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

An Overview of Activities at Penn StateAn Overview of Activities at Penn State

Sense and Respond Logistics Forum

Defense Acquisition University

21 September, 2006

Ed Crow

814/863-9887

ecc1@psu.edu

ARLPenn State

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

MATURE:

Log Operational Architecture(s)

Championing Open Standards

Standardized Engineering Methodology for Implementation

Metrics & Business Case Analysis

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

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

ARLPenn State

Common Needs to Transform Enterprise Processes

-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

Capabilities Measures Needs

ARLPenn State

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

GCCS Commanders S2 S3

Value Added: End-to-End Prototyping from Vehicle to Enterprise

Off-PlatformArchitecture

On-PlatformArchitecture 1

Synchronize

3Commonality

4Interoperability

5ERP

2Integration

GCSS MC S4 Maintainers PM’s

Common Standards, Specifications, Protocols

Commonality&

Interoperability

Embedded Health Management System

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

Research Design Develop

Test Implement

Network Enabled

Distributed Processing

Data Requirements

Sensor Based & Linked

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-Detect and isolate component degradation and incipient failure-Give appropriate alerts to operator, maintainer, log/supply and C2

Failure Prevention Failure Response

Normal Operation

Fault Initiation

Functional FailureCollapse Return to

Service

Diagnostics- High Supportability Payoff

Prognostics-Very High Tactical Value

Platform “Sensors”the Key Enabler- get data flowing

Apply appropriate sensors (data), analysis (knowledge), and reasoning (interpretation) to provide system level health assessment.

Earlier Notification Buys Time

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Battery Graveyard… ¼ - 1/3 of these are still good…

ARLPenn State

“Sensors” at the Platform Level- Batteries

SubSystem Monitoring

Component Monitoring

System Monitoring

Signal

Condition

Health

Capability

Demand

C2

Log/Supply

Sensors• impedance sensor

Sensors• impedance sensor

Feature determination:-signal processing-models-automated reasoning

Feature determination:-signal processing-models-automated reasoning

Determination of State-State of Charge-State of Health-State of Life

Determination of State-State of Charge-State of Health-State of Life

Targeted Degraders• Charge• Cold Cranks• Cycle life

Targeted Degraders• Charge• Cold Cranks• Cycle life

3233

3435

36 9

9.5

10

10.5

4.4

4.6

4.8

5

5.2

5.4

R e(Z)

Im(Z

)

W

DLCw1

q+W

ws

D ecreasingFrequency

Ohmic Resistance

Diffusion Layer Im pedance Charge Transfer ResistancesW

q

CDLElectrical Double Layer Capacitance

Good Short Circuit

Open Circuit Passivation

Battery is healthy

Battery is healthy, but low charge

Battery has failed- passivation Will need Battery

Need Battery

ARLPenn State

MobilityElectrical

PowerCombat

Resources

Sensors

Engine / Motor

Drive Train GeneratorAlternator

Batteries Fuel, LubeH2O

Ammo

Sensors

SubsystemMonitor

SubsystemMonitor

Diagnostic/Prognostic

Unit

Operator /Commander

SubsystemMonitor

Planner /Logistics

Platform Status and Health Reporting Architecture

Knowledge

Data

ARLPenn State

USMC Solution:Autonomic Logistics Op Concept

AL KPP’s:

Position Location Identification

Fuel, Ammo Levels

System Health

Mobile Loads

ARLPenn State

USMC Autonomic LogisticsRequest Management Process

Platform

BattalionS4

(RM)

OrderManager

(OM)

InventoryCapacityManager

(ICM)

DistributionCapacityManager(DCM)

MaintenanceCapacityManager(MCM)

MobileContactTeam(ME)

•Skills PartsTools

•Parts

•Transport

•Skills / Tools

Command

& Control(C2)

•Log Status

Automated Demand Flow

Focused & Tailored Response

•Work package for planetary wheel drive

repair

•AL Demand Message

•Condition-based demand triggered by sensors on planetary

wheel drive

ARLPenn State

GCSSInventory

(WMI / WMO)

Service Request(RMP)

Oracle Sensor Edge Server

RFID Reader & Mobile

Load Sensors

AutonomicLogistics

Control Unit (ALCU)

ALClient

GPS

Mobile Field Service Client

Oracle 11i APIs

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

ECS

Log P/E

CLC2S

C2PC

BP

EL

BizProccExecLang

Platform-based Logistic Sensors• Location from GPS• Platform Health and fuel status (CANBUS)• Ammo and mobile loads handled by the Edge

Device(s)

• 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

Platform-AL-GCSS

Workflow

ARLPenn State

Sea BaseSea Base

Sea Based Sense and Respondto Distributed Operations Ashore

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

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

ARLPenn State

ONR Distributed Operations Project-Status Reporting Capability for Sea Viking

LOE#3

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

Satellites receive data burst

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

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

IRIDIUM

IRIDIUM

Server

http://soademo.arl.psu.eduDO Platoon Status Web Page

Fuel, Water, Batteries

www

ARLPenn State

AUTOLOG SITUATION AWARENESS [log/supply monitor page]MY VIEW: Command Log/Supply Maintenance

SET UP CONFIGURATION MONITOR ORDER

POSITION, LOCATION TIME STATUS LEVELS RATES & SYSTEM HEALTH

CONSUMMABLES

ORGANIZATIONAL CONFIGURATION

Blue Force Tracker

in here

MOBILE

LOADS

SYSTEM

HEALTH

FUEL

H2O

BATTS

FMC

Now in

View

Current Levels Consumption Rates

PMC

FMC

FMC

NMC

Type/QTY

Type/QTY

Type/QTY

Type/QTY

Type/QTY

LAV1 LAV2 EFV1 EFV EFV31 Total Organization In View

ARLPenn State

Monitoring System Development and Implementation

CollectCollectraw dataraw data

Perform Perform assessmentassessment

MakeMakediagnosisdiagnosis

ReduceReducedatadata

Science Science

AnalyzeAnalyzedatadata

SensingSensing FeatureFeature ExtractionExtraction

FaultFaultDetectionDetection

DamageDamageEstimationEstimation

Feature Feature TrackingTracking

& Prognostics& Prognostics

DataData InformationInformation DecisionDecisionKnowledgeKnowledge

TechnologyTechnology

IntelligentIntelligentNodesNodes

IntelligentIntelligentNodesNodes

SmartSmartSensorsSensors

EnterpriseEnterpriseMonitor/Monitor/ControlControl

SubsystemSubsystemIntelligentIntelligent

NodesNodes

SystemSystemHealthHealth

MonitorMonitor

ActionAction

Engineering ImplementationEngineering Implementation

SensorsSensors HW/SWHW/SWArchitectureArchitecture

Comm.Comm.ArchitectureArchitecture

Comm.Comm.NetworkNetwork

Human-to-Human-to-MachineMachineInterfaceInterface

Open Systems ArchitectureOpen Systems Architecture

RCM/RCM/FMECAFMECA

ARLPenn State

Prognostics/CBM Effect on LCC

$400,000,000

$500,000,000

$600,000,000

$700,000,000

$800,000,000

$900,000,000

$1,000,000,000

$1,100,000,000

$1,200,000,000

$1,300,000,000

$1,400,000,000

5 7.5 10 12.5 15 17.5 20 22.5

Length of Estimate (Years)

To

tal

Lif

e C

ycle

Co

st

Adjusted Prognostics

LCC Without Prognostics

LCC With Prognostics

Cost-Benefit Analysis

Benefits increase as service life is

extended3-4 yr.

payback“s” shape effect due to

deferred depot overhauls

AAV RAM/RS Data (Hours) W/O Prog W/ProgMean Time Between Failures 64 73.6Mean Time To Repair 0.87 0.87Mean Logistics Delay Time 5.4 2.7675

AAV RAM/RS Calculations W/O Prog W/ProgForecasted Op Availability 91.08% 95.29%Increase in Op Avail w/Prog 4.21%Increased AAVs Mission Capable w/Prog 29Total LCC Costs per AAV w/Prog $973,504Operational AvailabilityOpportunity Benefit of Prognostics $27,890,754

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

ARLPenn State

Championing Open Standards

ISO-13374 Condition Monitoring and Diagnostics of Machines

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

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

MIMOSA OSA-CBM Open System Architecture for

Condition-Based Maintenance

MIMOSA OSA-EAI Open System Architecture-

Enterprise Application Integration

2 3

1

www.mimosa.org

ARLPenn State

Our Involvement

ELog 21HQ I&L Log Modernization

MCSC GCSS

MCSC Autonomic Logistics

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

LTA- Common Logistics Operating Environment

Future Combat Systems

KSC, JSC & MSFC

Sea Basing

Sea Based Sense & Respond Logistics

HBCT- Vehicle Health Management

FCS- LDSS, P/SMRS Analysis

Joint ARMY/USMC AL

TWV- HEMTT TransitionShip CBM

ONR S&T

ARLPenn State

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

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

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

Key S&T Needed

Decision Support

Methods to trade &

optimize best COA’s

Forecast & Future Usage Models Derived from

Commander’s Intent

Prognostics for

accurate RUL

estimates

Puts the autonomic into AL

KPP’s and Gaps

ARLPenn State

Experiences in Prototyping Systems on Platforms

Prototype Systems

Technology Base

Air Defense

SpaceTactical Wheeled Vehicles

AircraftRotorcraft

Ships

Combat Vehicles

Fire Support

Unmanned Systems

Power

Fire Support

ARLPenn State

Penn State’s Applied Research Laboratory

Ed Crow, Div Head (814) 863-9887 ecc1@psu.eduKarl Reichard, Head Complex Systems Dept. (814) 863-7681 kmr5@psu.eduBob Walter, Head Enterprise Systems Dept. (814) 863-8876 rlw9@psu.edu

Concepts

Processes

ProductsSolutions

Technologies

AcquisitionDOTMLPF

DoctrineOrganization

Training Materiel Leadership Education Personnel FacilitiesStandards

Trials &

Evaluation

By a Non-V

ested

Party

NEED

Concepts

Processes

ProductsSolutions

Technologies

AcquisitionDOTMLPF

DoctrineOrganization

Training Materiel Leadership Education Personnel FacilitiesStandards

Trials &

Evaluation

By a Non-V

ested

Party

NEED

•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

ARLPenn State

Recent and Current Projects

USMC Distributed Operations

• Supporting Marines from the Sea Base

• Reduce physical and cognitive loads

• High level of integration

USMC GCSS and Autonomic Logistics

• Sandbox to reduce program risks

• Integrate ITV and COTS RFID for interorganization transfers

• Systems integration laboratory

Army Common Logistics Operating Environment

• OSA-CBM and OSA-EAI demos

• Standards for the AILA

• Coordinate Joint architectures

Army Future Combat Systems

• Logistics integration studies

• Web services for PBL

• ISHM standards

ARLPenn State

AL Transaction Manager

• Message Routing

• Synchronous Transaction Data Buffer

• Reference Data

• Force Structure

• Asset Registry

• Reporting parameter

Strategy for Integration and Roll-Up of AL Generated Demand

FBCB2

BCS3

C2PCService Request

Situation Report

CLC2S

GCSS-MC

DST

BN COC CSSOCB

atal

lion

Mar

ine

Design to be Generic within

Hierarchy

Pla

toon

Squ

ad

LOGSITREPSITREP

ARLPenn State

Force

on

Force

Distributed Op’s Require a Whole New LogC2 Calculus

SENSE

Interpret Demand

RESPOND

Non-Linear, Adaptive,Capabilities Based

Slow, Linear, Reactive

TODAY

Days/Hours

“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)

Distributed

Ops

OBJECTIVE

Minutes

ARLPenn State

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

OtherConsumers

OSA-EAITech-XML

Web Service(s)

OSA-EAITech-XML

Web Service(s)

OtherConsumers

OSA-EAITech-CDE

OSA-EAITech-XML

Other examples:Portable Maintenance AidsMobile Field Service ToolsInteractive Electronic Technical ManualsElectronic Maintenance Support Systems

OSA-CBMXML

OSA-CBMWeb Service

DataAcquisition

DataAcquisition

DataManipulation

DataManipulation

StateDetection

StateDetection

HealthAssessment

HealthAssessment

PrognosticsAssessment

PrognosticsAssessment

AdvisoryGeneration

AdvisoryGeneration

Sensor on Component

or LRU

Sensor on Component

or LRU

OSA-CBMWeb Service

OSA-CBMWeb Service

OSA-CBMWeb Service

OSA-CBMWeb Service

OSA-CBMWeb Service

2

OSA-EAITech-CDE

OSA-EAITech-CDE

Web Service

Proprietary algorithm(s) with open interfaces

OSA-EAIArchive

Failure Histories

Geo-Spatial Tracking

Component Tracking

Model Database

OEM Model

Reliability InfoRCM

Analysis Info

Root Cause

Analysis Info

Spare Part

Analysis Info

MRO Tools

MRO Labor

MRO Materials

Work Order Tracking

Pre-Planned Work Packages

Reactive Main-

tenancePreventive

Main-tenance

Condition-Based Maint-enance

Calibration & Config.

Mgmt

Open Object

Registry Management

3

www.mimosa.org