Application of Agent Technology

for ENRON

Application of Agent Technology

for ENRON

Dr. Thomas E. Potok

Collaborative Technologies Research Center

Computer Science and Mathematics Division

Oak Ridge National Laboratory

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

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Future Technology Trend

Face to Face

Telephone

Internet

AGEN

TS

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 ControlNeural 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 yearsCollaborations with leading agent experts

1985 1990 1995 2000

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...Software entities that assist people and act on their behalf

...Software “robots”

Goal-drivenhave a purpose andact in accordance withthat purpose until it isfulfilled

Communicativeable to interact andcommunicate with users and other agents

Proactivedetect changes in theirenvironment and react to those in a timely mannerby answering to events and initiating actions

Autonomouscan have control over their own actions and be able to work and launch actions independent of the user or other actors

Learninghave the ability tolearn from experiencesin their environment

State

Traditional Software Object

Behavior

What are Agents?

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Simple Agent Example

Agent, find me the book “War and Peace,”

and I need it tomorrow

Does the agent understand

buying books?

Form a planto buy the

book

Execute the plan

Amazon

Barnes andNobel

B. Dalton

Library

...

2 Days$18.50

1 Day $21.75

1 Day $20.25

1 Day Free

Order thebook

Learn for next time

eBay1 Day $12.50

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Oak Ridge Technology

SURGESupply Chain Optimization

MABESAgent-based Network Modeling

Agent-based Network ModelingAgent-based Network Modeling

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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

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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

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Vision Agents that

provide the ability to: conduct

business from the desktop

connecting to resources across town and across the country

Agent-based Supply Chain Optimization

Agent-based Supply Chain Optimization

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Process Overview

Projectedor Actual

Parts Need

GroupParts

Form LeanCells

Optimize Cells

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SURGE Grouping AgentsPart FamiliesAgent Group Themselves

Agent Mediator

Parts represented by

Agents

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Results on C-130 PartsGroup 3

Group 2

Group 1

Gro

up 5

Gro

up 4

Part Description

Matl Description Matl Type A lloy

Type Part

Agent Grouping Process Spec

BEARING C 1 2SCREW-NLG SCREW STEEL 8630 C 1 2 MIL-S-6050POST-JATO RECEPTACLE BAR HEX BRASS CA360 C 1 2 QQ-B-626SHAFT, FLAP QUAD FRICTION LOCK ROD STEEL 4130 C 1 2 MIL-S-6758SUPPORT-MLG BRAKE LINE CASTING ALUM A356 C 1 2 MIL-A-21180PLUNGER ROD RND STEEL 1095 C 1 2 MIL-S-8559BUSHING BAR HEX STEEL 4130 C 1 2 MIL-S-6758FITTING ROD ALUM 2024 C 1 2 QQ-A-225/6SPACER-DOOR MECH BEARING MLG ROD CRES STL 15-5 C 1 2 AMS5659 TYPE ICONE-MALE LWR ENG MOUNT BAR RND STEEL 4340 C 1 2 MIL-S-5000SHAFT-ESCAPE LADDER AND SEAT S ROD STEEL 4130 C 1 2 MIL-S-6758BUSHING-O/W FLAP BAR HEX STEEL 4130 C 1 2 MIL-S-6758RING-MANIFOLD BAR RND ALUM 2024 C 1 2 QQ-A-225/6STUD-LITTER TIE-DOWN BAR RND STEEL 4130 C 1 2 MIL-S-6758ABUSHING-FLAP CONTROL LEVER ASM ROD CRES STL 303SE C 1 2 AMS 5641BUSHING-ENG COND CONT ROD BRASS CA464 C 1 2 QQ-B-637ROLLER ROD STEEL 4130 C 1 2 MIL-S-6758SPACER-AILERON HINGE FITTING ROD CRES STL 303SE C 1 2 AMS 5641ROLLER ROD STEEL 303SE C 1 2 ASTM A582-80SPACER-CONTROL COL. BASE ROD ALUM 2024 C 1 2 QQ-A-225/6ORFICE,REFRIG INTERCOOLER ROD STEEL 347 C 1 2 QQ-S-763ORIFICE-REFRIGERATOR-FLIGHT DE ROD CRES STL 321 C 1 2 QQ-S-763BOLT-1/2 SQ HD 1/4-28 UNF-3A ROD SQ STEEL 4130 C 1 2 MIL-S-6758BOLT ROD SQ STEEL 4130 C 1 2 MIL-S-6758BOLT-HEAD-DRILLED HEAD-FULL TH BAR HEX STEEL 4130 C 1 2 MIL-S-6758BOLT-1/2 IN SQUARE HEAD SQ ROD STEEL 4130 C 1 2 MIL-S-6758STUD-TIE DOWN CUTER STANCHION HEX BAR STEEL 4130 C 1 2 MIL-S-6758SPACER N.L.G. FULCRUM-BRG-INN ROD STEEL 4130 C 1 2 MIL-S-6758WASHER ROD STEEL 8630 C 1 2 MIL-S-6050WASHER-MLG SWIVEL BOLT BAR RND STEEL 4130 C 1 2 MIL-S-6758WASHER ROD STL 4130 C 1 2 MIL-S-6758WASHER BOLT WING JOINT LOWER ROD STEEL 4130 C 1 2 MIL-S-6758

Input Data Grouping Results

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0

10

20

30

40

50

60

70

80

Number of parts

1 2 3 4 5

Agent Groups

Manual Vs Agent Grouping

Extrusion

Sheet Metal

Plate

Weld Assemblies

Bonded Assemblies

C130 Grouping Results

Why are extrusions spread over two groups?

Part Number # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #363797-1 1 1 1 1 1 1 1 1 1 356089-1L 1 1 1 1 1 339392 1 1 1 1 1 1 1 1 368092-1 1 1 1 1 1 1 1 1 1 3311717-13 1 1 1 1 1 1 1 1 364216-3 1 1 1 1 1 389217-1 1 1 1 1 1 1 1 399860-5 1 1 1 1 1 1 1 388400-27 1 1 1 1 1 1 1 1 1 399860-7 1 1 1 1 1 1 1 1 339210-64 1 1 1 1 1 1 1 1 1 1 1 1 1 373580-1L 1 1 1 1 1 1 1 374957-5 1 1 1 1 1 1 1 1 1 374403-2 1 1 1 1 1 1 1 1 1 1 1 1 1 357771-3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3341136-1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 339659-12 1 1 1 1 1 1 1 1 1 1 1 1 377053-1 1 1 1 1 1 1 1 1 356251-6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 356808-1 1 1 1 1 1 1 1 1 1 1 338696-38 1 1 1 1 1 1 1 1 1 1 1 1338696-40 1 1 1 1 1 1 1 1 1 1 1375229-2L 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 339838-7 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 338742-8L 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1338736-28L 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Common Processes

Group “3” Processes

Group “5” Processes

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Results

Wire Harness Data forms 3 groups

Possible cell layout

Group 1

Group 2

Group 3

Group 1Group 2Group 3

Cell 1

Cell 2

Cell 3

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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

SURGE 1st Phase

$0

$2

$4

$6

$8

$10

$12

$14

Investment Savings

Mill

ions

Pricing

Inventory

Agent

Non-Agent

Agent Investment

Total Savings

{

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SURGE Summary

An advanced logistics optimization system Significant research breakthroughs in

clustering technology Provides significant savings and lead-time

reductions to DLA

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Traditional Methods Consume Time and Effort

Technology

Experts

Information

Management

Foreman

Weeks or Months

Cell Optimization

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Value of Agent Systems

Technology Foreman

MinutesMinutes

Agent System

Experts Management

FastFlexible

Collaborative

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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

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MABES Summary

An advanced supply chain decision support system

Provides asset visibility into the logistics supply chain

Two patents filed on this technologyDeployed on the F-16 manufacturing

line

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Killer app – Supply Chain Integration

Manufacturing Operations

SUPPLIER

SUPPLIER

3rd TIER SUPPLIER

2nd TIER SUPPLIER

PARTNER

SISTER DIVISION

1st TIER SUPPLIER

FABRICATION - SUBASSEMBLY - FINAL - DELIVERYPARTNER

How does a problem here affect operations here

MarketSupply Chain NEEDED:

1) Fast, reliable, private networks

2) Flexible software agents in integrate suppliers

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Palmtop or Cell-phone

Hurricane Jim will disruptAcme ExtrusionsApex bolts

Recommend activating Johnson bolts and extrusions as a backup Details

Henderson Pins needs reviewStock price has drop 23% in 2 days7 Press reports possibly about:

ExtortionFederal indictmentSee press URL

Recommend shifting pin production to Wilson Pins

Henderson Pins

1516

1718

1920

2122

2324

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Date

Sto

ck P

rice

Supplier Scenario

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Agent-based Solutions for Enron

SURGESupply Chain Optimization

MABESAgent-based Network Modeling

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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