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Open Bernardo Dissertation - Final.Pdf The Pennsylvania State University The Graduate School College of Information Sciences and Technology HARD/SOFT INFORMATION FUSION IN THE CONDITION MONITORING OF AIRCRAFT A Dissertation in Information Sciences and Technology by Joseph T. Bernardo 2014 Joseph T. Bernardo The U.S. Government has a copyright license in this work pursuant to a Cooperative Research and Development Agreement with Naval Air Warfare Center Aircraft Division Patuxent River. Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy December 2014 The dissertation of Joseph T. Bernardo was reviewed and approved* by the following: David L. Hall Professor, College of Information Sciences and Technology Dissertation Advisor Chair of Committee Michael D. McNeese Co-director, General Electric (GE) Center for Collaborative Research in Intelligent Gas Systems (CCRNGS) Research Center, Professor, College of Information Sciences and Technology, Affiliate Professor of Psychology, Affiliate Professor of Learning and Performance Systems Guoray Cai Associate Professor of Information Sciences and Technology, Affiliate Associate Professor of Geography Richard L. Tutwiler Deputy Director, Center for Network-Centric Cognition and Information Fusion (NC2IF), Professor of Acoustics, Affiliate Professor of Information Sciences and Technology Carleen Maitland Director of Graduate Programs, Interim Associate Dean for Undergraduate and Graduate Studies, Associate Professor of Information Sciences and Technology, Affiliate Professor of the School of International Affairs *Signatures are on file in the Graduate School iii ABSTRACT The synergistic integration of information from electronic sensors and human sources is called hard/soft information fusion. In the condition monitoring of aircraft, the addition of the multisensory capability of human cognition to traditional condition monitoring may create a more complete picture of aircraft condition. A large data set from Naval Air Systems Command (NAVAIR) on maintenance of multi-mission vertical takeoff and landing (VTOL) 22 series B (MV-22B) aircraft provided the opportunity to explore the value of hard/soft information fusion in aviation maintenance. First, cognitive and functional frameworks were applied to hard/soft information fusion in the condition monitoring of aircraft. The steps of the Orasanu decision process model were applied to the macrocognitive functions and processes of the aviation maintainer. Emerging literature on hard/soft information fusion in condition monitoring was organized into the levels of the Joint Directors of Laboratories (JDL) data fusion process model, and the levels were applied to the process functions of aviation maintenance. Second, a research design was created for a retrospective analysis of sensor readings, human observations, and choices made in the maintenance of MV-22B aircraft. The data set from Decision Knowledge Programming for Logistics Analysis and Technical Evaluation (DECKPLATE), a NAVAIR database, provided information collected without the interference of interviewer bias. Third, a research methodology was created for studying hard/soft information fusion in aviation maintenance. Content analysis of the descriptive and corrective action narratives showed faults and aircraft components chosen for repair, replacement, fabrication, or calibration. Problem complexity was found to be an important factor. Additionally, expertise level also had an effect, and it was described through longitudinal trending. iv Fourth, the addition of human observation to sensor data was highly associated with the aircraft components chosen for action. Additionally, for complex problems, the addition of human observation to sensor data was significantly associated with improved outcomes. Descriptive statistics showed reduced diagnostic effort with human observation in complex problems. The improved outcomes and reduced diagnostic effort with human observation in complex problems may reduce operational maintenance cost, increase mission readiness, and increase flight safety. Keywords: hard/soft information fusion, condition-based maintenance, condition monitoring, aircraft maintenance, human factors, and decision-making v TABLE OF CONTENTS Contents LIST OF FIGURES ................................................................................................................. viii LIST OF TABLES ................................................................................................................... x LIST OF EQUATIONS ........................................................................................................... xi ACKNOWLEDGEMENTS ..................................................................................................... xii Chapter 1 Introduction ............................................................................................................ 1 Definitions ........................................................................................................................ 1 Sociotechnical Systems .................................................................................................... 2 Failure Modes and Effects Analysis (FMEA) and Failure Modes, Effects, and Criticality Analysis (FMECA) ....................................................................................... 5 FMEA and the JDL Model ............................................................................................... 8 Motivation ........................................................................................................................ 9 Research Questions .......................................................................................................... 10 Findings and Implications ................................................................................................ 11 Research Goal and Contributions ..................................................................................... 12 Roadmap for this Dissertation .......................................................................................... 13 Chapter 2 Background: The Context of Maintenance Work on MV-22B Aircraft ................ 16 Introduction to Naval Aviation ........................................................................................ 16 MV-22B Bell Boeing Osprey .......................................................................................... 19 How Aircraft Work .......................................................................................................... 24 Flight Crew ...................................................................................................................... 32 Pilots ................................................................................................................................ 33 Warrant Officers .............................................................................................................. 34 Maintainers....................................................................................................................... 35 Aviation Maintenance ...................................................................................................... 36 Chapter 3 Literature Review ................................................................................................... 40 Macrocognition ................................................................................................................ 40 Machines Need People to ... but People Need Machines to ... ......................................... 42 Condition-Based Maintenance Plus ................................................................................. 44 Hard/Soft Information Fusion .......................................................................................... 47 JDL Data Fusion Process Model ...................................................................................... 49 The JDL Model and CBM+ ...................................................................................... 50 Organizing the Literature on Hard/Soft Fusion in Condition Monitoring into Levels of the JDL Data Fusion Process Model .............................................................. 53 Level 2/3 Human-Influenced Diagnostics and Prognostics ..................................... 53 vi Level 2/3/5 Integrated Machine- and Human-Based Diagnostics and Prognostics ........................................................................................................... 54 Level 5 Human Information Processing ................................................................... 55 Alternative Information Fusion Frameworks ................................................................... 56 Summary .......................................................................................................................... 58 Chapter 4 Cognitive and Functional Frameworks .................................................................. 61 Cognitive Framework for Hard/Soft Information Fusion in the Condition Monitoring of Aircraft.................................................................................................... 61 Functional Framework for Hard/Soft Information Fusion in the Condition Monitoring of Aircraft.................................................................................................... 64 Chapter 5 Research Design ..................................................................................................... 68 Philosophy .......................................................................................................................
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