Identifying Factors that Most Strongly Predict Aircraft Reliability Behavior

Abstract

This research analyzes twelve independent qualitative variables and one dependent qualitative variable for the C-17A Globemaster III. JMP, version 10, and Excel are used to analyze data from 1 October 2009 thru 31 August 2010. Contingency Table analysis and backward stepwise logistic regression are used to determine which factors most strongly predict C-17A aircraft reliability behavior. Qualitative data is extracted from the Global Decision Support System II, Logistics, Installations and Mission Support-Enterprise View, and the Core Automated Maintenance System for Mobility/G081. The model does generate tangible statistical values but with very little practicality and suggests aircrafts monthly hours, mission type, or component status have the weakest associations with departure reliability.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2013
Accession Number
ADA587533

Entities

People

  • Ryan L. Theiss

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Business Administration
  • Databases
  • Information Science
  • Information Systems
  • Knowledge Management
  • Logistics
  • Maintenance
  • Maintenance Management
  • Management Personnel
  • Military Science
  • Organizational Structure
  • Regression Analysis
  • Reliability
  • Short Takeoff Aircraft
  • Warfare

Readers

  • Aerospace Engineering
  • Computational Modeling and Simulation
  • Regression Analysis.