fightless-fuel

204 Pages·2012·6.69 MB·English

Calhoun: The NPS Institutional Archive
DSpace Repository
Theses and Dissertations 1. Thesis and Dissertation Collection, all items
2013-06
More fightless-fuel: reducing fuel burn
through ground process improvement
Gerber, Chad A.; Clark, Jeremy A.
Monterey, California: Naval Postgraduate School
http://hdl.handle.net/10945/34667
Downloaded from NPS Archive: Calhoun
NAVAL
POSTGRADUATE
SCHOOL

MONTEREY, CALIFORNIA

MBA PROFESSIONAL REPORT

MORE FIGHT–LESS FUEL: REDUCING
FUEL BURN THROUGH GROUND
PROCESS IMPROVEMENT

By: Chad A. Gerber, and
Jeremy A. Clark
June 2013

Advisors: Michael Dixon,
Uday Apte,
Roberto Szechtman

Approved for public release; distribution is unlimited
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June 2013 MBA Professional Report
4. TITLE AND SUBTITLE 5. FUNDING NUMBERS
MORE FIGHT–LESS FUEL: REDUCING FUEL BURN THROUGH GROUND
PROCESS IMPROVEMENT
6. AUTHOR(S) Chad A. Gerber and Jeremy A. Clark
7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION
Naval Postgraduate School REPORT NUMBER
Monterey, CA 93943-5000
9. SPONSORING /MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSORING/MONITORING
N/A AGENCY REPORT NUMBER
11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy
or position of the Department of Defense or the U.S. government. IRB Protocol number ____N/A____.
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Approved for public release; distribution is unlimited A
13. ABSTRACT (maximum 200 words)
Aligning fiscal policies with energy conservation initiatives and operational requirements is vital to achieving a
positive and sustainable energy outlook for the United States Navy. The purpose of this study is to fill critical gaps in
current military aviation energy conservation research. To date, such research has failed to incentivize and reward
individual aviation squadrons to conserve. Commercial aviation uses collaborative decision-making (CDM) tools to
minimize costs associated with aircraft delays. Embracing a lean approach to operational management, the
commercial sector has refined communications between air carriers, airport operators, ground handlers, and air traffic
control. This study suggests applying commercial CDM frameworks to all of Naval Aviation to increase efficiency
and operational effectiveness. Specific analysis includes the impact of ground resource capacity management, airfield
demand analysis (slot arrival system) and demand management cost analysis on F/A-18 Hornet squadrons.

14. SUBJECT TERMS Energy conservation, slot management, demand analysis, truck refueling, hot 15. NUMBER OF
skid refueling, Simio, modeling and simulation, discrete event simulation, F/A-18, cultural change PAGES
203
16. PRICE CODE
17. SECURITY 18. SECURITY 19. SECURITY 20. LIMITATION OF
CLASSIFICATION OF CLASSIFICATION OF THIS CLASSIFICATION OF ABSTRACT
REPORT PAGE ABSTRACT
Unclassified Unclassified Unclassified UU
NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89)
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Approved for public release; distribution is unlimited

MORE FIGHT–LESS FUEL: REDUCING FUEL BURN THROUGH GROUND
PROCESS IMPROVEMENT

Chad A. Gerber, Lieutenant Commander, United States Navy
Jeremy A. Clark, Lieutenant Commander, United States Navy

Submitted in partial fulfillment of the requirements for the degree of

MASTER OF BUSINESS ADMINISTRATION

from the

NAVAL POSTGRADUATE SCHOOL
June 2013

Authors: _____________________________________
Chad A. Gerber

_____________________________________
Jeremy A. Clark

Approved by: _____________________________________
Michael Dixon, Lead Advisor

_____________________________________
Uday Apte, Support Advisor

_____________________________________
Roberto Szechtman, Support Advisor

_____________________________________
William R. Gates, Dean
Graduate School of Business and Public Policy
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MORE FIGHT–LESS FUEL: REDUCING FUEL BURN THROUGH
GROUND PROCESS IMPROVEMENT

ABSTRACT

Aligning fiscal policies with energy conservation initiatives and operational requirements
is vital to achieving a positive and sustainable energy outlook for the United States Navy.
The purpose of this study is to fill critical gaps in current military aviation energy
conservation research. To date, such research has failed to incentivize and reward
individual aviation squadrons to conserve. Commercial aviation uses collaborative
decision-making (CDM) tools to minimize costs associated with aircraft delays.
Embracing a lean approach to operational management, the commercial sector has
refined communications between air carriers, airport operators, ground handlers, and air
traffic control. This study suggests applying commercial CDM frameworks to all of
Naval Aviation to increase efficiency and operational effectiveness. Specific analysis
includes the impact of ground resource capacity management, airfield demand analysis
(slot arrival system) and demand management cost analysis on F/A-18 Hornet squadrons.
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TABLE OF CONTENTS
I. INTRODUCTION........................................................................................................1
A. BACKGROUND ..............................................................................................1
1. Department of Defense Energy Strategy ...........................................2
2. Naval Aviation Energy Conservation (Air-ENCON) .......................5
3. Incentivized Energy Conservation (i-ENCON) .................................7
B. CONTEXT ........................................................................................................9
1. Current Naval Aviation Organizational Structure ...........................9
2. Current Scheduling Process ..............................................................12
3. Type Wing Leadership ......................................................................15
C. BENEFITS OF THE STUDY .......................................................................17
D. METHODOLOGY OVERVIEW .................................................................19
II. LITERATURE REVIEW .........................................................................................21
A. AIRFIELD DEMAND MANAGEMENT ....................................................21
1. Slot Management and Compression Algorithms ............................21
2. Managing Aircraft Arrival Uncertainty ..........................................23
3. De-peaking through Slot Management ............................................25
4. Delay Propagation ..............................................................................27
B. COLLABORATIVE DECISION-MAKING (CDM) .................................29
1. Traffic Flow Management .................................................................30
2. Aviation Decision Support Systems ..................................................32
3. United Airlines DSS Case Study .......................................................34
C. AVIATION ENERGY CONSERVATION RESEARCH ..........................35
1. Cost-Benefit Analysis of F/A-18 Refueling Operations ..................36
2. Improving Refueling Operations Ashore.........................................37
3. Cold Truck and Hot Pit Refueling: Ratio Analysis ........................39
D. ADDITIONAL READING ............................................................................39
III. METHODOLOGY ....................................................................................................41
A. SIMULATION ...............................................................................................42
1. Objective .............................................................................................44
2. Level of Detail .....................................................................................45
B. APPROACH ...................................................................................................47
1. Collecting Input Data ........................................................................47
a. Planned Flight Data................................................................47
b. Actual Flight Data ..................................................................48
c. Cost Data .................................................................................49
d. Airfield Data ............................................................................51
e. Refueling Data ........................................................................52
2. Building the Model .............................................................................53
3. Validating the Model .........................................................................56
4. Conducting Experiments ...................................................................56
a. Slot Management Policy .........................................................56
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