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Naval Aviation Squadron Risk Analysis Predictive Bayesian Network Modeling Using Maintenance Climate Assessment Survey Results Old Dominion University ODU Digital Commons Computational Modeling & Simulation Computational Modeling & Simulation Engineering Theses & Dissertations Engineering Winter 2014 Naval Aviation Squadron Risk Analysis Predictive Bayesian Network Modeling Using Maintenance Climate Assessment Survey Results Harry Michael Robinson Old Dominion University Follow this and additional works at: https://digitalcommons.odu.edu/msve_etds Part of the Risk Analysis Commons, and the Systems Engineering Commons Recommended Citation Robinson, Harry M.. "Naval Aviation Squadron Risk Analysis Predictive Bayesian Network Modeling Using Maintenance Climate Assessment Survey Results" (2014). Doctor of Philosophy (PhD), Dissertation, Computational Modeling & Simulation Engineering, Old Dominion University, DOI: 10.25777/99tt-9m41 https://digitalcommons.odu.edu/msve_etds/41 This Dissertation is brought to you for free and open access by the Computational Modeling & Simulation Engineering at ODU Digital Commons. It has been accepted for inclusion in Computational Modeling & Simulation Engineering Theses & Dissertations by an authorized administrator of ODU Digital Commons. For more information, please contact [email protected]. NAVAL AVIATION SQUADRON RISK ANALYSIS PREDICTIVE BAYESIAN NETWORK MODELING USING MAINTENANCE CLIMATE ASSESSMENT SURVEY RESULTS by Harry Michael Robinson B.S. May 1982, Pennsylvania State University M.S. December 1992, University of Tennessee A Dissertation Submitted to the Faculty of Old Dominion University in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPLY MODELING AND SIMULATION OLD DOMINION UNIVERSITY December 2014 Approved by: John A. Sokolowski (Director) K. Ash Anthony Pj. Ciavarelli (Member) -------------- Ariel Pinto (Merhber) Robert R. Safford (Member) UMI Number: 3662419 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Di!ss0?t&Ciori Piiblist’Mlg UMI 3662419 Published by ProQuest LLC 2015. Copyright in the Dissertation held by the Author. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 ABSTRACT NAVAL AVIATION SQUADRON RISK ANALYSIS PREDICTIVE BAYESIAN NETWORK MODELING USING MAINTENANCE CLIMATE ASSESSMENT SURVEY RESULTS Harry Michael Robinson Old Dominion University, 2014 Director: Dr. John A. Sokolowski Associated risks in flying have resulted in injury or death to aircrew and passengers, and damage or destruction of the aircraft and its surroundings. Although the Naval Aviation's flight mishap rate declined over the past 60 years, the proportion of human error causal factors has stayed relatively constant at about 80%. Efforts to reduce human errors have focused attention on understanding the aircrew and maintenance actions occurring in complex systems. One such tool has been the Naval Aviation squadrons’ regular participation in survey questionnaires deigned to measure respondent ratings related to personal judgments or perceptions of organizational climate for meeting the extent to which a particular squadron achieved the High Reliability Organization (HRO) criteria of achieving safe and reliable operations and maintenance practices while working in hazardous environments. Specifically, the Maintenance Climate Assessment Survey (MCAS) is completed by squadron maintainers to enable leadership to assess their unit’s aggregated responses against those from other squadrons. Bayesian Network Modeling and Simulation provides a potential methodology to represent the relationships of MCAS results and mishap occurrences that can be used to derive and calculate probabilities of incurring a future mishap. Model development and simulation analysis was conducted to research a causal relationship through quantitative analysis of conditional probabilities based upon observed evidence of previously occurred mishaps. This application would enable Navy and Marine Corps aviation squadron leadership to identify organizational safety risks, apply focused proactive measures to mitigate related hazards characterized by the MCAS results, and reduce organizational susceptibility to future aircraft mishaps. This dissertation is dedicated to my family, especially Anne and Andrew, for their support and understanding. I am grateful to my father, Captain “Fast Eddie” Robinson, U.S. Naval Reserve, who introduced me to Naval Aviation and my mother, Deborah Lowenthal Robinson who pinned on my wings of gold. The research conducted and detailed here within is for the men and women who ardently serve in the United States Navy and Marine Corps. Their determination and spirit is the bedrock of Naval Aviation which enables the capability to V ACKNOWLEDGEMENTS There are many individuals whom have guided me and supported the successful completion of this dissertation. I extend my sincere gratitude to my committee members for their counsel, advice, and patience on my research and editing of this manuscript. I am very appreciative for the advocacy and mentoring provided by my dissertation director, Dr. Sokolowski. My attendance at his dissertation defense in 2003 as the first doctoral candidate in Modeling and Simulation at Old Dominion University served to be very inspiring. A temporary duty assignment to the Aviation Safety Officer course at the Naval Postgraduate School in 1993 led to my introduction to Dr. Tony Ciavarelli. His instruction in Aviation Psychology served as a firm footing for this research, and his continued support was critical. John Scott, the Data Management and Services Division Head, U.S. Naval Safety Center, was absolutely essential for providing the double blinded data set for the Maintenance Climate Assessment Surveys and Aviation Mishap Summary Reports. Without his effort, accomplished above his normal duties, this research could not have been conducted. I am also appreciative to Rear Admiral George Mayer and Commander Michael Scavone from the Naval Safety Center for their support of this endeavor. I need to publicly recognize the counsel and advice received from both Missy Cummings, Ph.D., of Duke University and former Navy F/A-l 8 fighter pilot as well as Paul Weigand, PhD from the University of Central Florida, Institute of Simulation and Technology. Their suggestions, instructions, and encouragement were critical in starting this effort and bringing it to conclusion. TABLE OF CONTENTS LIST OF TABLES...................................................................................................................ix LIST OF FIGURES............................................................................................................... xiv 1. INTRODUCTION................................................................................................................. 1 1.1. PURPOSE.......................................................................................................................1 1.2. BACKGROUND...........................................................................................................1 1.3. PROBLEM STATEM ENT.........................................................................................8 1.4. THESIS STATEMENT............................................................................................... 9 1.5. RESEARCH QUESTIONS AND HYPOTHESES...............................................10 1.6. RESEARCH EXPECTATIONS............................................................................... 11 1.7. ASSUMPTIONS........................................................................................................ 11 1.8. SCOPE AND LIMITATIONS ................................................................................. 12 1.9. MOTIVATION ............................................................................................................13 1.10. RESEARCH CONTRIBUTION............................................................................14 1.11. RESEARCH APPROACH AND ORGANIZATION......................................... 14 2. LITERATURE REVIEW..................................................................................................16 2.1. DEFINITION OF TERMS........................................................................................16 2.2. INFLUENTIAL WORK............................................................................................22 2.3. RESEARCH CONTEXT...........................................................................................40 2.4. USE OF SURVEY RESULTS TO ASSESS ORGANIZATIONAL SAFETY............................................................................................................................... 40 2.5. DISCRETE EVENT SIMULATION MODELING TECHNIQUES.................43 3. METHODOLOGY............................................................................................................ 56 3.1. DESCRIPTION.......................................................................................................... 56 3.2. APPROACH................................................................................................................57 3.3. NAVAL AVIATION ORGANIZATIONAL CONSTRUCT AND PROCESSES......................................................................................................................
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