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Navy Aircraft Carrier Gap Analysis

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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

INCOSE/SCEA

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





1

NAE Risk Methodology



Risk ID &

Foundational

Aircraft Carrier

Operations

Efforts

(Initial Data Gathering &

Formulation; Risks Identified

from a Variety of Sources)





Historical Data

Analyses

(Data Gathered,

Trends & Outliers Analyzed)



Definitions Definitions

Constraints Stakeholder

Risk Modeling Constraints

Survey Results

Objectives

Assumptions Stakeholder

Risk Modeling

Collaboration Objectives

Assumptions

Survey

(Key Inputs Discussed & 1 2 3 4









Reviewed)

DRAFT FINAL

Cost Schedule Cost Schedule

Risk Risk Mapping

Risk A



(Discrete Risks Mapped to Cost Risk B

Elements & Schedule Tasks)









2

NAE Risk Methodology (cont’d)

Cost Risk Schedule

600 Risk 1

FY08$M









500 0.8

400

300 Modeling









Cumulative Probability

0.6

200

100 0.4

0

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

Drivers





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









3

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









4

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









5

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







6

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.









7

Questions?



Justin Hornback

hornback_justin@bah.com



Robin Smith

smith_robin_k@bah.com









8


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