Navy Aircraft Carrier Gap Analysis

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					Navy Aircraft Carrier Gap Analysis
Justin Hornback & Robin Smith

          Decision Analysis and Its Applications to Systems Engineering
                                                     November 18, 2009
The Naval Aviation Enterprise (NAE) Carrier Readiness Team (CRT)
required holistic view for assessing strategic plans for future
aircraft carrier availability
  Problem: The NAE CRT required a holistic understanding of the risks associated with the looming aircraft
   carrier availability gap and how best to handle these risks.
    – Reduction in number of aircraft carriers from 11 to 10, planned retirement of USS Enterprise 2012
    – Demand for aircraft carrier deployment unchanged

  Several important questions needed to be addressed:
    – How does risk impact aircraft carrier operational availability (Ao)?
    – What are the cost and schedule impacts of risk?
    – How should mitigation dollars be prioritized against high-impact risks?
    – Is historical data useful for future planning?
    – How does one carrier in the enterprise(portfolio) impact the others?

  Previous attempts to address this problem were largely qualitative in nature and lacked a rigorous analytical
   framework and incorporated no uncertainty or risk.

  Applied the operational RISC-IQTM methodology to this problem to address these challenges.

      Constrained Resources and Emphasis on Efficiency Makes
   Understanding Risks Essential to Carrying Out Strategic Objectives

NAE Risk Methodology

                                                       Risk ID &
   Aircraft Carrier
                                                      (Initial Data Gathering &
                                                   Formulation; Risks Identified
                                                    from a Variety of Sources)

                                                     Historical Data
                                                        (Data Gathered,
                                                   Trends & Outliers Analyzed)

               Definitions                                                                Definitions
                 Constraints                         Stakeholder
                                                   Risk Modeling                           Constraints
                                                                                                               Survey Results
                      Assumptions   Stakeholder
                                                   Risk Modeling
                                                    Collaboration                               Objectives
                                                     (Key Inputs Discussed &                                           1   2   3   4

                      DRAFT                                                                    FINAL
    Cost                             Schedule                                      Cost                        Schedule
                          Risk                       Risk Mapping
                                                                                               Risk A

                                                  (Discrete Risks Mapped to Cost               Risk B
                                                   Elements & Schedule Tasks)

NAE Risk Methodology (cont’d)
              Cost                Risk   Schedule
      600                                                    Risk                                                                                                      1

      500                                                                                                                                                              0.8
      300                                                   Modeling

                                                                                                                                                                              Cumulative Probability
      100                                                                                                                                                              0.4
         2009 2011 2013 2015
            2010 2012 2014 2016                      (Simulations Run to Evaluate                                                                                      0.2

                                                        Risk Impacts on Cost &                                                                                         0
                                                                                                           34   32    30        28         26         24     22   20
                                                               Schedule)                                                                                               -0.2
                                                                                                                     Months Meeting Availability Objective

                                                       Translation to                  Ao Metrics
                                                     Availability Metrics

                                                     (Simulation Results Compiled,
                                                    Aggregate Ao Metrics Calculated)

                                                    Sensitivity Analyses
                                                      Risk Modeling
                                                      Risk Modeling
                                                      (Simulation Data Analyzed,
                                                    Excursions Run, “What If” Cases                                                                    Cost/
                                                              Developed)                                                                             Schedule

                                                     Recommendations                   Strategic Focus Areas:
                                                                                       - A, B, C Maintenance
                                                                                       Schedules During Months D,
                                                                                       E, F                     -
                                                        (Results Compiled &            System Dependency G
                                                    Recommendations Formulated)        - Bottleneck Point H
                                                                                       - Costs of I, J, K
                                                                                       - Stakeholder L

Schedules were overlaid upon another to create the “S” curve from
the Monte Carlo simulations   Likelihood (Percentage)
                                                            Months achieving desired
                                                            readiness level (48 max)

                                           Multiple Scenario generation

                                           Slope of S curve relates the amount
                                            of risk associated with a scenario

Key Challenges
  Client‟s first application of this methodology

  Politically charged environment
   – Potential conflict with previous Congressional Briefings

  Diverse stakeholders
   – World-wide implications

  Initial resistance due to client‟s unfamiliarity with the process
   – Report Card of performance

  Client used to stand-alone (i.e., stoplight chart) risk management
   that did not reveal the range of potential outcomes
   – Optimistic Schedules

  Complex environment with intricate interdependencies
   – Cyclical critical path
   – Resource constraints, industrial complex

Applying the RISC- IQ methodology supplied the client with
information required to make informed decisions

 This process was beneficial in that it..
   – Quantified the intuition of industry stakeholders
       • Specified availability of assets
   – Examined the root cause of schedule divergences
   – Allowed the client to build confidence in their „go forward‟ plan
   – Built a foundation from which further analyses can be conducted
        • Expansion outside of Aircraft Carriers
   – Generated a portfolio of risk models
        • Each risk model represented a unique compilation of data

     which created…

                       Quantifiable and Defendable Results

Aircraft Carrier Maintenance Stack-Up
  September 2009, four carriers in carrier maintenance at Northrop Grumman Shipbuilding, Newport News
   (NGSB NN) creating work capacity risks across all four carriers.
   – 36% of aircraft carrier fleet

  2004 CV/CVN Maintenance Availability Schedule projected 1 carrier at NGSB – September 2009
   – CVN 65 EDSRA

  Risk Analysis of 2004 CV/CVN Maintenance Schedule projects potential of 3 carriers - September 2009
   – CVN 65 EDSRA (>90%)
   – CVN 70 PSA/SRA (50%)
   – CVN 77 PSA/SRA (80%)
   – (% likelihood/potential of CVN maintenance event occurring at NGSB NN - September 2009)

  CVN 71 RCOH was not projected due to the 2004 scheduled RCOH start date of 11/2009. This date was
   moved up to 9/2/2009 during CVN 71 RCOH planning in 2007.


 Justin Hornback

 Robin Smith


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