February 5, 2004
Research Topics & Initial Mapping
PLM Focus Areas  GIT Activities
PLM Center of Excellence
http://www.marc.gatech.edu/plm/
Georgia Institute of Technology
Document Contacts:
Robert.Fulton@me.gatech.edu
Chris.Paredis@me.gatech.edu
Russell.Peak@marc.gatech.edu
Steven.Danyluk@marc.gatech.edu
1
Sample GIT PLM-Related Activities
ME: Paredis
Composable
Simulations
Design-Analysis
Integration
ME: Mistree
Strategic
Design
MARC: Peak
Standards for
Systems Engineering
Lean Principles
IE: McGinnis
Marketing
Strategy
Virtual Factories
Mgt: Malhotra
AE: Mavris
Market
Planning
Portfolio
Planning
Concept
Development
Design
Production
& Testing
Sales &
Distribution
Maintenance
& Support
PLM
Robust Design
Simulation
Customer
Requirements
Design
Collaboration
Manufacturing
Collaboration
Aircraft
Lifecycle
Support
Services
Collaboration
Customer
Feedback
PLM Collaborative Foundation
Customers
Product Family
Design
Customers
Marketing/Sales
Collaboration
B2B integration
CoC: Rossignac
Collaborative
Visualization
Environments
Design
Definition
Partners
Component
Management
Other Enterprise
Locations
AE: Schrage
Design Change
Management
Factory
Information
Systems
MARC: Dugenske
Change Mgt. in
Product Model
Databases
Suppliers
Source: IBM PLM definition slide at PDES Inc. Board Mtg. 2003-11
Engineering
Knowledge
Representation
Arch: Eastman
Collaborative Design
Optimization
Design-Supply Chain
Process Integration
Design
Repositories
ME: Fulton
2
PLM Focus Areas
Addressing Top Industry Pain Points
Source: IBM slides at PDES Inc. Board Mtg. 2003-11
3
Mapping PLM Focus Areas  GIT Activities - p1
Product Innovation Management



(and related faculty)
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)
4
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)
5
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)
6
Quad Charts for
Sample Research Topics
PLM Center of Excellence
http://www.marc.gatech.edu/plm/
Georgia Institute of Technology
7
Next-Gen. PLM with Fine-Grained Interoperability
Customer Needs /
Acquisitions
Abstraction Level
…
…
Systems Engineering
Legend
Human Interaction
Electronics
Structures
Requirements
Development Process
…
…
…
…
Model interfaces:
Associativities among
domain-specific models
& system-level models
Fine-grained models:
Information objects
Parametric relations
…
Domain
Models of varied abstractions and domains
After Bajaj, Peak, & Waterbury
2003-09
8
Hierarchic Market Space Definition and Exploration
Student: Christopher Williams
Faculty: Farrokh Mistree, Janet K. Allen
Objectives
Contributions & Benefits
Scholarship
• To develop formal, mathematically correct, and rigorous principles for
Sequencing modes of managing product variety
designing product architectures that facilitate the production of customized
• How can a designer synthesize multiple modes of managing product variety in
products.
order to realize a customized product?
• Determine an optimal arrangement of product variety techniques that link all
• How does the designer select which mode to use first? What sequence will
points in the market space in order to satisfy any customer demand so that
provide the most affordable coverage of the market space at a high quality?
cost is minimized.
T
T
V
Dealing
with non-uniform demand
V
R
• How does the arrangement of the hierarchy change as demand is non-uniform?
30 P
30
• Can this question be answered without using varying sized constructs?
L
• Will this affect the sequencing of the modes of managing product variety?
P [MPa]
P
P [MPa] 20
Industry
• Provision of manufacturing firms an efficient (through rigorous and systematic
10
methodology) foundation for realizing customized products, thus enhancing the
10
responsiveness of manufacturing organizations to changes in the market or
10
20
30
10
30
demands for customization.
V [m3]
V [m ]
h
s
3
1
1
2
3
Background
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.
S3
S4
S5
S6
S2
y
The Smallest Area, S1
S1
D1
H1
V0
E
V1
L1
.
P(x,y)
x
Time, Complexity, Evolution
Resources, Status, Publications, etc.
Resources
• SRL Knowledge Base
• X-DPR, iSIGHT, Matlab, Concurrent Versioning System (CVS)
Status
• Nearing completion of MS Research
• Adaptation to the development of a process family
• Consideration of non-uniform demand, risk and uncertainty
Publications
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.
Strategic Design
Student: Matthew Chamberlain
Faculty: Farrokh Mistree
Objectives
Contributions & Benefits
• 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
Scholarship
• 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
Background
Tasks
Strategic Design is a comprehensive approach for designing products
and processes that efficiently and effectively accommodate…
•changing markets and associated customer requirements
•technological innovations
• 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
… In a collaborative, distributed environment
Property B
Expanded Technology
Resources
x
• One student.
Available
Technology
Property A
Future Technology
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.
Design Process, Information, and Knowledge Management in
Distributed, Collaborative Design
Student: Jitesh H. Panchal
Objectives
Faculty: Farrokh Mistree, Janet K. Allen
Contributions & Benefits
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
Background
• 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
Collaboration Needed
Design Equation: K = T (I)
Decision Based Design
Process Detail
Decision Support Problem (DSP) Technique
Scope
Design process at various levels
2 PhD Students
Student 1: Development of method for Integrated Design of
Products and Design Processes
Student 2: Application of the method to design of materials
References
[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, "DecisionBased 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.
A Decision Support Framework (DSF)
for Distributed Collaborative Design and Manufacture (DCDM)
Student: Marco Gero Fernández
Objectives
Faculty : Farrokh Mistree and Janet K. Allen
Contributions & Benefits
• Develop and commercialize a Decision Support Framework (DSF) for
Scholarship
Distributed Collaborative Design and Manufacture (DCDM), where
• Emphasis is placed on development of theory, creation of domain independent
decision support refers to the cumulative means of modeling, structuring,
constructs for characterizing and modeling decisions, and formalization of
and negotiation solutions to decisions and any of their interactions.
interactions among distributed design agents via digital interfaces
• Provide a consistent mechanism for supporting designers in their
• Development of logic for design process reconfiguration and investigation of
capacity as decision-makers. The fundamental goals are to (1) manage
strategic decision-making/resource allocation
the design process, (2) facilitate the collaboration of stakeholders, and (3) Industry
effectively share information.
• Facilitation of strategic decision-making from a systems perspective and
• Effectively structure design processes and properly reflect decision
enhancement of design process reconfiguration with regard to flexibility,
critical information and any dependencies.
efficiency, and effectiveness.
• Enablement of companies to trace errors to their origins within a given design
Background
chain and allow for remediation through dynamic design modification and/or
• This research will expand upon a substantial knowledge base in
process reconfiguration
Decision Based Design, design theory, and decision theory that has
The Role of Decisions throughout
The Strategic Reduction of Design Freedom through Decisions…
evolved in the Systems Realization Laboratory (SRL) since its
the Design Process…
establishment in 1992.
STRUCTURAL
ENGINEERING
h

ECONOMICS
Ledger
Ledger
Resource
Resource $$
Activity $
Activity $
Total
Total $$
ELECTRICAL
ENGINEERING
R
THERMAL
ENGINEERING
w
+
-
i
V
T1 Q T2
L
C
k
Resources, Status, Publications, etc.
Designer #1
Designer #2
Designer #3 Designer #4
Fundamental Assertions
• 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.
Resources
• SRL Knowledge Base
• X-DPR, iSIGHT, Web Board, Concurrent Versioning System (CVS)
Status
• Completion of MS Research, Development of Decision Constructs and
Information Model required for DSF
• Active consideration/infusion of Risk and Uncertainty into decision-making
Publications
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.
Digital Clay for Shape Input and Display
15 Students
Faculty:
Wayne Book, Mark Allen, Imme Ebert-Uphoff,
Ari Glezer, David Rosen, Jarek Rossignac
Objectives
 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.
Background
 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.
Contributions & Benefits
 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.
Supported by 5 year NSF grant.
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 ShapeGenerating Mechanisms,” IEEE Robotics and Automation Conference, 2003.
 Rosen, D.W., Nguyen, A., and Wang, H., “On the Geometry of Low Degree-ofFreedom 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.
Constrained Objects: A Knowledge Representation
for Design, Analysis, and Systems Engineering Interoperability
Students: Manas Bajaj, Injoong Kim, Greg Mocko
Faculty: Russell Peak
Chip Package Stress
Analysis Template
Objectives
Contributions & Benefits
 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
To 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
Constrained Object (COB) Formulations
Approach & Status
Collaboration Needed
Approach
 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)

Constraint Schematic-S
 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 Interoperability
http://eislab.gatech.edu/pubs/conferences/2003-asme-detc-cie-peak/

Support for 1-3 students
depending on project scope
Sponsor involvement to
provide domain knowledge
and facilitate pilot usage
Subsystem-S
COB Structure
Definition Language
(COS)
I/O Table-S
Object Relationship Diagram-S
Constraint Graph-S
XML UML
Express-G
STEP
Express
COB-based Airframe Analysis Template
CAD-CAE Associativity
(idealization usage)
lugs
diagonal brace lug joint
analysis context
L [ j:1,n ]
j = top
hole
lugj
product structure (lug joint)
Geometry
2
size,n
deformation model
diameters
L [ k] k = norm
Dk
normal diameter, Dnorm
oversize diameter, Dover
mode (ultimate static strength)
thickness, t
0.35 in
edge margin, e
0.7500 in
material
Plug joint
condition
e
W
max allowable ultimate stress, FtuL
Plu g jo in t
Plug
67 Ksi
Boundary Condition Objects
Margin of Safety
(> case)
(links to other analyses)
actual
Requirements
0.7433
Paxu
14.686 K
W
 1) DtFtuax
D
Solution Tool
Interaction
estimated axial ultimate strength
allowable
MS
Kaxu
F tuax
Paxu  Kaxu (
4.317 K
n
8.633 K
objective
DM 6630
t
Material Models
7050-T7452, MS 7-214
r1
D
0.7500 in
effective width, W 1.6000 in
Max. torque brake setting
detent 30, 2=3.5º
Lug Axial Ultimate
Strength Model
Model-based Documentation
2.40
Program
L29 -300
Part
Outboard TE Flap, Support No 2;
Inboard Beam, 123L4567
Feature
Diagonal Brace Lug Joint
Template Lug Joint
Axial Ultimate Strength Model
Dataset
j = top lug
k = normal diameter
(1 of 4)
Composable Simulations: Model Archiving and Reuse for Systems Design
Students: Rich Malak, Tarun Rathnam, Steve Rekuc
Faculty: Chris Paredis
Objectives
Contributions & Benefits
 Develop integrated representations for multi-disciplinary products
and their corresponding behavioral models
To 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 reuse
To Industry
 Faster and broader exploration of design space
 Capture history of design exploration and analyses
 Save resources by reusing validated simulation 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
Approach & Status
Collaboration Needed
Approach
 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.

Support for 1-2 students
depending on scope of study

Engineering support to
provide application domain
knowledge for example
study.
Additional Info
C.J.J. Paredis, A. Diaz-Calderon, R. Sinha, and P.K.
Khosla, "Composable Models for Simulation-Based
Design", Engineering with Computers. Vol. 17, pp. 112128, 2001.
(http://www.cs.cmu.edu/~paredis/pubs/EWC01.pdf)
http://srl.marc.gatech.edu/people/paredis/
COINSIDE framework:
Composition in Simulation and Design
Composition of port-based objects
allows for automatic composition of the
corresponding simulation and
CAD models
Supply Chain Design and Analysis Testbed
Students: Jin-Young Choi, Nan Li
Faculty: Leon McGinnis
Objectives
Contributions & Benefits
 Develop distributed simulation testbed for analyzing global supply
chains, including factories, warehouses, transportation
To 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
 Use the distributed simulation testbed to investigate alternative
designs, planning methods, and supply chain management
methods
Approach & Status
Collaboration Needed
Approach
 Use HLA to support distributed simulation, using
legacy models where necessary
 Develop general purpose simulation models for
warehouses and transportation
 Develop supply chain manager models
Status
 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

Demonstration case study

Development and evaluation of specific supply chain planning
and/or management methods

Integrating existing legacy models to permit supply chain analysis
Additional Info
This project has been conducted in collaboration with
SimTech, the Singapore Institute for Manufacturing Technology
School of Industrial and Sy stems Engineering
Georgia Institute of Technology
Atlanta, GA 30332-0205
http://factory .isy e.gatech.edu
High Fidelity Factory Modeling
Students: 5 PhD students
Faculty: L. McGinnis, C. Zhou, S. Reveliotis
Objectives
Contributions
 Develop a new generation of factory modeling tools that:
To 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
 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
Approach & Status
Collaboration Needed
Approach
 Object oriented
 Separation of process and control
 Explicit material handling
 Java, HLA
Status
 Third generation toolkit
 Currently testing against Sematech 300mm model

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
Additional Info
http://factory.isye.gatech.edu/vfl/research/hifive.php
For interim status report, presentations, and demonstrations
School of Industrial and Sy stems Engineering
Georgia Institute of Technology
Atlanta, GA 30332-0205
http://factory .isy e.gatech.edu
GIT Contacts & Departments
Unit
Dept.
Admin
-
OIP
First Name
Last Name Titles
Charles
Liotta
Vice Provost for Research and
Dean of Graduate Studies
MARC Dr.
Steve
Danyluk
OIP
OIP
MARC Mr.
MARC Dr.
Andy
Russell
Dugenske
Peak
MARC Director, Prof. and
Bryan Chair in ME
Senior Researcher
Senior Researcher
CoA
-
Dr.
Chuck
Eastman
Director, PhD Program and
Professor
CoC
GVU
Dr.
Jarek
Rossignac
Professor
CoE
CoE
CoE
ECS
ECS
Dr.
Mr.
Ms.
Narl
Tord
Sandra
Davidson
Dennis
Pierotti
Associate Dean
Research Engineer I
Manager, ECS
CoE
CoE
CoE
AE
AE
AE
Mr.
Dr.
Dr.
Pete
Dimitri
Dan
Hart
Mavris
Schrage
Research Engineer I
Professor
Professor
CoE
ISyE
Dr.
Leon
McGinnis
Professor
CoE
CoE
CoE
CoE
CoE
ME
ME
ME
ME
ME
Dr.
Dr.
Dr.
Dr.
Dr.
Bob
Farrokh
Chris
Dave
Suresh
Fulton
Mistree
Paredis
Rosen
Sitaraman
Professor
Professor
Assistant Professor
Professor
Associate Professor
CoM
-
Dr.
Naresh
Malhotra
Regents Professor
Dr.
Abbreviations
AE
School of Aerospace Engineering
CoA
College of Architecture
CoC
College of Computing
CoM
College of Management
CoE
College of Engineering
CEE
School of Civil and Environmental Engineering
ECE
School of Electrical and Computing Engineering
ECS
Engineering Computing Services (campus CAx services - under GIT CoE)
ISyE
School of Industrial and Systems Engineering
MARC
Manufacturing Research Center
ME
School of Mechanical Engineering (includes Nuclear and Health Physics)
OIP
Office of Interdisciplinary Programs
PTFE
School of Polymer, Textile & Fiber Engineering
ASDL
CBAR
EIS Lab
FIS Group
MISL
PLMCC
PLM CoE
RPMI
SRL
Aerospace Systems Design Lab
Center for Board Assembly Research
Engineering Information Systems Lab
Factory Information Systems Group
MARC Information Systems Lab
Product Lifecycle Management Center of Competence
Product Lifecycle Management Center of Excellence
Rapid Prototyping & Manufacturing Institute
Systems Realization Lab
GIT Organization Charts
http://www.provost.gatech.edu/flowchart.html
Be aware that CoE has two meanings above: Center of Excellence and College of Engineering
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