# Presentation: 641391

## 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

**Notes:**
Audience: 
Military and government leaders
Message:
I understand your problem
We have mature technology that can help solve your problem
Opening:
Good Morning
I have had the privilege to see several presentations on military logistics, including one by Mr. Kallock at last years NCMS conference in Florida, where you quoted one of my favorite books, Bob Buford’s Halftime.
As I understand it, there are three major challenges today in military logistics 1) an increased number of military operations, each more diverse than the last one, 2) a need for deployments to be better, cheaper, and faster. What took hundreds of days in the gulf war, is now targeted to take hundreds of hours,  3) the existing logistics systems are complex and out dated.

## Collaborative Technologies Research Center (CTRC)

**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

## 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

## Future Technology Trend

**Future Technology Trend**

- Face to Face

- Telephone

- Internet

**AGENTS**

## 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

- 1985

- 1990

- 1995

- 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

## What are Agents?

**...Software entities that *****assist people and act on their behalf***
**...Software “robots”**

**What are Agents?**

- Agent
- Technology

- _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

## 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**
**$18.50**

**1 Day **
**$21.75**

**NA**

**1 Day **
**$20.25**

- Order the
- book

- Learn for next time

## Oak Ridge Technology

**Oak Ridge Technology**

- SURGE
- Optimize Logistics
- Minimize wait time

- MABES
- Total Asset Visibility
- Supply Chain Model

- CME
- Integrated,
- Collaborative,
- Distributed Information

## SURGE

## Supply Chain Overview

**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

## SURGE Grouping Agents

**SURGE Grouping Agents**

- Part Families

- Agent Group Themselves

- Agent Mediator

- Parts represented by Agents

## Results on C-130 Parts

**Results on C-130 Parts**

- Group 3

- Group 2

- Group 1

- Group 5

- Group 4

- Input Data

- Grouping Results

## C130 Grouping Results

**C130 Grouping Results**

- Why are extrusions spread over two groups?

- Common
- Processes

- Group “3” Processes

- Group “5”
- Processes

_**Why two groups?**_

## 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

## 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

- {

## Forecasting Direction

- Small Variance

- Large Variance

- Higher Volumes, Reduced Inventory
- Potential for large savings

- Traditional
- low bid part

- Part family
- with key supplier

## Neural Network Forecasting

- Full Training Set

- Partial
- Training Set

- Forecast

## SURGE Summary

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

## MABES

## Process Overview

- Projected
- or Actual
- Parts
- Need

- Group
- Parts

- Form Lean
- Cells

- Optimize
- Cells

## Traditional Methods Consume Time and Effort

- Technology

- Experts

- Information

- Management

- Foreman

- Weeks or Months

- Cell Optimization

## Value of Agent Systems

- Technology

- Foreman

- Minutes

- Agent System

- Experts

- Management

*Fast*
*Flexible*
*Collaborative*

## MABES: Analytic Model

*MABES: Analytic Model*

**Activity Metrics**

**Minimization**

**Manufacturing Rules**

**Process Metrics**

**Throughput**

- At 17 Planes Per month:
-   - Machine utilization 85%
-   - Cost is $65M
-   - Span time is 48 Days

## MABES: Dynamic Model

- Pull/Push/Takt Animation

*MABES: Dynamic Model*

- Queues and Task Centers

- Identify
- Bottlenecks
- Network Sensitivity
- Outages

## Visibility into the Supply Chain

**Manufacturing**
** ****Operations**

**SUPPLIER**

**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**

## 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

## The Collaborative Management Environment

- 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**

## 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.

## Sample FWP

## Same XML Data Type Definition

- Tag Definitions

- Tagged
- Document

## CME System

## 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

## Joint Theater Logistics Management

**Joint Theater Logistics Management**

- SURGE
- Optimize Logistics
- Minimize wait time

- MABES
- Total Asset Visibility
- Supply Chain Model

- CME
- Integrated,
- Collaborative,
- Distributed Information

## 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