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What is Academia Doing to Develop and Mature Sense and Respond Capabilities? An Overview of Activities at Penn State. Sense and Respond Logistics Forum Defense Acquisition University 21 September, 2006. Ed Crow 814/863-9887 [email protected]

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slide1

What is Academia Doing to Develop and Mature Sense and Respond Capabilities?

An Overview of Activities at Penn State

Sense and Respond Logistics Forum

Defense Acquisition University

21 September, 2006

Ed Crow

814/863-9887

[email protected]

slide2

What is Academia Doing to Develop and Mature Sense and Respond Capabilities?

MATURE:

Log Operational Architecture(s)

Championing Open Standards

Standardized Engineering Methodology for Implementation

Metrics & Business Case Analysis

DEVELOP:

Sensor Systems that report status and health of combat critical items

Comms and IT Linkages linkages from tactical units into Global Combat Service Support

Doing end-to-end demonstrations to show organizational and technical interfaces, gaps and overlaps

common needs to transform enterprise processes
Common Needs to Transform Enterprise Processes

Capabilities Measures Needs

-Collect & Share Data

-Have Visibility

-Work Together Off a Common Operating Picture

-Effective

-Speed

-Time

-Safety

-Cost

-Mass

-Volume

-Manpower

Architecture

Interoperability

Technology Infusion

Common Standards

Path to Implementation

value added end to end prototyping from vehicle to enterprise
Value Added: End-to-End Prototyping from Vehicle to Enterprise

Data Requirements

  • Situational Awareness & Situational Understanding for Commanders in Mission Planning
  • Critical platform data for planning and execution
  • Reach as required

Network Enabled

5

ERP

Off-Platform

Architecture

GCCS

  • Commanders
  • S2
  • S3

GCSS MC

  • S4
  • Maintainers
  • PM’s

Common Standards, Specifications, Protocols

4

Interoperability

Distributed Processing

  • Synchronize & Reduce redundant efforts
  • Establish Configuration Control of Architecture
  • Business Process baseline for Autonomic Logistics
  • Provide Adaptable Technologies

Commonality

&

Interoperability

3

Commonality

Embedded Health Management System

2

Integration

Sensor Based & Linked

On-Platform

Architecture

  • Research
  • Design
  • Develop
  • Test
  • Implement

1

Synchronize

slide5

Platform “Sensors”the Key Enabler- get data flowing

Apply appropriate sensors (data),

analysis (knowledge), and reasoning (interpretation) to provide system

level health assessment.

-Detect and isolate component

degradation and incipient failure

-Give appropriate alerts to operator,

maintainer, log/supply and C2

Earlier Notification Buys Time

Failure Prevention

Failure Response

Normal Operation

Functional Failure

Collapse

Return to Service

Fault Initiation

Prognostics-

Very High Tactical Value

Diagnostics- High Supportability Payoff

sensors at the platform level batteries
“Sensors” at the Platform Level- Batteries

Need Battery

GoodShort Circuit

Open CircuitPassivation

Will need Battery

Demand

Battery has failed- passivation

Battery is healthy, but low charge

Capability

Battery is healthy

Log/Supply

Determination of State

-State of Charge

-State of Health

-State of Life

System Monitoring

C2

Health

Feature determination:

-signal processing

-models

-automated reasoning

Condition

SubSystem Monitoring

  • Targeted Degraders
  • Charge
  • Cold Cranks
  • Cycle life
  • Sensors
  • impedance sensor

Signal

Component Monitoring

platform status and health reporting architecture
Platform Status and Health Reporting Architecture

Planner /

Logistics

Operator /

Commander

Knowledge

Diagnostic/

Prognostic

Unit

Subsystem

Monitor

Subsystem

Monitor

Subsystem

Monitor

Engine

/ Motor

Drive Train

Generator

Alternator

Batteries

Fuel, Lube

H2O

Ammo

Sensors

Sensors

Mobility

Electrical

Power

Combat

Resources

Data

usmc solution autonomic logistics op concept
USMC Solution:Autonomic Logistics Op Concept

AL KPP’s:

Position Location Identification

Fuel, Ammo Levels

System Health

Mobile Loads

usmc autonomic logistics request management process
USMC Autonomic LogisticsRequest Management Process

Command

& Control(C2)

BattalionS4

(RM)

OrderManager(OM)

  • Work package for planetary wheel driverepair
  • Log Status
  • Parts

InventoryCapacityManager(ICM)

Automated Demand Flow

  • Transport
  • AL Demand Message
  • Condition-based demand triggered by sensors on planetary wheel drive
  • Skills / Tools

DistributionCapacityManager(DCM)

Focused & Tailored Response

Platform

MaintenanceCapacityManager(MCM)

MobileContactTeam(ME)

  • Skills PartsTools
slide11

Platform-AL-GCSS

GCSS

Oracle 11i

APIs

BPEL

CLC2S

  • Assumptions
  • Wireless LAN (no BW limits)
  • No Security Issues

Inventory

(WMI / WMO)

Log P/E

Service Request

(RMP)

ECS

C2PC

BizProccExecLang

Workflow

  • On-Condition Based Demand Messages
  • Differential
  • Alternator
  • Fuel Pump
  • Time-Based Demand Triggered by “meter” readings
  • Odometer
  • Engine Hours
  • Rounds Fired
  • Supply Demand based on reported quantity
  • Fuel
  • Ammo
  • Mobile Loads

Mobile Field Service Client

AL

Client

Oracle Sensor Edge Server

AutonomicLogistics Control Unit (ALCU)

GPS

RFID Reader & Mobile Load Sensors

  • Platform-based Logistic Sensors
  • Location from GPS
  • Platform Health and fuel status (CANBUS)
  • Ammo and mobile loads handled by the Edge Device(s)
sea based sense and respond to distributed operations ashore

Sea Base

Sea Based Sense and Respondto Distributed Operations Ashore

S&RL EC connects the Sea Base with the tactical operational picture thru integrated log/C2

Anticipated “demands” from distributed operational forces ashore are dynamically supported from a sea based Log/C2 system that is paced with the heartbeat of operations

The Sea Based Log/C2 center assimilates, prioritizes, synchronizes and de-conflicts to achieve a focused and tailored logistics response to tactical forces

The Sea Base is much more than an automated, floating, forward supply point

onr distributed operations project status reporting capability for sea viking loe 3

ONR Distributed Operations Project-Status Reporting Capability for Sea Viking LOE#3

IRIDIUM

Satellites receive data burst

Iridium ground station receives data burst and sends it through DoD gateway into internet.

IRIDIUM

http://soademo.arl.psu.edu

DO Platoon Status Web Page

Fuel, Water, Batteries

Server

Platoon Master Vehicle sends Platoon data directly to S4 at predetermined interval.

www

Shipboard Web Access- S4 on ship accesses information about status and levels from DO platoon

slide14

AUTOLOG SITUATION AWARENESS [log/supply monitor page]

MY VIEW: CommandLog/Supply Maintenance

SET UP CONFIGURATION

MONITOR ORDER

POSITION, LOCATION TIME

STATUS LEVELS RATES & SYSTEM HEALTH

Current Levels Consumption Rates

Blue Force Tracker

in here

LAV1 LAV2 EFV1 EFV EFV31 Total Organization In View

FUEL

CONSUMMABLES

H2O

ORGANIZATIONAL CONFIGURATION

BATTS

Now in View

MOBILE

LOADS

Type/QTY

Type/QTY

Type/QTY

Type/QTY

Type/QTY

FMC

FMC

PMC

FMC

NMC

SYSTEM

HEALTH

monitoring system development and implementation

Science

Sensing

Feature

Extraction

FaultDetection

Damage

Estimation

Feature

Tracking

& Prognostics

Collectraw data

Reducedata

Analyzedata

Makediagnosis

Perform assessment

Technology

Intelligent

Nodes

Enterprise

Monitor/

Control

Intelligent

Nodes

Subsystem

Intelligent

Nodes

System

Health

Monitor

Smart

Sensors

Data

Information

Knowledge

Decision

Action

Engineering Implementation

Open Systems Architecture

RCM/

FMECA

Sensors

HW/SW

Architecture

Comm.

Architecture

Comm.

Network

Human-to-Machine

Interface

Monitoring System Development and Implementation
slide16

Cost-Benefit Analysis

Benefits increase as service life is extended

3-4 yr. payback

“s” shape effect due to deferred depot overhauls

Benefits can either be: increased Ao; decreased life cycle cost or reduced number of assets for same total operational availability

championing open standards
Championing Open Standards
  • THE CHALLENGE
  • Implement a common architecture framework that:
    • Has a foundation in open standards
    • Approaches the goal of plug and play
    • Allows vendors to protect proprietary solutions
  • THE SITUATION
  • Increasingly DOD acquisition programs are requiring availability, readiness, supportability and life cycle cost
  • Response is to ambitiously reaching toward prognostics
  • Each is developing a unique data architecture
  • Vendors want to protect proprietary solutions

1

ISO-13374 Condition Monitoring and Diagnostics of Machines

2

3

MIMOSA OSA-CBM Open System Architecture for Condition-Based Maintenance

MIMOSA OSA-EAI Open System Architecture- Enterprise Application Integration

www.mimosa.org

our involvement
Our Involvement

Future Combat Systems

ELog 21

HQ I&L Log Modernization

Sea Basing

LTA- Common Logistics Operating Environment

Sea Based Sense & Respond Logistics

MCSC GCSS

HBCT- Vehicle Health Management

MCSC Autonomic Logistics

KSC, JSC & MSFC

FCS- LDSS, P/SMRS Analysis

MCSC Platforms- LAV, MTVR, Howitzer, HWWMV, G/ATor

Ship CBM

TWV- HEMTT Transition

ONR S&T

Joint ARMY/USMC AL

slide19

KPP’s and Gaps

  • Logistics KPP’s
  • Dispatching tailored logistics support
  • Minimizing footprint ashore
  • Uninterrupted operational availability of equipment
  • Meeting anticipated and forecasted demands
  • Ability to adjust to dynamically changing demands
  • Command Control KPP’s:
  • Maintain ability to observe, decide and act without impediment
  • Maintain Operational Tempo
  • Maximize Agility with low/no footprint
  • Distance/depth of operations

Key S&T Needed

  • Technology Products:
  • Predictions of remaining useful operational life of equipment (caused by depletion of consumables or fault/failure)
  • Visualization of Commander’s Intent w.r.t. demand on consumables, spares, parts & maintenance
  • Automation of individual platform information into an aggregated and “context” relevant situational picture

Forecast & Future Usage Models Derived from Commander’s Intent

Decision Support Methods to trade & optimize best COA’s

Prognostics for accurate RUL estimates

Puts the autonomic into AL

experiences in prototyping systems on platforms
Experiences in Prototyping Systems on Platforms

Rotorcraft

Ships

Aircraft

Fire

Support

Air Defense

Power

Fire Support

Space

Tactical Wheeled Vehicles

Prototype Systems

Technology Base

Combat Vehicles

Unmanned Systems

slide21

Penn State’s Applied Research Laboratory

  • Engineering of Embedded Diagnostics and Prognostics
  • Architecture Design for Logistics/Command-Control Systems
  • Full Time Dedicated Science & Engineering Staff
  • US Citizens, cleared for DoD
  • Established Tech Transfer Processes

Ed Crow, Div Head

(814) 863-9887

[email protected]

Karl Reichard, Head Complex Systems Dept.

(814) 863-7681

[email protected]

Bob Walter, Head Enterprise Systems Dept.

(814) 863-8876

[email protected]

recent and current projects
Recent and Current Projects
  • USMC Distributed Operations
  • Supporting Marines from the Sea Base
  • Reduce physical and cognitive loads
  • High level of integration
  • Army Common Logistics Operating Environment
  • OSA-CBM and OSA-EAI demos
  • Standards for the AILA
  • Coordinate Joint architectures
  • USMC GCSS and Autonomic Logistics
  • Sandbox to reduce program risks
  • Integrate ITV and COTS RFID for interorganization transfers
  • Systems integration laboratory
  • Army Future Combat Systems
  • Logistics integration studies
  • Web services for PBL
  • ISHM standards
slide23

DST

C2PC

BCS3

GCSS-MC

FBCB2

CLC2S

Platoon

Squad

Strategy for Integration and Roll-Up of AL Generated Demand

BN COC

CSSOC

Situation Report

Service Request

  • AL Transaction Manager
  • Message Routing
  • Synchronous Transaction Data Buffer
  • Reference Data
    • Force Structure
    • Asset Registry
    • Reporting parameter

LOGSITREP

SITREP

Batallion

Design to be Generic within Hierarchy

Marine

distributed op s require a whole new logc2 calculus
Distributed Op’s Require a Whole New LogC2 Calculus

Distributed

Ops

Slow, Linear, Reactive

Force

on

Force

Non-Linear, Adaptive,

Capabilities Based

SENSE

OBJECTIVE

Minutes

Interpret Demand

TODAY

Days/Hours

RESPOND

“Demand Drives Everything”- the log/C2 systems need to be informed by real-time, accurate demands from platforms in service (autonomic logistics)

Thus log response is highly flexible, rather than highly optimized (global combat support system)

implementing mimosa standards for ishm in a services oriented architecture soa

AdvisoryGeneration

Other examples:

Portable Maintenance Aids

Mobile Field Service Tools

Interactive Electronic Technical Manuals

Electronic Maintenance Support Systems

OSA-CBM

Web Service

PrognosticsAssessment

OSA-CBM

Web Service

2

OSA-EAITech-CDE

OtherConsumers

OtherConsumers

HealthAssessment

OSA-CBM

Web Service

OSA-EAITech-XML

OSA-EAITech-CDE

Web Service

OSA-EAITech-XML

Web Service(s)

OSA-EAITech-XML

Web Service(s)

StateDetection

OSA-CBM

Web Service

3

OSA-EAITech-CDE

OSA-EAI

Archive

DataManipulation

OSA-CBM

Web Service

OSA-CBMXML

DataAcquisition

OSA-CBM

Web Service

Sensor on Componentor LRU

Implementing MIMOSA Standards for ISHMin a Services Oriented Architecture (SOA)

Proprietary algorithm(s) with open interfaces

www.mimosa.org

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