Symposium Presentation (for Acquisition Research Program)Symposium PresentationAcquisition Research ProgramApproved for public release; distribution is unlimited

DeLaurentis, Daniel

Mane, Muharrem

Calhoun, Institutional Archive of the Naval Postgraduate School

Calhoun: The NPS Institutional ArchiveReports and Technical Reports All Technical Reports Collection2011-05-12Capability and Development TimeTrade-off Analysis in Systems-of-SystemsMuharrem Manehttp://hdl.handle.net/10945/33693School of Aeronautics and AstronauticsCapability and Development Time Tradeoff Analysis in Systems-of-SystemsMuharrem Mane Email: mane@purdue.eduDaniel DeLaurentisEmail: ddelaure@purdue.eduSponsor: NPS Acquisition Research ProgramSchool of Aeronautics and AstronauticsO iverv ew• Development of SoS is complex– Numerous interdependencies RequirementsCapability – Changing over time• SoS capability comprised of t bilitiSystems / Programssys em capa es– Interdependent system requirements– Legacy  systems• Goal: make the AoA smarter in pre-acquisitionPotential capability vs expected–   .  development• A high-level approach can aid in th l d l t t d2e ear y eve opmen  s ages an  requirement definition and allocationSchool of Aeronautics and AstronauticsResearch QuestionsGiven a network of systems•      – How do system-specific (node) characteristics impact the successful development of SoS capability?H d t i t d d i i t th– ow o sys em n er epen enc es mpac  e development process?• How do disruptions propagate in complex networks of interdependent s stems? y• How can we quantify the cascading effects of development risk?• Focus of previous year research• What is the tradeoff between SoS capability and expected development time?3– Key tradeoff in analysis of alternatives (AoA)– Focus of this year’s workSchool of Aeronautics and AstronauticsMethods of Approach• Simulation Approach– Developing Computational Exploratory Model (CEM)– Discrete-event, stochastic simulation based on steps in DoD SoS SE Guide– First-order modeling of capabilityA l ti l A h T22, D22• na y ca  pproac– Based on probability and network theory– Analysis of expected delay propagation 2T12 D12T23, D23T33, D33T21, D21 3T31, D314for given SoS network configurations 1FT11, D11, T3F, D3FT1F, D1FT2F, D2FSchool of Aeronautics and AstronauticsCurrent Research Efforts• Analysis of alternatives in the context of De elopment time– v  – Capability level• First-order capability estimation d lmo e• Capability / development time tradeoffs for alternative iti f Ai b LDefense Industry Daily, 2009Capability(intercept ballisticmissiles)SoS Capabilitycompos ons o  r orne aser system– Categories of components comprise the capabilityRequirement(detect, track,target, destroy)Requirements (requirement capability)Systems(system capability)system-A(Adaptive Optics)system D5  – Proof of concept applicationsystem-B(aircraft)system-C(COIL)-(Detection System)School of Aeronautics and AstronauticsDevelopment Model (CEM)• Discrete-event, stochastic simulation( ) ( )( )irimriR isys βα ,1, −=• Disruption occurrence and propagation• System risk (Rsys) as a function Capability(intercept ballisticmissiles)Requirements SoS Capabilityof system readiness-level (m) – Similar to TRL metric and SRL metric proposed by Sauser et al.Requirement(detect, track,target, destroy)(requirement capability)Systems(system capability)• Impact of disruptions a function of – Network topology and strengthsystem-B(aircraft)system-A(Adaptive Optics)system-D(Detection System)6     of system interdependenciessystem-C(COIL)School of Aeronautics and AstronauticsCapability Modeling• Assume desired ABL capability to “disable threat from 600 km (slant range)”C t i f t d– a egor es o  sys ems an  requirements create different capability levels• Identify functions that compriseDefense Industry Daily, 2009    capability• Identify systems that perform each functionDisable missile from 600 km• First-order quantification of capability– Aircraft system indirectly id d (h t f thDetect & Track MissileEngage MissileDisable MissileD t ti & COIL AO7cons ere  os  o  o er systems)e ec on  Tracking System Beam Aircraft SystemSchool of Aeronautics and AstronauticsCapability Contributors• Detection and tracking system– Detects threat and generates track to enable engagement– Capability contribution: detection time, TdDisable missile from 600 km R• Higher detection time reduces available dwell-time, te• Adaptive Optics (AO) system– Accounts for atmosphericDetect & Track MissileEngage MissileDisable MissileDetection & Tracking SystemCOIL Beam AircraftAOSystem   disturbances to deliver maximum laser power to target– Capability contribution: beam quality diff ti li it d b th t i te D, P, λ bq, SRrac on m e , q, a  ncreases Strehl ratio, SR• COIL beam power– Laser power to disable a liquid fuel• Fc: energy required to disable target• D: laser beam diameter• λ: laser beam wavelength• R: slant range8       ICBM – 32 MJ/m2 required (Fc)• P: laser power• te: dwell-time• SR: Strehl ratioSchool of Aeronautics and AstronauticsABL Capability SpaceP=5 MW P=4 MWP=3 MWABL capability = f(beam quality, laser power, available dwell-time)1.21.4600 km)System requirements;0.60.81y (normalized to 6  Will drive development time 100.20.4ABL capability91.21.41.61.8 1011121314detection time, Tdbeam quality difraction limited, bqSchool of Aeronautics and AstronauticsAnalysis of Alternatives Results• 81 possible solutions240    • Three alternatives for each constituent system• Non-dominated solutions result in a Pareto frontier• Clear tradeoff between capability and expected development timeHi h bilit i210220230[time units]Solution 6Solution 7– g er capa y requ res higher development time (result of non-mature technology)• Seven solutions identified190200opment Time Solution 3   here– Combination of new and existing systems (high and low capability)160170180xpected DevelSolution 1Solution 510 250 300 350 400 450 500 550 600140150ABL Capability (slant range [km])Ex Solution 2 Solution 4 School of Aeronautics and AstronauticsObservations• No single optimal solution 230240its] Solution 7   – Tradeoff between capability and development time • Non-dominated solutions are 190200210220ment Time [time unSolution 3Solution 6   comprised of legacy and new systems– Development model captures 150160170180Expected DevelopmSolution 1Solution 5   higher order impact of interdependenciesD&T Aircraft COIL beam ABL Capability Expected250 300 350 400 450 500 550 600140ABL Capability (slant range [km]) Solution 2 Solution 4Solution  System  System   System AO System  [slant range, km] Completion Time [time units] 1 STSS new system Alternative-1 Alternative-3 285 152 2 STSS new system Alternative-1 Alternative-2 307 153 3 UAV new system Alternative-1 Alternative-2 371 157 4 UAV new system Alternative 1 Alternative 1 402 16011   - -5 new system new system Alternative-1 Alternative-1 461 170 6 new system new system Alternative-2 Alternative-1 533 185 7 new system new system Alternative-3 Alternative-1 596 215  School of Aeronautics and AstronauticsConclusions• CEM and capability modeling enables analysis of alternatives early in development process– CEM captures cascading effect of developmental disruptions• Enabling enhanced selection of constituent systems and requirements• Analytical tools early in acquisition and      development phase enhance decision-making– Build intuition and guide acquisition efforts12     School of Aeronautics and AstronauticsFuture Work• Analytical model for measuring system development      performance– Indicators of good network structure– Identification of features that can lead to problems or         success• Requirement evolution is at root of most development issues– Want more / better capability– Get schedule and cost overruns • Continue development of a capability module for CEM       – Analysis of impact of requirement dependencies on both development and capability– Can we “design” a controller for requirement evolution?13       • Ability to measure impact of requirement evolution on system (and SoS) development School of Aeronautics and AstronauticsM k P ti N t kar ov erspec ve on e wor  Interdependencies• Aggregation of system-specific disruptions to generate network-level performance metric– Focus on cascading effect of disruptions– Identify network characteristics that increase probability of project successFABACCFP Bypass ground obstaclesCapabilities / Functional AreasActivitySystems /ProgramsMMT database contains Programmatic informationi.e. programmatic system interdependenciesF‐18    • Proposed approach gives ability to– Rank constituent systems based on criticality/vulnerability duringDestroy movingaerial targetsE2‐CJLENSDetermineCFFICECPAC3Link 16WIN‐TSLAMRAAMNavy Std. MissileDDG 1000SSGNEA‐18GF‐35CV‐22JTRSLCSP‐8DDG 51SSN‐774  development– A network-level metric enables comparison of networks (that can varyx2x3D22=1,T22D =2 TD21=2, T21 D13=2,T1314      with time)x1D11=2, T1133 , 33D31=1, T31xFDF1=0, TF1DF3=0, TF3DF2=0, TF2School of Aeronautics and AstronauticsNetwork-Level Metric• Compute expected accumulated delay– Measure of network performance• Measure of system criticality / vulnerability 0 20.250.30.35ty function      when contributions from each system are ranked• Compute variation about the 0.050.10.15.probability densi    expectation– Measure of the risk associated with the estimated network performance0 5 10 15 20 250time-step, n0.80.91unction  0.40.50.60.7mulative probability fu( ) ( ) ( )( )( ) ( )ncxnF btosubjectnAn j ζζζζ===+0|0       1150 5 10 15 20 250.20.3time-step, ncu( )( )[ ] ∑∞==10|nnj bncAxnFESchool of Aeronautics and AstronauticsThank You 16School of Aeronautics and AstronauticsBack-Up Slides 17School of Aeronautics and AstronauticsContributors to Capability: Detection & TrackingCapability assumptions•   – 170 seconds of boost-time (engagement window)– Desired raid size of 12 missiles: determines required dwell-time• Ideal detection time is 10 seconds; allows interception of 12 missiles • Development assumptionsNormalized TRL indicates initial readiness level–     -• Determines probability of disruptions during developmentDetection Alternative Detection time [sec] TRL Level Initial Readiness-Level [mo(i,r)] New System 10 6 0.67 UAV 11 8 0.8918  STSS 12 9 1.00 School of Aeronautics and AstronauticsContributors to Capability: Adaptive Optics• Capability assumptions– Only a function of the beam quality diffraction limit, bq– Ideal beam quality diffraction limited is 1 2      .• Development assumptions– Normalized TRL indicates initial readiness-level• Determines probability of disruptions during developmentDetection Alternative Beam Quality Diffraction Limited TRL Level Initial Readiness-Level [mo(i,r)] Alternative 1 1.2 2 0.22 Alt ti 2 1 3 3 0 3319erna ve  .  .Alternative 3 1.4 5 0.56 School of Aeronautics and AstronauticsContributors to Capability: COIL beam• Capability assumptions– Published “achievable” COIL beam power of 3 MW• Development assumptions– Normalized TRL indicates initial readiness-level• Determines probability of disruptions during development– Published TRL level of 4 for a power of 3 MWCOIL beam Alternative Power  [MW] TRL level Initial Readiness-Level [mo(i,r)] Alternative 1 3 4 0.44 Alternative 2 4 3 0 3320  .Alternative 3 5 1 0.11 School of Aeronautics and AstronauticsSystem Risk and Interdependencies• Candidate families of systems can have different combinations of system-         risk and interdependency strengths– These characteristics have different impact on development success40e [time-steps]Strongly dependent systems3035mentation time10 150.22025pected implem2100.20.40.60.800.050.1.dependency strength, S(i,j)maximum inherent risk, α iexpIndependent systems School of Aeronautics and AstronauticsSystem Risk and Interdependencies• Candidate families of systems can have different       combinations of system-risk and interdependency strengths• These characteristics have different impact on development success140e-steps]Independent systems Strongly dependent systems0 60.70.80.9 m(i,r)sys-Asys-Bsys-C3035tation time [time0.30.40.5.Readiness-level,0.22025cted implement220 10 20 30 40 5000.10.2Implementation time-step 00.20.40.60.8100.050.10.15dependency strength, S(i,j)maximum inherent risk, α iexpeSchool of Aeronautics and AstronauticsCapability Modeling• Assume desired ABL capability to “disable threat from 600 km (slant range)”C t i f t t– a egor es o  sys ems crea e different capability levels• Identify functions that comprise capabilityDefense Industry Daily, 2009• Identify systems that perform each function• First-order quantification of Disable missile from 600 km Rcapability– Aircraft system indirectly considered (host of other t )Detect & Track MissileEngage MissileDisable MissileD t ti & COIL AO23sys ems e ec on  Tracking System Beam Aircraft Systemte D, P, λ bq, SRSchool of Aeronautics and AstronauticsDisable missile from 600 kmDetect & Track MissileEngage MissileDisable MissileDetection & Tracking SystemCOIL Beam AircraftAOSystem24

Capability and Development Time Trade-off Analysis in Systems-of-Systems

Proceedings Paper (for Acquisition Research Program)Capability-based acquisition has led to the simultaneous development of systems that must eventually interact within a system-of-systems (or major sub-systems that must integrate on a single platform).  The necessary interdependencies between systems also generate complexity and can increase development risk. Trades between capability and risk are essential during analysis of alternatives in pre-acquisition phases. For example, while legacy assets can potentially provide a certain level of capability with relatively low risk, their eventual capability may be restricted because of some specific characteristic or inherent rigidity.  These features create a trade-off space between development risk and capability potential of a system.  Existing tools for such trades can be cumbersome and non-intuitive when complexity is high.  The authors'' prior work has developed a Computational Exploratory Model to simulate the development process dynamics for these complex networks of systems intended for a system-of-systems capability.  The progress documented in this paper couples the computational model with a capability module applied to the Airborne Laser (ABL) system and presents an exemplary analysis of alternatives by comparing expected development time and capability level under certain probabilities of disruption.Acquisition Research ProgramApproved for public release; distribution is unlimited

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Capability and Development Time Trade-off Analysis in Systems-of-Systems

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