GIT PLM-related Activities by xiuliliaofz


									              February 5, 2004

Research Topics & Initial Mapping
PLM Focus Areas  GIT Activities
          PLM Center of Excellence
      Georgia Institute of Technology

            Document Contacts:

               Sample GIT PLM-Related Activities
                                                                                    ME: Paredis
                                              Composable                                                 Design-Analysis
                                              Simulations                                                  Integration
 ME: Mistree
                                                                                                  MARC: Peak
  Strategic                           Standards for
                                                                                                                              Lean Principles
   Design                          Systems Engineering                                                                                                      IE: McGinnis
                                                                                                                                                             Virtual Factories
Mgt: Malhotra
                   Market            Portfolio                 Concept                              Production       Sales &      Maintenance
  AE: Mavris     Planning            Planning                Development
                                                                                                     & Testing     Distribution                       PLM
                                                                                                                                   & Support                   AE: Schrage
Robust Design
 Simulation                                                                                                                                                       Aircraft
                                        Marketing/Sales                         Design             Manufacturing       Services                                  Lifecycle
                                         Collaboration                        Collaboration        Collaboration     Collaboration
Product Family                                                                                                                                                   Support


                                    Customer                                                                                         Customer
                                   Requirements                           PLM Collaborative Foundation                               Feedback                     Factory
                                                                                     B2B integration                                                              Systems
                                                      Design                             Component                 Design Change
CoC: Rossignac                                       Definition                          Management                 Management                               MARC: Dugenske

Collaborative                                       Partners                          Other Enterprise               Suppliers                                Change Mgt. in
Visualization                                                                            Locations                                                            Product Model
Environments                                                                                                                                                   Databases
                 Source: IBM PLM definition slide at PDES Inc. Board Mtg. 2003-11

 Engineering                                                                                                                                                 Arch: Eastman
 Knowledge                       Collaborative Design                               Design-Supply Chain                             Design
Representation                       Optimization                                    Process Integration                          Repositories
                                                                                                                                                             ME: Fulton
         PLM Focus Areas
Addressing Top Industry Pain Points

           Source: IBM slides at PDES Inc. Board Mtg. 2003-11
Mapping PLM Focus Areas  GIT Activities - p1
                                                (and related faculty)
  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)
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)
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
     Integrating design chain processes with supply chain processes
     Standards-based engineering frameworks (Peak)

   Quad Charts for
Sample Research Topics
       PLM Center of Excellence
   Georgia Institute of Technology

Next-Gen. PLM with Fine-Grained Interoperability
                                                                                                                  Customer Needs /
                           Abstraction Level

                                                                                                        …        Systems Engineering


                                                                                                                    Model interfaces:
                                                                                                                    Associativities among
                                                                                                                    domain-specific models
                                                                                                                    & system-level models

                                                                                                                    Fine-grained models:
     Development Process


                                                                                                                       Information objects
                                                                                                                       Parametric relations

                                                                                         Human Interaction




                                                                                                                         After Bajaj, Peak, & Waterbury
                                                Models of varied abstractions and domains                                                      2003-09    8
                                                     Hierarchic Market Space Definition and Exploration
                                                 Student: Christopher Williams                                          Faculty: Farrokh Mistree, Janet K. Allen
Objectives                                                                                                              Contributions & Benefits
 • To develop formal, mathematically correct, and rigorous principles for               Scholarship
    designing product architectures that facilitate the production of customized          Sequencing modes of managing product variety
    products.                                                                             • How can a designer synthesize multiple modes of managing product variety in
 • Determine an optimal arrangement of product variety techniques that link all             order to realize a customized product?
    points in the market space in order to satisfy any customer demand so that            • How does the designer select which mode to use first? What sequence will
    cost is minimized.            T                  Th                  V     s
                                                                                            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?
                                                             30 P
                                                                                          • Can this question be answered without using varying sized constructs?
P [MPa]                                     L                                             • Will this affect the sequencing of the modes of managing product variety?
                                                     P [MPa] 20                      P                             2
                                                                                          • Provision of manufacturing firms an efficient (through rigorous and systematic
                                                             10                             methodology) foundation for realizing customized products, thus enhancing the
                                                                                            responsiveness of manufacturing organizations to changes in the market or
              10         30                                        10          20 30

                  V [m3]                                                   V [m ]           demands for customization.

Background                                                                                                              Resources, Status, Publications, etc.
                             Constructal Theory                                                                          Resources
• The hierarchic structures (tree networks) that we observe in natural and                                                • SRL Knowledge Base
  artificial systems are the “fingerprint” of the minimization of flow                                                    • X-DPR, iSIGHT, Matlab, Concurrent Versioning System (CVS)
  resistance between a finite volume and one point.                                                                      Status
                                                                                                                          • Nearing completion of MS Research
                                                                                                                          • Adaptation to the development of a process family
                                                                                                                          • Consideration of non-uniform demand, risk and uncertainty
                                                                                                                          Williams, C. B., Panchal, J., Rosen, D. W., 2003, “A General Decision-Making Method for the Rapid
• An access problem can be solved through the optimization of the shape of                                                 Manufacturing of Customized Parts,” accepted by the 23rd Conference on Computers and
  the smallest, inner-most space elements and the hierarchic assembly of                                                   Information in Engineering, ASME, September 2-6, Chicago, Illinois.
  these elements into larger “constructs” until covering the entire geometric
                                                                                                                          Carone, M. J., Williams, C.B., Allen, J. K., and Mistree, F., 2003, “An Application of Constructal
  space.                                                                                                                   Theory in the Multi-Objective Design of Product Platforms,” accepted by the 15th International
• The abstraction of a space of customization as a geometric space in need of                                              Conference on Design Theory and Methodology, ASME, September 2-6, Chicago, Illinois.
  access optimization, allows a designer to effectively develop a product                                                 Hernandez, G., Williams, C. B., Allen, J.K., Mistree, F., “Design of Platforms for Customizable
  architecture for customized products.               S3   S4              S5                 S6
                                                                                                                           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
           The Smallest Area, S1                                                                                           Products,” ASME Design Automation Conference, Montreal, Canada, DETC2002/DAC-34095.
                    S1              .   P(x,y)

      H1   E


                                                                                                                          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,
                                                                Time, Complexity, Evolution                                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:       • Effective tools for creating representations of n-dimensional market spaces and
        •Changes in market trends                                          design capabilities
        •Changes in the capabilities of existing technologies            • Systematic approaches for designing families of products that can evolve and
        •New or evolving technologies                                      accommodate change and innovation and a systematic tool for choosing
• To develop a number of new techniques that would be parts of a           between multiple available approaches
  strategic design method, including:                                    • Methods for forecasting and characterizing the impact of innovation on a
        •N-dimensional market visualization techniques                     feasible space in a manner meaningful to the design process
        •Innovation modeling and early technology impact forecasting     Industry
                                                                         • Computing, information, and decision frameworks for coordinating distributed
                                                                           decision makers carrying out strategic design
• To develop a plan for coordinating the many disparate methods that
                                                                         • Methods for linking market and design capability forecasts to design decisions
  would make up strategic design as well as a logic for choosing           and plans for product portfolios
  between different modes of managing product variety

Background                                                               Tasks
Strategic Design is a comprehensive approach for designing products      • Strategic product planning techniques for forecasting dynamic requirements and
and processes that efficiently and effectively accommodate…                technological capabilities and for assessing the potential impact of innovation on
•changing markets and associated customer requirements                     complex products and processes.
•technological innovations                                               • Product variety design techniques for leveraging and adapting existing products.
                                                                         • Decision support techniques that are formal, rigorous, and flexible, and account for
                         … In a collaborative, distributed environment     uncertainty
                                  Expanded Technology                    • Coordination mechanisms for multiple agents in product development activities
                                                                         • Flexible computing and information infrastructures for effective distributed design
     Property B

                               x                                         • One student.

                                                    Available            • Seepersad, C. C., F. S. Cowan, M. K. Chamberlain and F. Mistree, 2002,
                                                   Technology              "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
                                     Property A                            Technology, Atlanta, GA.
            Future Technology
                        Design Process, Information, and Knowledge Management in
                                     Distributed, Collaborative Design
                         Student: Jitesh H. Panchal     Faculty: Farrokh Mistree, Janet K. Allen
Objectives                                              Contributions & Benefits
Development of                                           • Means for improvement of design processes
• A method for Integrated Design of Products             • Systematic method for configuring design chains
and Design Processes                                     • Design knowledge reuse in an organization
• Computational model of design processes in             • Tools for modeling and reconfiguring design
the form of a design equation                            processes
• Quantitative metrics for openness of products          • A new dimension to the design information
and processes                                            management and reuse
• Method for synthesizing design processes
• Application to design of materials

Background                                              Collaboration Needed

  Design Equation: K = T (I)                              2 PhD Students
                                                          Student 1: Development of method for Integrated Design of
  Decision Based Design                                   Products and Design Processes
                                                          Student 2: Application of the method to design of materials
  Decision Support Problem (DSP) Technique              References
                                                      [1] B. A. Bras, "Designing Design Processes for Decision-Based
       Process Detail

                                                      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.
                            Scope                     Jersey City, New Jersey, 1990, pp. 565-597.
  Design process at various levels                    [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      Faculty : Farrokh Mistree and Janet K. Allen
Objectives                                                                            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.
Background                                                                            • Enablement of companies to trace errors to their origins within a given design
 • This research will expand upon a substantial knowledge base in                        chain and allow for remediation through dynamic design modification and/or
   Decision Based Design, design theory, and decision theory that has                    process reconfiguration
   evolved in the Systems Realization Laboratory (SRL) since its                              The Role of Decisions throughout   The Strategic Reduction of Design Freedom through Decisions…
                                                                                                   the Design Process…
   establishment in 1992.
                     STRUCTURAL                                    ELECTRICAL
                     ENGINEERING                                  ENGINEERING
                           h                                               R
                                              THERMAL
 ECONOMICS                                   ENGINEERING          +
                                                                  -    i
                           w                                  V
       Ledger                                                                  L
      Resource $$
      Activity $$
       Activity                               T1 Q T2                      C
      Total     $
       Total     $

                                                                                      Resources, Status, Publications, etc.
             Designer #1       Designer #2   Designer #3 Designer #4
                                                                                      • SRL Knowledge Base
Fundamental Assertions                                                                • X-DPR, iSIGHT, Web Board, Concurrent Versioning System (CVS)
 • It is the nature and types of decisions, implemented that determine the
                                                                                      • Completion of MS Research, Development of Decision Constructs and
   progress of a design
                                                                                        Information Model required for DSF
 • Decisions in all stages of engineering design depend on scientific,
                                                                                      • Active consideration/infusion of Risk and Uncertainty into decision-making
   factual information as well as empirical, experience-based knowledge,
   designer preferences, and uncertainty.                                             Fernández, M.G., D.W. Rosen, J.K. Allen, and F. Mistree (2002). “A Decision
 • There is a need to propagate decision-critical, up-to-date information             Support Framework for Distributed Collaborative Design and Manufacture”. 9th
   alongside design knowledge for both sequential and concurrent design               AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta,
   tasks, particularly for dependent and interdependent decisions that                GA, AIAA-4881.
   cannot be made in isolation.                                                       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                                                                   Contributions & Benefits
  Develop an interactive, 3-D haptic computer input/output device.                 Define state-of-the-art in haptics (force-based) computer interaction.
   Specifically, the device will enable:                                            Greatly impact distributed collaboration when shape must be
         • Shape input through a “sculpting” interaction mode                        communicated.
         • Shape display of a computer model (e.g. CAD model)                       Potentially, impact the ability for visually impaired people to interact
         • Stiffness (“feel”) display of shapes with various material
                                                                                     with computers.
            properties.                                                             Significantly impact technology in hydraulics, controls, kinematics,
  Demonstrate the digital clay device on a variety of mechanical and                manufacturing, and human-computer interface areas.
   architectural shape design applications, distributed collaboration,
                                                                             Supported by 5 year NSF grant.
   and dynamic simulations.

Background                                                                   Collaboration Needed
  Hydraulics will be used for actuation and sensing.                           1 student to develop digital clay prototypes and test them in
  A formable skin will comprises the bulk and shape of the “clay”               mechanical design applications.
   device. The skin will have inflatable bladders to enable the skin to         Materials and supplies to construct digital clay prototypes.
   change shape and to sense user forces.
  Stereolithography used to fabricate skin and clay structure.              References
  MEMS technologies will be utilized to fabricate array of pressure         Bosscher, P. and Ebert-Uphoff, I., “Digital Clay: Architecture Designs for Shape-
   sensors and valves in device backplane.                                    Generating Mechanisms,” IEEE Robotics and Automation Conference, 2003.
  Human-computer interface studies will determine appropriate               Rosen, D.W., Nguyen, A., and Wang, H., “On the Geometry of Low Degree-of-
   methods of interaction with clay devices.                                  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.
                  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
Objectives                                                                    Contributions & Benefits                                                                                Analysis Template
 Develop better methods of capturing engineering knowledge that :            To Scholarship
         Are independent of vendor-specific CAD/CAE/SE tools                  Develop richer understanding of modeling
         Support both easy-to-use human-sensible views and                     (including idealizations and multiple levels of
          robust computer-sensible formulations in a unified manner             abstraction) and representation methods
         Handle a diversity of product domains, simulation disciplines,      To Industry
          solution methods, and leverage disparate vendor tools                Better designs via increased analysis intensity
 Apply these capabilities in a variety of sponsor-relevant test scenarios:    Increased automation and model consistency
         Proposed candidates are templates and custom capabilities            Increased modularity and reusability
          for design, analysis, and systems engineering                        Increased corporate memory
                                                                                via better knowledge capture                  Constrained Object (COB) Formulations
                                                                                                                                                                                Constraint Schematic-S                                                           Subsystem-S
                                                                                                                                                                                                                   COB Structure
Approach & Status                                                             Collaboration Needed                                                                                                               Definition Language

Approach                                                                            Support for 1-3 students
                                                                                                                                                                                                                                                                   I/O Table-S
     Extend and apply the constrained object (COB) representation                   depending on project scope
      and related methodology based on positive results to date                     Sponsor involvement to                                                               Object Relationship Diagram-S

     Expand within international efforts like the OMG UML for                       provide domain knowledge
                                                                                                                                                                                                                           XML UML
                                                                                                                                                                                                                                                         Constraint Graph-S

      Systems Engineering work to broaden applicability and impact                   and facilitate pilot usage                                                             Express-G
                                                                              COB-based Airframe Analysis Template
     Current generation capabilities have been successfully
                                                                                                                                      CAD-CAE Associativity                                                                                        deformation model
      demonstrated in diverse environments (circuit boards, electronic                                                                lugs           (idealization usage)                                          diameters
                                                                                                                                                                                                                                                   Lug Axial Ultimate
                                                                                                                                                                                                                        L [ k] k = norm
      chip packages, airframes) with sponsors including NASA,                 analysis context
                                                                                                   diagonal brace lug joint
                                                                                                 product structure (lug joint)
                                                                                                                                  L [ j:1,n ]                   j = top
                                                                                                                                                                 lugj       hole
                                                                                                                                                                                              normal diameter, Dnorm             Dk                 Strength Model
                                                                                                                                                                                              oversize diameter, D over
      Rockwell Collins, Shinko (a major supplier to Intel), and Boeing.                                                                                                                                                             0.7500 in
                                                                                                                                                                                                                                                                   DM 6630
                                                                                                                                                          2                Geometry
     Templates for chip package thermal analysis are in production                                                                                  size,n                                   thickness, t            0.35 in
                                                                                                                                                                                              edge margin, e          0.7500 in                                                   0.7433
                                                                                          mode (ultimate static strength)                                                                                                                           e                   Kaxu
      usage at Shinko with over 75% reduction in modeling effort                                                                                                                              effective width, W 1.6000 in
                                                                                                                                                                                                                                                    W                   Paxu      14.686 K
      (deformation/stress templates are soon to follow)                                     Max. torque brake setting
                                                                                                                                7050-T7452, MS 7-214
                                                                                                                                                                           Material Models
                                                                                                                                                                                              max allowable ultimate stress, FtuL
                                                                                            detent 30, 2=3.5º                                                                                                                                      F tuax
                                                                                                                         Plug joint                            Plug                           67 Ksi                                                             W
                                                                                          condition                                     Plug joint                                                                                              Paxu  K axu (      1) DtFtuax
 Additional Information:                                                                                                                    n
                                                                                                                                                                      4.317 K                                                                                    D

                                                                                                        objective          8.633 K

1.                                                                 Margin of Safety                                                    Boundary Condition Objects                                        Solution Tool
2. Response to OMG UML for Systems Engineering RFI:
                                                                                                         (> case)
                                                                                                                                                                                   (links to other analyses)                                 Interaction
                                                                                                                                                                                                                                    estimated axial ultimate strength                                                                 allowable

                                                                                                                                                              Model-based Documentation
                                                                                                                    MS       2.40
3. Characterizing Fine-Grained Associativity Gaps:
  A Preliminary Study of CAD-E Model Interoperability                                                                    Program       L29 -300
                                                                                                                                                                                    Template Lug Joint
                                                                                     Requirements                                      Outboard TE Flap, Support No 2;
                                                                                                                                                                                             Axial Ultimate Strength Model                                                     Part
                                                                                                                                       Inboard Beam, 123L4567
                                                                                                                                                                                    Dataset     j = top lug
                                                                                                                                       Diagonal Brace Lug Joint                                 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   To Scholarship
  and their corresponding behavioral models                             Develop understanding of the relationship between configuration of
 Develop algorithms for reusing and composing simulation models of      components and configuration of simulation models
  individual components into models for entire systems                  Create ontology for ports (locations of intended interaction) and artifacts
 Characterize the validity and accuracy of simulation models at        Develop understanding of validity and accuracy of models to enable reuse
  multiple levels of abstraction                                       To Industry
                                                                        Faster and broader exploration of design space
 Support the seamless transition between models at multiple levels
  of abstraction while progressing through the design process           Capture history of design exploration and analyses
                                                                        Save resources by reusing validated simulation models

Approach & Status                                                      Collaboration Needed
Approach                                                                  Support for 1-2 students
 Semantically rich product representations in OWL (Web                    depending on scope of study
  Ontology Language); combined with object-oriented
  simulation models in Modelica                                           Engineering support to
                                                                           provide application domain
 Define and populate a repository of components and                       knowledge for example
  models to demonstrate reuse and composition                              study.
 Investigate the compatibility, composability, and accuracy
  of models and model configurations.
 We have demonstrated the concept of composable
  simulations for satellite systems (with Lockheed-Martin)
  and for transportation systems (with Bombardier).
                                                                                                                          COINSIDE framework:
 We have implemented an initial software prototype,                                                       Composition in Simulation and Design
  COINSIDE: Composition in Simulation and Design.

Additional Info
                                                                                                          Composition of port-based objects
 C.J.J. Paredis, A. Diaz-Calderon, R. Sinha, and P.K.
 Khosla, "Composable Models for Simulation-Based                                                          allows for automatic composition of the
 Design", Engineering with Computers. Vol. 17, pp. 112-                                                   corresponding simulation and
 128, 2001.                                                                                               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   To Scholarship
  chains, including factories, warehouses, transportation                    Testbed for evaluating proposed supply chain planning/management
 Use the distributed simulation testbed to investigate alternative           methods
  designs, planning methods, and supply chain management               To Industry
  methods                                                                    Tools that permit collaboration between supply chain partners to
                                                                              analyze/design the supply chain without revealing proprietary data

Approach & Status                                                      Collaboration Needed
Approach                                                                  Demonstration case study
     Use HLA to support distributed simulation, using
      legacy models where necessary                                       Development and evaluation of specific supply chain planning
                                                                           and/or management methods
     Develop general purpose simulation models for
      warehouses and transportation                                       Integrating existing legacy models to permit supply chain analysis
     Develop supply chain manager models
     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

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
                                                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
         Support high fidelity description of factory resources and           Comprehensive reference model for semiconductor fabrication
        operations                                                              operations
                                                                               Testbed for exploring alternative factory designs, alternative scheduling
         Are based on concepts that map one-to-one with factory                and control methods
                                                                         To Industry
         Enable abstraction to support more aggregate models and              Testbed for evaluating proposed factory designs or factory planning and
        analyses                                                                control strategies
 Demonstrate new tools in semiconductor wafer fabs

Approach & Status                                                        Collaboration Needed
Approach                                                                    Demonstration case studies of specific fabs
     Object oriented
                                                                            Evaluation of through-stocker versus point-to-point AMHS
     Separation of process and control
     Explicit material handling                                            Linking factory operations models with “real” factory control
                                                                             software to create a “virtual” factory
     Java, HLA
     Third generation toolkit
     Currently testing against Sematech 300mm model

Additional Info
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
                             GIT Contacts & Departments

Unit    Dept.         First Name   Last Name Titles                            Abbreviations
                                                                               AE        School of Aerospace Engineering
Admin   -       Dr.   Charles      Liotta      Vice Provost for Research and   CoA       College of Architecture
                                               Dean of Graduate Studies        CoC       College of Computing
                                                                               CoM       College of Management
OIP     MARC Dr.      Steve        Danyluk     MARC Director, Prof. and        CoE       College of Engineering
                                                                               CEE       School of Civil and Environmental Engineering
                                               Bryan Chair in ME
                                                                               ECE       School of Electrical and Computing Engineering
OIP     MARC Mr.      Andy         Dugenske    Senior Researcher
                                                                               ECS       Engineering Computing Services (campus CAx services - under GIT CoE)
OIP     MARC Dr.      Russell      Peak        Senior Researcher
                                                                               ISyE      School of Industrial and Systems Engineering
                                                                               MARC      Manufacturing Research Center
CoA     -       Dr.   Chuck        Eastman     Director, PhD Program and       ME        School of Mechanical Engineering (includes Nuclear and Health Physics)
                                               Professor                       OIP       Office of Interdisciplinary Programs
                                                                               PTFE      School of Polymer, Textile & Fiber Engineering
CoC     GVU     Dr.   Jarek        Rossignac   Professor
                                                                               ASDL        Aerospace Systems Design Lab
CoE     -       Dr.   Narl         Davidson    Associate Dean                  CBAR        Center for Board Assembly Research
CoE     ECS     Mr.   Tord         Dennis      Research Engineer I             EIS Lab     Engineering Information Systems Lab
CoE     ECS     Ms.   Sandra       Pierotti    Manager, ECS                    FIS Group   Factory Information Systems Group
                                                                               MISL        MARC Information Systems Lab
CoE     AE      Mr.   Pete         Hart        Research Engineer I             PLMCC       Product Lifecycle Management Center of Competence
CoE     AE      Dr.   Dimitri      Mavris      Professor                       PLM CoE     Product Lifecycle Management Center of Excellence
CoE     AE      Dr.   Dan          Schrage     Professor                       RPMI        Rapid Prototyping & Manufacturing Institute
                                                                               SRL         Systems Realization Lab
CoE     ISyE    Dr.   Leon         McGinnis    Professor
                                                                               GIT Organization Charts
CoE     ME      Dr.   Bob          Fulton      Professor
CoE     ME      Dr.   Farrokh      Mistree     Professor
CoE     ME      Dr.   Chris        Paredis     Assistant Professor
CoE     ME      Dr.   Dave         Rosen       Professor                       Be aware that CoE has two meanings above: Center of Excellence and College of Engineering
CoE     ME      Dr.   Suresh       Sitaraman   Associate Professor

CoM     -       Dr.   Naresh       Malhotra    Regents Professor


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