An Evaluation of Aircraft Maintenance Performance Factors in the Objective Wing

Abstract

Prior to 1992, organizational maintenance was aligned under a - separate maintenance organization. In 1992, the Air Force restructured into Objective Wings with organizational maintenance aligned under the flying squadrons. This study looks at the impact of this reorganization on maintenance performance factors. The researchers developed maintenance performance models using regression and principal component analysis. Mission Capable Rate and Total Not Mission Capable Maintenance Rate are used as dependent variables. A comparison of key maintenance performance indicators and model predictions before and after the reorganization is accomplished. Based on the results of this analysis, the researchers conclude that there is significant improvement in all dependent variables, model predictions of these dependent variables and improvement in some of the independent variables. Improvement occurred after organizational structure changed, however, other factors not included in the models such as the stand-down of the Alert Force may also contribute to this improvement. Maintenance Management, Aircraft Maintenance, Regression Analysis Air Force Organizations, Principal Component Analysis

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1993
Accession Number
ADA276010

Entities

People

  • Margaret M. Ranalli
  • Mark A. Gray

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircraft Maintenance
  • Aircrafts
  • Business Administration
  • Data Mining
  • Data Science
  • Factor Analysis
  • Information Science
  • Knowledge Management
  • Maintenance
  • Management Personnel
  • Organizational Structure
  • Regression Analysis
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Surveys

Fields of Study

  • Business

Readers

  • Aerospace logistics and air mobility.
  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.