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Agent-Based Joint Theater Logistics Management

Agent-Based Joint Theater Logistics Management. Dr. Thomas E. Potok Collaborative Technologies Research Center Computer Science and Mathematics Division Oak Ridge National Laboratory Lockheed Martin Energy Research. Collaborative Technologies Research Center (CTRC).

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Agent-Based Joint Theater Logistics Management

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  1. Agent-Based Joint Theater Logistics Management Dr. Thomas E. Potok Collaborative Technologies Research Center Computer Science and Mathematics Division Oak Ridge National Laboratory Lockheed Martin Energy Research

  2. Collaborative Technologies Research Center (CTRC) • Computer Science and Mathematics Division • Pioneering research in • Agent technology • Information integration • Cluster analysis • Software engineering • We have successfully developed systems for Lockheed Martin, the Department of Energy, and the Defense Logistics Agency. • Approach • Small Entrepreneurial team of researchers and software developers • Broad range of collaborators, including • LM, DLA, DOE, University of Tenn, NIST, CMU, NCSU, NTRC

  3. CTRC Key Projects • SURGE - Supplier Utilization through Responsive Grouped Enterprises • DLA funded to drastically reduce cost/delivery time for military spares • Software agents and grouping technology used to define part families • MABES - Manufacturing Agent Based Emulation System • LMTAS to rapidly model fundamental changes to manufacturing systems • Software agents to analyze the impact of changes to manufacturing lines • CME - Collaborative Management Environment • DOE funded to provide significant improvement in research funding • Information integration used to gather, search over, and report on heterogeneous information from a number of national laboratories

  4. Future Technology Trend AGENTS Internet Telephone Face to Face

  5. Successful Projects Supply Chain Management Agent System • We have extensive expertise in agent development • Began working with agent technologies in 1980s Manufacturing Emulation Agent System Collaborative Decision Support System Neural Nets for Recovery Boiler Control Neural Nets for Bankruptcy Prediction Neural Nets for Spring-back Prediction Collaborative Design System Neural Nets for Resistance. Spot Welding Neural Nets for Material Mix Optimization Genetic Algorithms for Chemical Synthesis • Over 10 successful projects within the last 5 years • Collaborations with leading agent experts Knowledge-based Systems - Manufacturing Advisors Knowledge-based Systems for Constructability Design and Analysis of Computer Experiments Knowledge-based Computer Systems Calibration 1985 1990 1995 2000

  6. Recent Accomplishments • Guest researcher at NIST for standardization of agent frameworks • Delivered a multi-agent part grouping system for DLA • Press Release: Lockheed Martin Completes First Phase in Applying 'Agent-Based' Software to JSF • Papers and Presentations • Invited presentation to MIT’s Lean Aerospace Initiative Forum • An invited paper to the IEEE Internet Computing Journal • Presented two multi-agent papers at the ISAS'99 conference • Paper accepted by International Journal of Flexible Automation and Integrated Manufacturing. • Paper accepted by Flexible Automation and Intelligent Manufacturing Conference

  7. What are Agents? ...Software entities that assist people and act on their behalf ...Software “robots” Proactive detect changes in their environment and react to those in a timely manner by answering to events and initiating actions Traditional Software Object Goal-driven have a purpose and act in accordance with that purpose until it is fulfilled Behavior State Agent Technology Communicative able to interact and communicate with users and other agents Autonomous can have control over their own actions and be able to work and launch actions independent of the user or other actors Learning have the ability to learn from experiences in their environment

  8. Simple Agent Example Agent, find me the book “War and Peace,” and I need it tomorrow Amazon 2 Days $18.50 Barnes and Nobel 1 Day $21.75 Borders NA ... Does the agent understand buying books? Form a plan to buy the book Execute the plan Order the book B. Dalton 1 Day $20.25 Learn for next time

  9. WEB BASED What’s Going? DLA/Services What’s Coming? PREPO Forces Commercial ANY THEATER TRANSCOM JFC/JTF “DAFL” Strategic Pipeline AIRLIFT SEALIFT Prepositioned Capabilities CINCs Oak Ridge Technology • SURGE • Optimize Logistics • Minimize wait time • MABES • Total Asset Visibility • Supply Chain Model • CME • Integrated, • Collaborative, • Distributed Information

  10. SURGE

  11. How is it made? What can the supplier build? When and how much is needed? Supply Chain Overview History Future Demand Part Optimal Part Family Optimal Supplier Smooth Demand Supplier Capability

  12. SURGE Grouping Agents Part Families Agent Group Themselves Agent Mediator Parts represented by Agents

  13. Results on C-130 Parts Input Data Grouping Results Group 1 Group 5 Group 2 Group 4 Group 3

  14. C130 Grouping Results Why two groups? Common Processes Group “3” Processes Group “5” Processes Why are extrusions spread over two groups?

  15. Results Cell 1 Group 2 Group 1 Group 2 Group 3 Cell 2 Group 1 Group 3 Cell 3 Wire Harness Data forms 3 groups Possible cell layout

  16. Forecasting Direction Part family with key supplier Traditional low bid part Large Variance Small Variance Higher Volumes, Reduced Inventory Potential for large savings

  17. Neural Network Forecasting Partial Training Set Forecast Full Training Set

  18. SURGE Summary • An advanced logistics optimization system • Significant research breakthroughs in clustering technology • Provides significant savings and lead-time reductions to DLA

  19. MABES

  20. Process Overview Projected or Actual Parts Need Group Parts Form Lean Cells Optimize Cells

  21. Cell Optimization Traditional Methods Consume Time and Effort Experts Management Technology Foreman Information Weeks or Months

  22. Value of Agent Systems Fast Flexible Collaborative Experts Management Agent System Technology Foreman Minutes

  23. MABES: Analytic Model Manufacturing Rules Minimization Throughput At 17 Planes Per month: - Machine utilization 85% - Cost is $65M - Span time is 48 Days Activity Metrics Process Metrics

  24. MABES: Dynamic Model Queues and Task Centers • Identify • Bottlenecks • Network Sensitivity • Outages Pull/Push/Takt Animation

  25. Visibility into the Supply Chain Supply Chain Manufacturing Operations Theater Operations PARTNER SUPPLIER SUPPLIER SISTER DIVISION 3rd TIER SUPPLIER 2nd TIER SUPPLIER PARTNER FABRICATION -SUBASSEMBLY - FINAL - DELIVERY 1st TIERSUPPLIER How does a problem here affect operations here

  26. MABES Summary • An advanced supply chain decision support system • Provides asset visibility into the logistics supply chain • Two patents filed on this technology • Deployed on the F-16 manufacturing line

  27. The Collaborative Management Environment Ames Lab Berkeley Lab Fermi Lab Los Alamos Lab Sandia Lab Livermore Lab Oak Ridge Lab Database Management Human Computer Interaction Meta-modeling Languages Object-oriented Technologies Scalable Algorithms Security Collaborative Management Environment Information Integration XML Software Engineering

  28. Current situation • Problem • Field Work Proposals (FWPs) submitted to DOE are in paper books • Weeks and thousands of dollars are spend in collating, copying, binding, and shipping these books • The books provide very limited query and search capability • Approach • Developed an FWP “ontology” for several national laboratories • Pioneered use of the Extended Markup Language (XML) as a means of storing, querying, and presenting FWP information. • Simple data storage technology • Very low costs to the labs, integration work done by CME team • Very well received article at XML’98, InForum’99, InterLab’99.

  29. Sample FWP

  30. Same XML Data Type Definition Tag Definitions Tagged Document

  31. CME System

  32. CME Summary • One common picture to DOE • Integrated, collaborative, and distributed information in a secure web-based environment • Innovation • Use of Extended Markup Language (XML) for low-cost information integration • Staged Schema migration CME information model • DOE evaluating CME to be a corporate system

  33. CINC: Class III is my priority DLA: We’re on it! CINC: Class III is my priority DLA: We’re on it! Forces N Home Reload Images Open Print Find http://ebw.ops.cop Sustainment DLA Logistics C1 JRSOI COA JTAV JTL Tools Operations Joint Theater Logistics Management • SURGE • Optimize Logistics • Minimize wait time • MABES • Total Asset Visibility • Supply Chain Model • CME • Integrated, • Collaborative, • Distributed Information

  34. Summary • We have expertise and experience with developing • Advanced Logistics systems • Collaborative decision support systems • We are pioneering in agent and information integration technologies • We can help transform joint theater logistics management to a real-time logistics information system

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