Explanatory Factors for Marine Corps Aviation Maintenance Performance

Abstract

The thesis identifies F/A-18 squadron characteristics that are important predictors of maintenance performance and draws insights on the linkage between the utilization of engineering and technical services (ETS) and maintenance performance measures. Statistical analysis is conducted to identify squadron characteristics that have a detectable contribution to the variability of the performance measure man-hours per maintenance action, and how much additional variability is explained by the squadron that is not accounted for by the squadron characteristics already considered. Thirty months of data were collected for thirteen active duty Marine Corps F/A-18 squadrons. Regression is used to model man-hours per maintenance action as a linear combination of explanatory variables that describe the squadrons in terms of manpower, inventory, and ETS metrics. The test for significance indicates that the model developed in this study is highly likely to have better explanatory power than an intercept-only (average) estimate of the response variable. The study concludes with recommendations for data collection methods that would facilitate the correlation of squadron characteristics to ETS utilization. Critical to the success of this approach is the linkage of ETS utilization to specific squadron maintenance activities, and the development of methods to quantify maintainer training currency.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2005
Accession Number
ADA439388

Entities

People

  • Gregory L. Chesterton

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Aircraft Equipment
  • Airframes
  • Data Science
  • Databases
  • Fighter Aircraft
  • Information Science
  • Logistics
  • Maintenance
  • Maintenance Management
  • Maintenance Personnel
  • Management Personnel
  • Military Aviation
  • Naval Aviation
  • Personnel Management
  • Regression Analysis
  • Surveys

Readers

  • Aviation Science / Aeronautics.
  • Regression Analysis.
  • Systems Analysis and Design