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 Face to Face Telephone Internet AGENTS

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

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...Software entities that assist people and act on their behalf...Software “robots” What are Agents? Goal-driven have a purpose and act in accordance with that purpose until it is fulfilled Communicative able to interact and communicate with users and other agents Proactive detect changes in their environment and react to those in a timely manner by answering to events and initiating actions 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 State Traditional Software Object Behavior

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

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

SURGE

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

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

13 Results on C-130 Parts Group 3 Group 2 Group 1 Group 5 Group 4 Input DataGrouping Results

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

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

16 SURGE 1st Phase Results  Investment –Initial investment $3.3M –Agent investment $812K of the $3.3M –1st phase duration of 9 months  Return –7,832 of ~130K spare parts grouped, 4400 Parts Bid –$7.0M savings in Inventory Reduction (30%) –$5.8M Savings in reduced pricing (23%) –58% Reduction in lead times (from 220 to 93 days)  Total –$12.8M in savings –Significant reduction in lead times Agent Investment Total Savings {

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

18 Neural Network Forecasting Full Training Set Partial Training Set Forecast

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

MABES

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

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

23 Value of Agent Systems Technology Foreman Minutes Agent System ExpertsManagement Fast Flexible Collaborative

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

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

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

27 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

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

29 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.

30 Sample FWP

31 Same XML Data Type Definition Tag DefinitionsTagged Document

32 CME System

33 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

34 Sustainment Forces Operations JTL ToolsJTAV COA DLA Logistics HomeReloadImagesOpenPrintFind N C1 CINC: Class III is my priority DLA: We’re on it! CINC: Class III is my priority DLA: We’re on it! JRS OI Joint Theater Logistics Management SURGE Optimize Logistics Minimize wait time MABES Total Asset Visibility Supply Chain Model CME Integrated, Collaborative, Distributed Information

35 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