Agent-Based Joint Theater Logistics Management Dr Thomas E

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) } 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 2

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 3

Future Technology Trend Internet Telephone Face to Face 4 GE A TS N

Successful Projects }We have extensive expertise in agent development }Began working with agent technologies in 1980 s Supply Chain Management Agent System 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 Knowledge-based Systems - Manufacturing Advisors }Over 10 successful projects within the last 5 years Knowledge-based Systems for Constructability }Collaborations with leading Design and Analysis of Computer Experiments Knowledge-based Computer Systems Calibration 1985 5 1990 1995 agent experts 2000

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 6

What are Agents? . . . Software entities that assist people and act on their behalf. . . Software “robots” Traditional Software Object Proactive detect changes in their environment and react to those in a timely manner by answering to events and initiating actions Behavior 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 State Autonomous Learning have the ability to learn from experiences in their environment 7 can have control over their own actions and be able to work and launch actions independent of the user or other actors

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 B. Dalton Learn for next time 8 1 Day $20. 25 Order the book

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

SURGE

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

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

Results on C-130 Parts Input Data Grouping Results ro G ou Gr up 5 Group 1 G ro ro G up 4 p 2 up 3 13

C 130 Grouping Results Why two groups? Common Processes Group “ 3” Processes Group “ 5” Processes Why are extrusions spread over two groups? 14

Results Cell 1 Group 2 Group 1 Gr oup 2 up ro G 3 Cell 2 Group 1 Group 3 Wire Harness Data forms 3 groups 15 Cell 3 Possible cell layout

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

Neural Network Forecasting Full Training Set 17 Partial Training Set Forecast

SURGE Summary } An advanced logistics optimization system } Significant research breakthroughs in clustering technology } Provides significant savings and leadtime reductions to DLA 18

MABES

Process Overview Projected or Actual Parts Need Group Parts Form Lean Cells 02

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

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

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

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

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

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 26

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

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, In. Forum’ 99, Inter. Lab’ 99. 28

Sample FWP 29

Same XML Data Type Definition Tag Definitions 30 Tagged Document

CME System 31

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 lowcost information integration – Staged Schema migration CME information model } DOE evaluating CME to be a corporate system 32

Joint Theater Logistics Management SURGE Optimize Logistics Minimize wait time MABES Total Asset Visibility Supply Chain Model CINC: Class III is my priority DLA: We’re on it! Forces Sustainment CINC: Class III is my priority DLA: We’re on it! DLA Logistics JRS OI CME Operations Integrated, Collaborative, Distributed Information 33 COA JTAV JTL Tools Home Images Print Reload Open Find http: //ebw. ops. cop C 1 N

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 34