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Application of Agent Technology for ENRON Dr. Thomas E. Potok Collaborative Technologies Research Center Computer Science and Mathematics Division Oak.

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Presentation on theme: "Application of Agent Technology for ENRON Dr. Thomas E. Potok Collaborative Technologies Research Center Computer Science and Mathematics Division Oak."— Presentation transcript:

1 Application of Agent Technology for ENRON Dr. Thomas E. Potok Collaborative Technologies Research Center Computer Science and Mathematics Division Oak Ridge National Laboratory

2 2 Intelligence Agent Team  Pioneering research in –Knowledge Fusion Systems –Intelligent Agent technology  Successfully developed systems for –Industry: Lockheed Martin –Government: The Department of Energy –Military: The Defense Logistics Agency and USPACOM  Approach –Small Entrepreneurial team of researchers and software developers –Focusing on key strengths of each

3 3 Future Technology Trend Face to Face Telephone Internet AGENTS

4 4 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 1985199019952000

5 5...Software entities that assist people and act on their behalf...Software “robots” 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 What are Agents?

6 6 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 B. Dalton Library... 2 Days $18.50 1 Day $21.75 1 Day $20.25 1 Day Free Order the book Learn for next time eBay 1 Day $12.50

7 7 Oak Ridge Technology SURGE Supply Chain Optimization MABES Agent-based Network Modeling

8 Agent-based Network Modeling

9 9 Why Agents?  Simulation techniques are thorough, but can take hours to run  Mathematical methods can be very fast, but make broad assumptions  Both require extensive training and validation  Agents provide the capability to: –Bridge the gap between simulation and Mathematical methods –Easy to use and develop –Easy connection of other systems –Move from analysis to action

10 10 Agent Based Network Model Simulation and analytic models Control over local and global behavior Easy to setup and adapt From deployed MABES agent-based network model

11 11 Vision Agents that provide the ability to: conduct business from the desktop connecting to resources across town and across the country

12 Agent-based Supply Chain Optimization

13 13 Process Overview Projected or Actual Parts Need Group Parts Form Lean Cells Optimize Cells

14 14 SURGE Grouping Agents Part Families Agent Group Themselves Agent Mediator Parts represented by Agents

15 15 Results on C-130 Parts Group 3 Group 2 Group 1 Group 5 Group 4 Input DataGrouping Results

16 16 C130 Grouping Results Why are extrusions spread over two groups? Common Processes Group “3” Processes Group “5” Processes

17 17 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

18 18 SURGE 1st Phase Results  Investment –Initial investment $3.3M –Agent investment $812K –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 total savings –Significant reduction in lead times Agent Investment Total Savings {

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

20 20 Traditional Methods Consume Time and Effort Technology Experts Information Management Foreman Weeks or Months Cell Optimization

21 21 Value of Agent Systems Technology Foreman Minutes Agent System ExpertsManagement Fast Flexible Collaborative

22 22 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

23 23 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

24 24 Killer app – Supply Chain Integration Manufacturing Operations 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 MarketSupply Chain NEEDED: 1)Fast, reliable, private networks 2)Flexible software agents in integrate suppliers

25 25 Palmtop or Cell-phone Hurricane Jim will disrupt Acme Extrusions Apex bolts Recommend activating Johnson bolts and extrusions as a backup Details Henderson Pins needs review Stock price has drop 23% in 2 days 7 Press reports possibly about: Extortion Federal indictment See press URL Recommend shifting pin production to Wilson Pins Supplier Scenario

26 26 Agent-based Solutions for Enron SURGE Supply Chain Optimization MABES Agent-based Network Modeling

27 27 Summary –We have expertise and experience with developing Advanced agent-based systems Collaborative decision support systems –We are pioneering in agent and information integration technologies –Proven track record of success


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