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

1. 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 ecc1@psu.edu

2. 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

3. 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

4. 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

5. 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

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

7. “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

8. 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

9. USMC Solution:Autonomic Logistics Op Concept AL KPP’s: Position Location Identification Fuel, Ammo Levels System Health Mobile Loads

10. 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

11. 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)

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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 ecc1@psu.edu Karl Reichard, Head Complex Systems Dept. (814) 863-7681 kmr5@psu.edu Bob Walter, Head Enterprise Systems Dept. (814) 863-8876 rlw9@psu.edu

22. 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

23. 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

24. 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)

25. 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