aerospace systems engineering the fuzzy front end

C

Advanced Development

System Integration

System Demo

Risk Reduction & Demonstration

IOC

FUNDING & REQUIREMENTS

Concept Exploration

X

D

D

D

IPR

IPR

IPR

BA 2 or 3

BA 3

BA 5

BA 5/Prod

Production/O&M

MNS

Funding

Requirements

BA 4

ExploratoryDevelopment

AdvancedDevelopment

EngineeringDevelopment

Production Readiness/IOT&E, LRIP

Production

Initial ORD

ORD

Full Program Fundingthrough outyears

Full funding commitment occurs when systems-level work commencesMaintain requirements flexibility early to facilitate cost-performance trades

BA:Budget ActivityMNS:Mission Need StatementORD:Operational Requirements DocumentLRIP:Low Rate Initial ProductionIOT&E:Initial Operational Test and Evaluation

Research Category

6.2/6.3a

6.3a

6.3b

6.4

6.4

Production Readiness & LRIP

Production & Deployment

Support

CASA/CERT/PLMC

Dr. Daniel P. SchrageGeorgia Institute of TechnologyAtlanta, GA 30332-0150www.asdl.gatech.edu

NASAs Life Cycle Process Model (2nd Generation RLV Risk Reduction Solicitation)

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A Value Example: Military Transport Aircraft Overall Evaluation Criterion (OEC)

Si = 1 - PDPHPK

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OverallEvaluationCriterion(OEC)ResponseTimeOEC TargetSystem Design (Preliminary/Parameter)System Integration (Detail/Tolerance)Manufacturing (On-Line Quality)UncertaintyRisk Management/ReductionOEC TargetInitial DistributionSystem Definition & Tech. Development (Conceptual/System)Reduced Variability and Improved Mean ResponseTraditional Cp and Cpk Approach for Continuous, On-line Process ImprovementContinuous Product Improvement / InnovationFuzzy Front EndUpper SpecificationLower SpecificationUpper SpecificationLower SpecificationOverallEvaluationCriterion(OEC)ResponseConinuous RDS along the System Life Cycle to link the fuzzy front end to the process capability approaches

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The VSLCDE- Key CharacteristicsThe purpose of VSLCDE is to facilitate design decision- making over time (at any level of the organization) in the presence of uncertainty, allowing affordable solutions to be reached with adequate confidence. It is a research testbed. Virtual . . . Simulation-based system life-cycle prediction Stochastic . . . Time-varying uncertainty is modeled; temporal decision-making Life-Cycle . . . the design, engineering development, test, manufacture, flight test, operational simulation, sustainment, and retirement of a system. The operational simulation includes virtual testing, evaluation, certification, and fielding of a vehicle in the existing infrastructure, and tracking of its impact on the economy, market demands, environment. Design . . . Implies that the environments main role is to provide knowledge for use by decision-makers, especially for finding robust solutions Environment . . . Implies the support of geographically distributed analyses and people through collaboration tools and data management techniques

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Concept ExplorationMS 0TechReviewMS 1

MNS

MNS

ORDAlternative ConceptsAnalysis of AlternativesSystem Level Requirements

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What is IPPD?Integrated Product/Process Development (IPPD) is a management methodology that incorporates a systematic approach to the early integration and concurrent application of all the disciplines that play a part throughout a systems life cycle (Technology for Affordability: A Report on the Activities of the Working Groups to the Industry Affordability Executive Committee, The National Center for Advanced Technologies (NCAT), January 1994)IPPD evolved out of the commercial sectors assessment of what it took to be world class competitive in the 1980sThe DoD has required IPPD and the use of IPTs where practical throughout the DoD Acquisition Process for Major Systems (DoD 5000.2R)Conduct of IPPD requires Product/Process Simulation using Probabilistic Approaches

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Traditional Design & Development Using only a Top Down Decomposition Systems Engineering Process

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Life Cycle Cost Gets Locked In Early for Complex Systems using only Systems Engineering Decomposition

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Concurrent vs Serial Approach

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IPPD Requires the Computer Integration of Product and Process Models andIPPD Requires the Computer Integration of Product and Process Models andTools for System Level Design Trades and Cycle Time ReductionTools for System Level Design Trades and Cycle Time Reduction

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Georgia Tech Generic IPPD Methodology

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Georgia Tech Generic IPPD MethodologyMethodology provides a procedural design (trade-off iteration) approach based on four key elements:Systems Engineering Methods and Tools (Product design driven, deterministic, decomposition approaches; MDO is usually based on analytic design approach) Quality Engineering Methods and Tools (Process design driven, nondeterministic, recomposition approaches; MDO is usually based on experimental design approach)Top Down Design Decision Process Flow (Provides the design trade-off process required for Complex Systems)Computer Integrated Design Environment(Information Technology driven to provide a collaborative interactive environment)Methodology has been implemented through Robust Design Simulation (RDS) for a number of applications

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Georgia Tech Graduate Program in Aerospace Systems Design & AnalysisInitiative kicked of in the early 1990s based on IPPD ApproachEducation executed in the School of Aerospace Engineering and research program executed through the Center for Aerospace Systems Analysis (CASA) and its two major Laboratories, The Aerospace Systems Design Laboratory (ASDL) and The Space Systems Design Laboratory (SSDL)Currently has approximately 140 graduate students with over 80 % U.S. citizens top students from top universitiesResearch Program currently at approximately $6M per year including four faculty and 15 research engineers, plus 100 GRAsProgram is built on probabilistic approaches for implementing IPPD through Robust Design SimulationGoal is to develop, verify and validate, in collaboration with industry and government, a Virtual Stochastic Life Cycle Design Environment (VSLCDE)

CASA/CERT/PLMC


A System Integration and Practice-Oriented M.S.Program in Aerospace Systems Design & AnalysisLegend:Core ClassesElective ClassesSummerSemester IISemester IDesign Methods/TechniquesISE/PLMCDevelopmentSpecialProjectSafety By DesignAerospace SystemsEngineeringDisciplinaryElectivesPropulsionSystemsDesignSystemsDesign IAppliedDesign ISystemsDesign IIAppliedDesign IIDesign Tools/InfrastructureAdvancedDesign Methods IAdvanced DesignMethods IIProductLife CycleManagementInternshipMathematics (2 Required) Other Electives

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MethodsStudentsAerospace Systems Design Integrated Education & Research PhilosophyFundingMethods FormulationSupports Basic ResearchImplementation of MethodsPartners:ONRNASAAFRLNRTCGovernmentIndustryRelevantProblemsData & ToolsPartners:GEAERRALMTASBoeingSikorskyFunding

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Complex System Formulation initially taught In Aerospace Systems Engineering using an Integrated Set of Simple Tools

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Current Complex System Formulation Projects in Aerospace Systems Engineering Course (Fall 2003)AIAA Graduate Student Missile Design Competition Multi Mission Cruise Missile Design AHS Student Design Competition for Design Certification Mountain Rescue Helicopter NASA Identified Complex System of Systems Problem: Future Air Transportation Architecture - A System of Systems ProblemNASA Specific Complex System Problem: Space Shuttle Derivative: What it takes to make it Safe and Flyable NASA Identified Complex System Problem: Two Stage Turbine Based Combined Cycle (TBCC) Space Access Launch Vehicle NASA Aerospace Vehicle Systems Technology Office Student Design: Quiet Supersonic Business Jet and Transport

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Current Complex System Formulation Projects in Aerospace Systems Engineering Course (Fall 2003)7.Homeland Security and Coast Guard Initiative: Feasibility of Accelerating the Integrated Deepwater System (IDS): A Network Centric Complex System 8.Missile System Technical Committee: Long Range Liquid Target Vehicle (LRLTV)9.University Student Design Competition: International Micro Aerial Vehicle (MAV) Competition 10.Complex System Formulation for: Boeing 7E7 Dreamliner Commercial Transport 11.Complex System Formulation for : Morphing UCAV Aircraft 12.NASA Aerospace Vehicle Systems Technology Office Student Design Competition for: Unmanned Air Vehicle Systems and Technologies: Replacement for Helios

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Roadmap to Affordability Through Robust Design SimulationObjectives:ScheduleBudgetReduce LCCIncrease AffordabilityIncrease Reliability. . . . .Customer SatisfactionSynthesis & SizingTechnology Infusion

Physics-Based Modeling

Activity and Process-Based ModelingSubject toEconomic & Discipline UncertaintiesImpact of New Technologies-Performance & Schedule RiskRobust SolutionsRobust Design SimulationSimulationOperational EnvironmentEconomic Life-Cycle AnalysisDesign & Environmental Constraints

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Synthesis & Sizingis the key for translating Mission into GeometryAerodynamicsEconomicsPropulsionSafetyAerodynamicsS&CPropulsionPerformanceManufacturingEconomicsSafetyStructuresManufacturingStructuresPerformanceConceptual Design Tools (First-Order Methods)Synthesis & SizingPreliminary Design Tools (Higher-Order Methods)Increasing Sophistication and ComplexityApproximating Functions Direct Coupling of AnalysesIntegrated Routines Table LookupS&C

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Aircraft Life Cycle Cost Analysis (ALCCA) - including Economic Cash Flow Analysis

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Risk & Uncertainty are Greatest at the FrontKNOWN-UNKNOWNSUNKNOWN-UNKNOWNSKNOWNSKnown Unknowns correspond to Risk and Known Probability DistributionUnKnown Unknowns correspond to Uncertainty and Unknown Probability Distribution

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The Five Step RDS Process YNNP(feas) < esmallProblem DefinitionIdentify objectives, constraints, design variables (and associated side constraints), analyses, uncertainty models, and metrics Determine System FeasibilityDesign Space ModelConstraint Fault TreeP(feas)FPI(AIS) or Monte CarloYExamine Feasible Space Constraint Cumulative Distribution Functions (CDFs)Design Space ModelFPI(AMV) or Monte CarloYTechnology Identification/Evaluation/Selection (TIES) Identify Technology Alternatives Collect Technology Attributes Form Metamodels for Attribute Metrics through Modeling & Simulation Incorporate Tech. Confidence Shape Fcns. Probabilistic Analysis to obtain CDFs for the AlternativesDecision Making MADM Techniques Robust Design Simulation Incorporate Uncertainty Models Technology Selection Resource Allocation Robust Design SolutionXi = Design VariableCi = Constraint

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Interactive RDS Environment

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Two Examples on Applicationof IPPD Through RDSSystem of Systems: CDSE Process for FCS FST Team in Phase IDerivative Program: F-18C Conversion to F-18E/G

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FST Process Methodologyfor FCS Phase I Concept Development & Systems Engineering

Methodology Incorporates IPPD Principles, QFD, Analysis, Engineering Simulation, Systems Engineering Tools, and Force-on-Force Simulation(This presentation does not reflect the current thinking of the FCS LSI)

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The Full Spectrum Team(FST):One of Four Teams in FCS Phase I2408W-C07

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Network Centric System Design of a Lethal BrigadeDiverse, overlapping fires and sensor coverage at all echelonsNear and far fires with area and precision effectsMultiple layered sensor coverageSensor systemsWeapon systemsBrigade echelonBattle GroupechelonAssault Battle UnitechelonARVInfantryCarrierCommandVehicleLOS/BLOSNLOSMortarMarsupialUGVVehiclesObjective Crew Served Weapon

ARVCommon MissileObjective Crew Served WeaponRSTA Battle UnitTypical Vehicle SensorsEO/IR sensor/sightlaser detectorsglint detectorsHUMMWV SUVcommand vehiclesomittedCommandVehicleScoutVehicleARVMarsupialUGVNLOSMortarRSTAVehicleTethered UAVCommandVehicleNetFiresMM RadarSmall UAVStinger BlkIIECommandVehicleCommandVehicleScoutVehicleARVMarsupialUGVNLOSMortarRSTAVehicleTethered UAVRSTA Battle Group9 ton variantsMedium UAVNLOS BGNLOSNetFiresCommandVehicleHQThe FST Brigade is designed to fight with precision fires and high lethalityExternalaugmentationExternalaugmentationBDE Air DefenseSoldier SystemsSoldierSystemsMM Radar

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Concept Development & Systems Engineering (CDSE) ProcessIncorporates key aspects of modern systems engineering approaches, and lends itself to iterationRequirements FlowdownEngineering Trades / AnalysisForce Effectiveness Modeling and SimulationRisk MitigationAllows full exploration of need identification and problem definition, concept development, and concept selectionprior to system definition and designFacilitates group work and utilizes modern software based tools Allows full incorporation of increasingly detailed simulation-based analyses and designs Smoothly extends throughout engineering and manufacturing phases

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Integration of QFD, Morph and Pugh Products Into CDSE Process HOWsQFD 1-4Morphological MatricesBestAlternativeTech. Alternative IdentificationSubjective Evaluation(through expert opinion,surveys, etc.)PreliminaryQFD Context RationaleHOWsWeightsMulti Attribute Decision Methodology

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Full Spectrum Team FCS ConceptDevelopment & Systems Engineering (CDSE) ProcessRecompositionDecompositionMOEsEndStartPugh ForceConceptsSelection MatrixForceEffectivenessSimulationsGuidance - QFD 1AUTLTRADOC DocsMNS

Force ConceptsAlternatives 1Alternative 1O&OSystemsCapabilitiesTechnology /SubsystemsOptionsGuidance - QFD (2-4)MissionsTasksFunctionsCapabilitiesSystemsSet 1Design GuidanceOrganizationalOperationalEngineeringConcept 2CharacteristicsConcept 1CharacteristicsA0031tPugh ForceConceptsSelection MatrixProcess is Paralleland Iterative675312ProductsDecisionSystems Concept IPTTechnology IPTRequirements IPTAll IPTsLegendSelected ForceConceptsMorph Matrices -Selection ofConsistent Setsof Systems andTechnologies4Missions /ScenariosTechnology Trees

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Focus on RequirementsFlowdown through QFDAUTLMissionsNational Imperatives /Army VisionAUTLMissionsAUTL Combat TasksCommanderCentricWarfareFunctionsAUTL Combat TasksSystemCapabilitiesSystem CapabilitiesTechnologiesHowWhatWhatWhatHowHowDetermine Force Characteristics to Perform FunctionsSelect Technologies and Combine into Candidate ConceptsBest Concepts Determined in Process That Trades Technologies, Concepts and RequirementsCriteria / MOEsCandidate ConceptsBestRequirementsIPTCommanderCentric FunctionsQFD4Co-Ownedwith Concepts IPTCDSE ITERATION 2Incorporate Four Detailed Mission ScenariosMorpho-logical Matrix

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Representative FCS Trade StudiesCommunications TradesPeer-to-Peer and Client-ServerIslands and BackbonesFrequency Bands and BandwidthQoS (Latency, Availability, Bandwidth)C2 TradesLegacy, New, Organic, JointInitiative and ControlPlatform TradesTracks and WheelsWeight Studies (16t, 9t, 6t)Modularity and Commonality StudiesHybrid and Conventional PropulsionTurbine and DieselWheel and Body MotorsActive and Passive SuspensionForce TradesUAVs and UGVsManned and UnmannedMounted snd DismountedBLOS / NLOS / LOS MixBU Size and CompositionWeapons TradesGuns and Missiles105 and 120 BLOS/LOS Precision and Area FiresSensor TradesRadar, EO/IR, and LadarSystems (UAV, UGV, Mast, Tethered)On Board and Off Board FusionATR and Clutter (False Alarms)Survivability TradesActive and PassiveCollective and IndividualLinks and NodesHMI TradesAutonomy, Responsibility, WorkloadCommonality, SimplicityMotion and ManeuverLogisticsOPTEMPO and SustainmentDeployment (Weights, Times, Pulses)Prognostics, Distribution, Log Support

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The Trade Space is Defined by a Full Spectrum of Scenarios

ThreatEnvironmentScenario 2SolutionMissionScenario 3SolutionTheFCSSolutionWhat is the D in performance?PotentialFCSSolutionSensitivity analysis will help drive to The FCS SolutionPotentialFCSSolutionScenario 1Solution

CASA/CERT/PLMC


Scenario Driven OMS/MP Development Composite OMS/MP(Scenario Specific Consolidation)FST concept robustness is tested against a broad range of missions & scenarios which gain validity from extensive quantitative & qualitative wargaming & analysis Force Concept Was Developed Iteratively & in Parallel With OMS/MP Refinements Four Initial OMSMPsFour ScenarioSpecific OMS/MPInputsChad ScenarioKorean ScenarioBosnia Scenario Desert Storm ScenarioScenario WeightingFST Scenarios: Forcing Function for Full Spectrum Force DevelopmentFull SpectrumForce ConceptsOperationalExaminationCASTFOREM WargamingJANUS Wargaming

Tabletop MAPEX

Force Concept(Version 4.1)Wargaming Feedback

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Evolution of FCS Force ConceptsConcept 1Heavy reliance on robotic ground vehicles More RSTA and assaultDeployable by current rotary wing aircraft Max vehicle weight 10 tonsClient-server information architectureEvolutionary comms and software systems Concept 2Heavy reliance on NLOS range engmts / UAVsSignificantly more payload volume Mostly 18-ton vehiclesPeer-to-peer information architectureBased on Small Unit Operations comms techNew software services

BaselineBLK I / BLK IIBlending of Concept 1 and 2--Robotics and NLOS engmts6-ton ARVs, 9-ton CVs, 16-ton max vehicle weightHelo vertical envelopment with smaller vehicles16 ton limit for C-130 deployment on unimproved runwaysHybrid information architecturePeer-to Peer with communication islandsBased on Small Unit Operations comms technology New software services2012 FUE2012 FUE2008 FUE BLK I2013 FUE BLK IIBLK I - Employ available weapons systems - Most vehicles manned - 9-ton vehicles become 16 tonBLK II Employ advanced weapons systems - Many advanced robotic systemsSame information and comms arch. as Baseline

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Concept Baseline Alternatives SummarySmaller Number of UAVsLarge Number of Modestly Capable Ground Sensors (ARVs)SensorsInformationLarger Number of UAVsSmall Number of Highly Capable Ground Sensors (RSTA Vehicle)Full Spectrum, but Weighted for Beyond the Red ZoneRobotic Netfires, Small UGVManned C2, Infantry Carrier, Direct Fire, RSTA and Short Range NLOSC-130 Transportable (

aerospace systems engineering the fuzzy front end

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