1 research topics & initial mapping plm focus areas git activities plm center of excellence ...
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Research Topics & Initial Mapping PLM Focus Areas GIT Activities
PLM Center of Excellencehttp://www.marc.gatech.edu/plm/Georgia Institute of Technology
Document Contacts:[email protected]@me.gatech.edu
[email protected]@marc.gatech.edu
February 5, 2004
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Sample GIT PLM-Related Activities
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
MarketingStrategy
DesignRepositories
Change Mgt. in Product Model
Databases
Virtual Factories
Robust Design Simulation
Collaborative Design Optimization
Aircraft Lifecycle Support Product Family
Design
Collaborative Visualization
Environments
Standards for Systems Engineering
Lean Principles
Composable Simulations
Design-Analysis Integration
Strategic Design
Factory Information
Systems
Source: IBM PLM definition slide at PDES Inc. Board Mtg. 2003-11
Engineering Knowledge
RepresentationDesign-Supply ChainProcess Integration
IE: McGinnis
CoC: Rossignac
AE: Mavris
MARC: Dugenske
Arch: Eastman
ME: Fulton
MARC: Peak
Mgt: Malhotra
ME: Paredis
AE: Schrage
ME: Mistree
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PLM Focus Areas Addressing Top Industry Pain Points
Man
age
Man
age
Op
erat
ion
s O
per
atio
ns
& S
yste
ms
& S
yste
ms
Red
esig
n
Red
esig
n
Pro
cess
esP
roce
sses
Inst
all S
W
Inst
all S
W
and
an
d
Sys
tem
sS
yste
ms
PLM Integration / Collaboration Framework & Asset Portfolio
• Build integration tools assets and processes
Component, PlatformAsset Commonality
• Reuse parts and systems across products
Extended Enterprise Product Change Management
• Integrate changes across value chain
Product DevelopmentInfrastructure Outsourcing
• Manage & maintain PLM applications and infrastructure
Product Innovation Management
• Manage balanced product development investment portfolio
Virtual Product Innovation
• Design & test products, production, services online
Service After Sales
• Support products after sales
Business Process Outsourcing
• Outsource design of products and subsystems
ConceptConceptDevelopmentDevelopment
ProductionProduction& Testing& Testing
MaintenanceMaintenance& Support& Support
PortfolioPortfolioPlanningPlanning
DesignDesignSales & Sales &
DistributionDistribution
Source: IBM slides at PDES Inc. Board Mtg. 2003-11
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Mapping PLM Focus Areas GIT Activities - p1
Product Innovation Management Strategic design (Mistree) IPPD and PLM integration (Schrage, Hart) Marketing strategies over the product life-cycle (Malhotra)
Component, Platform and Asset Commonality Product family design (Rosen, Mistree) Design repositories (Paredis, Eastman ) Domain-oriented product access and management (Eastman) Lean principles (Schrage) Adoption and continued use of products and technologies (Malhotra)
Extended Enterprise Product Change Management Course: Interactive Computer Graphics and Computer-Aided Design
(Fulton, Sitaraman, Dennis) Course: Intro to PLM (Schrage, Hart) Engineering knowledge representation & info. systems (Peak, Fulton) Change management in product model databases (Eastman)
(and related faculty)
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Mapping PLM Focus Areas GIT Activities - p2
Virtual Product Introduction Course: Design and Engineering Database Management
(Fulton, Eastman, Peak) Course: Modeling and Simulation in Design (Paredis, Peak) Design-analysis integration (Peak) Standards for systems engineering (Peak, Paredis) Decision-based design (Mistree, Allen) Designing open processes (Mistree) Composable simulations (Paredis) Virtual factories (McGinnis, Bodner) Factory information Systems (Dugenske) Robust design simulation (Mavris) Collaborative visualization environments (Mavris) Collaborative design optimization (Olds and Braun) Visualization and human computer interaction (Rossignac)
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Mapping PLM Focus Areas GIT Activities - p3
Service after Sales Aircraft lifecycle support (Schrage)
Manage Operations & Systems Course: Aerospace Systems Engineering (Schrage) Domain specific parametric tool specification and
procurement (Eastman) Integrating design chain processes with supply chain
processes (Mistree) Standards-based engineering frameworks (Peak)
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Quad Charts for Sample Research Topics
PLM Center of Excellencehttp://www.marc.gatech.edu/plm/Georgia Institute of Technology
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Next-Gen. PLM with Fine-Grained Interoperability
Domain
Abs
trac
tion
Leve
l
Req
uire
men
ts
Str
uctu
res
Ele
ctro
nics
Hum
an
Inte
ract
ion
Systems Engineering
Models of varied abstractions and domains
Legend
Model interfaces:Associativities among domain-specific models & system-level models
Dev
elop
men
t Pro
cess
…
Fine-grained models: Information objects Parametric relations
…
…
…
…
…
After Bajaj, Peak, & Waterbury2003-09
Customer Needs /Acquisitions…
Hierarchic Market Space Definition and Exploration
Student: Christopher Williams Faculty: Farrokh Mistree, Janet K. Allen
Objectives Contributions & Benefits
Background Resources, Status, Publications, etc.
• To develop formal, mathematically correct, and rigorous principles for designing product architectures that facilitate the production of customized products.
• Determine an optimal arrangement of product variety techniques that link all points in the market space in order to satisfy any customer demand so that cost is minimized.
Sequencing modes of managing product variety• How can a designer synthesize multiple modes of managing product variety in
order to realize a customized product?• How does the designer select which mode to use first? What sequence will
provide the most affordable coverage of the market space at a high quality?Dealing with non-uniform demand• How does the arrangement of the hierarchy change as demand is non-uniform?• Can this question be answered without using varying sized constructs?• Will this affect the sequencing of the modes of managing product variety?
• Provision of manufacturing firms an efficient (through rigorous and systematic methodology) foundation for realizing customized products, thus enhancing the responsiveness of manufacturing organizations to changes in the market or demands for customization.
Williams, C. B., Panchal, J., Rosen, D. W., 2003, “A General Decision-Making Method for the Rapid Manufacturing of Customized Parts,” accepted by the 23rd Conference on Computers and Information in Engineering, ASME, September 2-6, Chicago, Illinois.
Carone, M. J., Williams, C.B., Allen, J. K., and Mistree, F., 2003, “An Application of Constructal Theory in the Multi-Objective Design of Product Platforms,” accepted by the 15th International Conference on Design Theory and Methodology, ASME, September 2-6, Chicago, Illinois.
Hernandez, G., Williams, C. B., Allen, J.K., Mistree, F., “Design of Platforms for Customizable Products as a Problem of Access in a Geometric Space,” Journal of Mechanical Design, Submitted.
Hernandez, G., Allen, J.K., and Mistree, F. 2002, “Design of Hierarchic Platforms for Customizable Products,” ASME Design Automation Conference, Montreal, Canada, DETC2002/DAC-34095.
Hernandez, Gabriel, 2001, “Platform Design for Customizable Products as a Problem of Access in a Geometric Space,” Ph.D. Dissertation, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA.
Constructal Theory• The hierarchic structures (tree networks) that we observe in natural and
artificial systems are the “fingerprint” of the minimization of flow resistance between a finite volume and one point.
• An access problem can be solved through the optimization of the shape of the smallest, inner-most space elements and the hierarchic assembly of these elements into larger “constructs” until covering the entire geometric space.
• The abstraction of a space of customization as a geometric space in need of access optimization, allows a designer to effectively develop a product architecture for customized products.
Scholarship
Industry
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• SRL Knowledge Base• X-DPR, iSIGHT, Matlab, Concurrent Versioning System (CVS)
• Nearing completion of MS Research• Adaptation to the development of a process family• Consideration of non-uniform demand, risk and uncertainty
Status
Resources
Publications
Strategic Design
Student: Matthew Chamberlain Faculty: Farrokh Mistree
Contributions & BenefitsScholarship• Effective tools for creating representations of n-dimensional market spaces and
design capabilities• Systematic approaches for designing families of products that can evolve and
accommodate change and innovation and a systematic tool for choosing between multiple available approaches
• Methods for forecasting and characterizing the impact of innovation on a feasible space in a manner meaningful to the design process
Industry• Computing, information, and decision frameworks for coordinating distributed
decision makers carrying out strategic design• Methods for linking market and design capability forecasts to design decisions
and plans for product portfolios
Tasks• Strategic product planning techniques for forecasting dynamic requirements and
technological capabilities and for assessing the potential impact of innovation on complex products and processes.
• Product variety design techniques for leveraging and adapting existing products.• Decision support techniques that are formal, rigorous, and flexible, and account for
uncertainty• Coordination mechanisms for multiple agents in product development activities• Flexible computing and information infrastructures for effective distributed design
Resources• One student.
Publications• Seepersad, C. C., F. S. Cowan, M. K. Chamberlain and F. Mistree, 2002,
"Strategic Design: Leveraging and Innovation for a Changing Marketplace," Engineering Design Conference, King's College, London, pp. 3-20.
• Chamberlain, M. K., 2002, “A Step Towards Web-Based Strategic Design,” MS Thesis, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA.
BackgroundStrategic Design is a comprehensive approach for designing products and processes that efficiently and effectively accommodate…
•changing markets and associated customer requirements•technological innovations
… In a collaborative, distributed environment
Property A
Pro
pert
y B
x
AvailableTechnology
Future Technology
Expanded Technology
Property A
Pro
pert
y B
x
AvailableTechnology
Future Technology
Expanded Technology
Objectives• To establish a method for allowing distributed designers to collaborate
on the design of products while taking into account:•Changes in market trends•Changes in the capabilities of existing technologies•New or evolving technologies
• To develop a number of new techniques that would be parts of a strategic design method, including:
•N-dimensional market visualization techniques•Innovation modeling and early technology impact forecasting methods
• To develop a plan for coordinating the many disparate methods that would make up strategic design as well as a logic for choosing between different modes of managing product variety
Objectives Contributions & Benefits
Background Collaboration Needed
References
Development of• A method for Integrated Design of Products and Design Processes• Computational model of design processes in the form of a design equation• Quantitative metrics for openness of products and processes• Method for synthesizing design processes• Application to design of materials
• Means for improvement of design processes• Systematic method for configuring design chains• Design knowledge reuse in an organization• Tools for modeling and reconfiguring design processes• A new dimension to the design information management and reuse
Design Equation: K = T (I)
Scope
Pro
ce
ss
De
tail
Bottom up
Top down
Design process at various levels
[1] B. A. Bras, "Designing Design Processes for Decision-Based Concurrent Engineering," presented at CERC's First Workshop on Product Development, Process Modeling and Characterization, Morgantown, West-Virginia, 1992.[2] F. Mistree, W. F. Smith, B. Bras, J. K. Allen, and D. Muster, "Decision-Based Design: A Contemporary Paradigm for Ship Design," in Transactions, Society of Naval Architects and Marine Engineers, vol. 98. Jersey City, New Jersey, 1990, pp. 565-597.[3] D. Muster and F. Mistree, "The Decision Support Problem Technique in Engineering Design," International Journal of Applied Engineering Education, vol. 4, pp. 23-33, 1988.
Decision Based Design
Decision Support Problem (DSP) Technique
2 PhD StudentsStudent 1: Development of method for Integrated Design of Products and Design ProcessesStudent 2: Application of the method to design of materials
Student: Jitesh H. Panchal Faculty: Farrokh Mistree, Janet K. Allen
Design Process, Information, and Knowledge Management in Distributed, Collaborative Design
A Decision Support Framework (DSF) for Distributed Collaborative Design and Manufacture
(DCDM)Student: Marco Gero Fernández Faculty : Farrokh Mistree and Janet K. Allen
Objectives Contributions & Benefits
Background
Resources, Status, Publications, etc.
• Develop and commercialize a Decision Support Framework (DSF) for Distributed Collaborative Design and Manufacture (DCDM), where decision support refers to the cumulative means of modeling, structuring, and negotiation solutions to decisions and any of their interactions.
• Provide a consistent mechanism for supporting designers in their capacity as decision-makers. The fundamental goals are to (1) manage the design process, (2) facilitate the collaboration of stakeholders, and (3) effectively share information.
• Effectively structure design processes and properly reflect decision critical information and any dependencies.
• This research will expand upon a substantial knowledge base in Decision Based Design, design theory, and decision theory that has evolved in the Systems Realization Laboratory (SRL) since its establishment in 1992.
• It is the nature and types of decisions, implemented that determine the progress of a design
• Decisions in all stages of engineering design depend on scientific, factual information as well as empirical, experience-based knowledge, designer preferences, and uncertainty.
• There is a need to propagate decision-critical, up-to-date information alongside design knowledge for both sequential and concurrent design tasks, particularly for dependent and interdependent decisions that cannot be made in isolation.
• Emphasis is placed on development of theory, creation of domain independent constructs for characterizing and modeling decisions, and formalization of interactions among distributed design agents via digital interfaces
• Development of logic for design process reconfiguration and investigation of strategic decision-making/resource allocation
• Facilitation of strategic decision-making from a systems perspective and enhancement of design process reconfiguration with regard to flexibility, efficiency, and effectiveness.
• Enablement of companies to trace errors to their origins within a given design chain and allow for remediation through dynamic design modification and/or process reconfiguration
Fundamental Assertions
Designer #1 Designer #2 Designer #3 Designer #4
ELECTRICALENGINEERING
THERMALENGINEERING
LedgerResource $Activity $Total $
LedgerResource $Activity $Total $
STRUCTURALENGINEERING
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• SRL Knowledge Base• X-DPR, iSIGHT, Web Board, Concurrent Versioning System (CVS)
• Completion of MS Research, Development of Decision Constructs and Information Model required for DSF
• Active consideration/infusion of Risk and Uncertainty into decision-making
Fernández, M.G., D.W. Rosen, J.K. Allen, and F. Mistree (2002). “A Decision Support Framework for Distributed Collaborative Design and Manufacture”. 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, GA, AIAA-4881.Others available upon request.
Publications
Status
Resources
Scholarship
Industry
The Role of Decisions throughout the Design Process…
The Role of Decisions throughout the Design Process…
The Strategic Reduction of Design Freedom through Decisions…
The Strategic Reduction of Design Freedom through Decisions…
15 Students Faculty: Wayne Book, Mark Allen, Imme Ebert-Uphoff, Ari Glezer, David Rosen, Jarek Rossignac
Background
Define state-of-the-art in haptics (force-based) computer interaction. Greatly impact distributed collaboration when shape must be
communicated. Potentially, impact the ability for visually impaired people to interact
with computers. Significantly impact technology in hydraulics, controls, kinematics,
manufacturing, and human-computer interface areas.
Contributions & BenefitsObjectives Develop an interactive, 3-D haptic computer input/output device.
Specifically, the device will enable:• Shape input through a “sculpting” interaction mode• Shape display of a computer model (e.g. CAD model)• Stiffness (“feel”) display of shapes with various material
properties. Demonstrate the digital clay device on a variety of mechanical and
architectural shape design applications, distributed collaboration, and dynamic simulations.
Hydraulics will be used for actuation and sensing. A formable skin will comprises the bulk and shape of the “clay”
device. The skin will have inflatable bladders to enable the skin to change shape and to sense user forces.
Stereolithography used to fabricate skin and clay structure. MEMS technologies will be utilized to fabricate array of pressure
sensors and valves in device backplane. Human-computer interface studies will determine appropriate
methods of interaction with clay devices.
Collaboration Needed 1 student to develop digital clay prototypes and test them in
mechanical design applications. Materials and supplies to construct digital clay prototypes.
References Bosscher, P. and Ebert-Uphoff, I., “Digital Clay: Architecture Designs for Shape-
Generating Mechanisms,” IEEE Robotics and Automation Conference, 2003. Rosen, D.W., Nguyen, A., and Wang, H., “On the Geometry of Low Degree-of-
Freedom Digital Clay Human-Computer Interface Devices,” Proceedings ASME CIE Conference, paper DETC2003-48295, Chicago, Sept. 2-6, 2003.
Zhu, H. and Book, W.J. “Control Concepts for Digital Clay,” 7th Annual International Symposium on Robot Control: SyRoCo 2003, Sept. 1-3, 2003, Wroclaw, Poland.
Supported by 5 year NSF grant.
Digital Clay for Shape Input and Display
Constrained Objects: A Knowledge Representation for Design, Analysis, and Systems Engineering Interoperability
Students: Manas Bajaj, Injoong Kim, Greg Mocko Faculty: Russell Peak
Approach & StatusApproach
Extend and apply the constrained object (COB) representation and related methodology based on positive results to date
Expand within international efforts like the OMG UML for Systems Engineering work to broaden applicability and impact
Status Current generation capabilities have been successfully
demonstrated in diverse environments (circuit boards, electronic chip packages, airframes) with sponsors including NASA, Rockwell Collins, Shinko (a major supplier to Intel), and Boeing.
Templates for chip package thermal analysis are in production usage at Shinko with over 75% reduction in modeling effort (deformation/stress templates are soon to follow)
Objectives Develop better methods of capturing engineering knowledge that :
Are independent of vendor-specific CAD/CAE/SE tools Support both easy-to-use human-sensible views and robust computer-sensible formulations in a unified manner Handle a diversity of product domains, simulation disciplines, solution methods, and leverage disparate vendor tools
Apply these capabilities in a variety of sponsor-relevant test scenarios: Proposed candidates are templates and custom capabilities for design, analysis, and systems engineering
Contributions & BenefitsTo Scholarship Develop richer understanding of modeling
(including idealizations and multiple levels of abstraction) and representation methods
To Industry Better designs via increased analysis intensity Increased automation and model consistency Increased modularity and reusability Increased corporate memory
via better knowledge capture
Additional Information:
1. http://eislab.gatech.edu/projects/
2. Response to OMG UML for Systems Engineering RFI:http://eislab.gatech.edu/tmp/omg-se-33e/
3. Characterizing Fine-Grained Associativity Gaps: A Preliminary Study of CAD-E Model Interoperabilityhttp://eislab.gatech.edu/pubs/conferences/2003-asme-detc-cie-peak/
Collaboration Needed Support for 1-3 students
depending on project scope Sponsor involvement to
provide domain knowledge and facilitate pilot usage
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Constrained Object (COB) Formulations
COB-based Airframe Analysis Template
Chip Package Stress Analysis Template
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Composable Simulations: Model Archiving and Reuse for Systems DesignStudents: Rich Malak, Tarun Rathnam, Steve Rekuc Faculty: Chris Paredis
Approach & StatusApproach Semantically rich product representations in OWL (Web
Ontology Language); combined with object-oriented simulation models in Modelica
Define and populate a repository of components and models to demonstrate reuse and composition
Investigate the compatibility, composability, and accuracy of models and model configurations.
Status We have demonstrated the concept of composable
simulations for satellite systems (with Lockheed-Martin) and for transportation systems (with Bombardier).
We have implemented an initial software prototype, COINSIDE: Composition in Simulation and Design.
Shaft-PulleyInteraction
Pulley
Bolt_4
Component Configuration
Mo
del
s
PulleyACMotor
Wire_1Wire_2Wire_1
Bolt_1
Bolt_3
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ShaftPort
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Co
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on
Shaft-PulleyInteraction
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Objectives Develop integrated representations for multi-disciplinary products
and their corresponding behavioral models
Develop algorithms for reusing and composing simulation models of individual components into models for entire systems
Characterize the validity and accuracy of simulation models at multiple levels of abstraction
Support the seamless transition between models at multiple levels of abstraction while progressing through the design process
Contributions & BenefitsTo Scholarship Develop understanding of the relationship between configuration of
components and configuration of simulation models Create ontology for ports (locations of intended interaction) and artifacts Develop understanding of validity and accuracy of models to enable reuseTo Industry Faster and broader exploration of design space Capture history of design exploration and analyses Save resources by reusing validated simulation models
Additional InfoC.J.J. Paredis, A. Diaz-Calderon, R. Sinha, and P.K. Khosla, "Composable Models for Simulation-Based Design", Engineering with Computers. Vol. 17, pp. 112-128, 2001. (http://www.cs.cmu.edu/~paredis/pubs/EWC01.pdf)
Collaboration Needed Support for 1-2 students
depending on scope of study
Engineering support to provide application domain knowledge for example study.
COINSIDE framework:Composition in Simulation and Design
Composition of port-based objectsallows for automatic composition of thecorresponding simulation andCAD models
http://srl.marc.gatech.edu/people/paredis/
Students: Jin-Young Choi, Nan Li Faculty: Leon McGinnis
Approach & StatusApproach
Use HLA to support distributed simulation, using legacy models where necessary
Develop general purpose simulation models for warehouses and transportation
Develop supply chain manager modelsStatus
First generation distributed simulation demonstrated, using factory models at SimTech, and warehouse and transportation models at Georgia Tech
Ongoing development of generic warehouse, transportation and supply chain manager models
Objectives Develop distributed simulation testbed for analyzing global supply
chains, including factories, warehouses, transportation
Use the distributed simulation testbed to investigate alternative designs, planning methods, and supply chain management methods
Contributions & BenefitsTo Scholarship
Testbed for evaluating proposed supply chain planning/management methods
To Industry Tools that permit collaboration between supply chain partners to
analyze/design the supply chain without revealing proprietary data
Additional InfoThis project has been conducted in collaboration with SimTech, the Singapore Institute for Manufacturing Technology
Collaboration Needed Demonstration case study
Development and evaluation of specific supply chain planning and/or management methods
Integrating existing legacy models to permit supply chain analysis
School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA 30332-0205 http:/ / factory.isye.gatech.edu
Supply Chain Design and Analysis Testbed
Students: 5 PhD students Faculty: L. McGinnis, C. Zhou, S. Reveliotis
Approach & StatusApproach
Object oriented Separation of process and control Explicit material handling Java, HLA
Status Third generation toolkit Currently testing against Sematech 300mm model
Objectives Develop a new generation of factory modeling tools that:
Support high fidelity description of factory resources and operations
Are based on concepts that map one-to-one with factory entities
Enable abstraction to support more aggregate models and analyses
Demonstrate new tools in semiconductor wafer fabs
ContributionsTo Scholarship
Comprehensive reference model for semiconductor fabrication operations
Testbed for exploring alternative factory designs, alternative scheduling and control methods
To Industry Testbed for evaluating proposed factory designs or factory planning and
control strategies
Additional Infohttp://factory.isye.gatech.edu/vfl/research/hifive.php
For interim status report, presentations, and demonstrations
Collaboration Needed Demonstration case studies of specific fabs
Evaluation of through-stocker versus point-to-point AMHS
Linking factory operations models with “real” factory control software to create a “virtual” factory
…
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Lot ReleaseController
InterBay MHSController
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IntraBay MHSController
Distributed Simulation ModelDistributed Simulation Models
SimulationExecution Architecture
IntegratedAnimator
Database
Virtual operational data set
Fab model
Fab DesignerScheduler
DesignFab model
Fab Design Architecture
Fab Model,Equipment Lib,Product Lib,Operation Data Set Output
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Data Analysis Architecture
Federates
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tion
…
Runtime InfrastructureInterface
Lot ReleaseController
InterBay MHSController
Bay 1Controller
IntraBay MHSController
Distributed Simulation ModelDistributed Simulation Models
SimulationExecution Architecture
IntegratedAnimator
Database
Virtual operational data set
Fab model
Fab DesignerScheduler
DesignFab model
Fab Design Architecture
Fab Model,Equipment Lib,Product Lib,Operation Data Set Output
Analyzeroperational data set
Data Analysis Architecture
Federates
Federa
tion
School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA 30332-0205 http:/ / factory.isye.gatech.edu
High Fidelity Factory Modeling
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GIT Contacts & Departments
AbbreviationsAE School of Aerospace EngineeringCoA College of ArchitectureCoC College of ComputingCoM College of ManagementCoE College of Engineering CEE School of Civil and Environmental EngineeringECE School of Electrical and Computing EngineeringECS Engineering Computing Services (campus CAx services - under GIT CoE)ISyE School of Industrial and Systems EngineeringMARC Manufacturing Research CenterME School of Mechanical Engineering (includes Nuclear and Health Physics)OIP Office of Interdisciplinary ProgramsPTFE School of Polymer, Textile & Fiber Engineering
ASDL Aerospace Systems Design LabCBAR Center for Board Assembly ResearchEIS Lab Engineering Information Systems LabFIS Group Factory Information Systems GroupMISL MARC Information Systems LabPLMCC Product Lifecycle Management Center of CompetencePLM CoE Product Lifecycle Management Center of ExcellenceRPMI Rapid Prototyping & Manufacturing InstituteSRL Systems Realization Lab
GIT Organization Chartshttp://www.provost.gatech.edu/flowchart.html
Be aware that CoE has two meanings above: Center of Excellence and College of Engineering
Unit Dept. First Name Last Name Titles
Admin - Dr. Charles Liotta Vice Provost for Research and Dean of Graduate Studies
OIP MARC Dr. Steve Danyluk MARC Director, Prof. and Bryan Chair in ME
OIP MARC Mr. Andy Dugenske Senior ResearcherOIP MARC Dr. Russell Peak Senior Researcher
CoA - Dr. Chuck Eastman Director, PhD Program and Professor
CoC GVU Dr. Jarek Rossignac Professor
CoE - Dr. Narl Davidson Associate DeanCoE ECS Mr. Tord Dennis Research Engineer ICoE ECS Ms. Sandra Pierotti Manager, ECS
CoE AE Mr. Pete Hart Research Engineer ICoE AE Dr. Dimitri Mavris ProfessorCoE AE Dr. Dan Schrage Professor
CoE ISyE Dr. Leon McGinnis Professor
CoE ME Dr. Bob Fulton ProfessorCoE ME Dr. Farrokh Mistree ProfessorCoE ME Dr. Chris Paredis Assistant ProfessorCoE ME Dr. Dave Rosen ProfessorCoE ME Dr. Suresh Sitaraman Associate Professor
CoM - Dr. Naresh Malhotra Regents Professor