Date of Award

Summer 9-2018

Access Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Aviation

Department

College of Aviation

Committee Chair

Haydee Muñoz Cuevas

First Committee Member

David A. Esser

Second Committee Member

Bruce A. Conway

Third Committee Member

Shari L. Frisinger

Abstract

This study examined the 12 preconditions for maintenance errors commonly known as the Dirty Dozen and applied them to actual incident and accident data provided by a participating airline (PA). The data provided by the PA consisted of Maintenance Event Reports (MERs) (reactive), Maintenance Operations Safety Assessment (MOSA) reports (proactive), and the results of the 2017 Maintenance Climate Awareness Survey (MCAS) (subjective). The MER and MOSA reports were coded by aviation maintenance subject matter experts (SMEs) using the 12 Dirty Dozen categories as the coding scheme, while the MCAS responses were parsed according to the precondition category they best represented. An examination and qualitative analysis of these data sets as they related to the Dirty Dozen categories answered the following research questions: (1) How does the reactive data (MER) analysis compare to the proactive (MOSA) analysis in terms of the Dirty Dozen? Do they echo similar Dirty Dozen categories, or do they seem to reflect different aspects of the Dirty Dozen? (2) What other preconditions for maintenance error become apparent from the analyses? What do they have in common? How complete is the Dirty Dozen? (3) What insights can be gleaned from the subjective report data (MCAS) with regard to maintenance personnel’s perceptions of the organization’s safety culture? The results revealed not only the presence of each Dirty Dozen category to some degree, but also the difference in sensitivity of the MER (reactive) and MOSA (proactive) to the 12 Dirty Dozen categories. Recommendations for practice and future research are discussed.

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