE/ME/Psyc/CE/IE/HCI
– New classroom for industry
– Platform for evaluation
vBNS Logical Network MapLast Updated 2/1/99
NOTE: Lines between institutions and aggregation points or NAPs represent the configured bandwidth of their connection to the vBNS.The bandwidth of the actual circuits may be greater than shown.
75 Operational Connections19 Planned Connections
MIT
13.8 Mbps
Wayne State
Wisconsin @
Milwaukee
Purdue
UMass
Chicago
Los Angeles
Boston
Texas
Cal PolyPomona
Cal State San Bernardino
New York City
Perryman, MD
Columbia
NYU
George Washington
Georgetown
SDSU
HoustonCalREN-2South
Cleveland
ESnet
iDREN
ESnet
DREN
NREN
ESnet
DRENSREN
APAN35 Mbps
CA*Net II
DREN
NREN
iDREN
ESnet
DREN
NI
NREN
FNAL ANL
San Francisco
Seattle
PNW
Washington @St. Louis
Missouri
MREN/STARTAP
CalREN-2North
NI
Denver
NASAAMES
MAX
MFSDC NAP
SprintNY NAP
SoX
Kentucky
Atlanta
Wake Forest
Penn State
UIUC
Yale
Boston U
Brown
Harvard
Minnesota
ChicagoUIC
Wisconsin @Madison
Northwestern
Iowa
Iowa State
UC Boulder
UtahNCAR
Washington
Ohio State
PSC
NCSA
Oregon State
UC Berkeley
Stanford
UC Davis
UCSF
UCSC
Arizona
UCSD
CalTech
UC Irvine
UC Riverside
UCSBUSC
USC ISI
CMU
Rutgers
Highway 1
UMD
Johns Hopkins
UMBC
VA Tech
UVAODU
Vanderbilt
Duke
NC State
NCSC
UNCUT Austin
Rice
Baylor C.of Medicine
Houston TAMU
IB&T @ Houston
Cornell
Princeton
Alabama @Birmingham
SDSC
MiamiFSU
Indiana
UCLA
Michigan
Notre Dame
GA Tech
MCI Reston
GA State
Michigan State
Merit
UPenn
UNM
Florida
Central Florida
Rochester
NYSERNETSyracuse
Rensselaer
SUNY Buffalo
Washington DC
NIH
MCI - vBNS POP
vBNS Approved Institution
Planned vBNS Approved Institution
vBNS Partner Institution
Network of vBNSPartner Institutions
Planned Network of vBNS Partner Institutions
Aggregation Point
Planned Aggregation Point
DS3
OC3
OC12
UNHDartmouth
Drexel
1998
Evaluation & Human FactorsGoal:
Work with practicing engineers and engineering educators to improve support for design and to understand performance of designers in distributed and collaborative design environments.
Approach:
• Assess computing system support for design and collaborative design through empirical examination of interaction effects among:– Hardware and Software characteristics
– Identifiable sets of users
• Evaluation as part of computing system design process:– Provides feedback to designers
– Enables users to contribute tool and system design ideas
– Forces ongoing concern with goals and the criteria for meeting them
– Evaluation will happen
Impact
• Improved tools for engineering design and collaboration• Tools that designers will want to use • Assessment techniques
Collaborators:– DVIRC
– Drexel ME
– SDRC
– Bridgeport
– Ford
– NIST
CUP: Conceptual Understanding and Prototyping
• Functional requirements“Enable back-of-the-envelope sketching”– capture basic 3D assembly structure– part relationships– function characteristics– behavior characteristics
• Collaborative environment• Internet-Centric