Developing a Predictive for Unscheduled Maintenance Requirements on United States Air Force Installations

Abstract

The United States Air Force Civil Engineer community continually strives for more descriptive methods to explain the impact of funding decisions on future infrastructure conditions. This paper develops one such method by using linear regression and time series analysis to develop a predictive model to forecast future year man-hour and funding requirements for unscheduled maintenance. The results provide predictive models for up to a 5 year forecast with improved results for a 3 year outlook and routine maintenance calls.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2008
Accession Number
ADA488205

Entities

People

  • J. D. Norton
  • Matthew D. Kovich

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Business Administration
  • Civil Engineering
  • Data Analysis
  • Data Science
  • Databases
  • Engineering
  • Engineers
  • Failure Mode And Effect Analysis
  • Information Science
  • Literature Surveys
  • Maintenance
  • Maintenance Requirements
  • Personnel Management
  • Predictive Modeling
  • Regression Analysis
  • United States

Readers

  • Life Cycle Cost Analysis
  • Psychometric Testing or Psychological Assessment.
  • Strategic Security Studies