A Feasibility Study of the Collection of Unscheduled Maintenance Data Using Statistical Sampling Techniques.

Abstract

This thesis explores the feasibility of using statistical sampling techniques in lieu of a census to collect Air Force maintenance (MDC) data. A practical sampling methodology is identified and the sample size required to collect data with a specified degree of statistical precision is illustrated. The variable cost of MDC data collection and processing is also identified. Using the F-16A Fire Control System on the aircraft at one base as an example, the potential cost and effort savings resulting from sampling are evaluated. The sampling concept is based on a simple random sample of aircraft, by serial number, with full data collected on all aircraft in the sample. The sampling plan is designed to estimate the base level monthly total unscheduled maintenance manhours at the two digit work unit code level, with 10 percent relative precision and 90 percent confidence. The methodology used to estimate the variable cost of collecting and processing MDC data records is limited to base and Air Force Logistics Command (AFLC) levels. Base level costs considered are the opportunity cost of a maintenance technician's time to enter one MDC record into an automated system terminal, and the cost of computer processing and transmission of data to AFLC. AFLC costs considered are the machine time charges assessed against the DO56 Product Performance System. In the single system studied, the variability in monthly unscheduled manhours per aircraft was found to be high.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1985
Accession Number
ADA161448

Entities

People

  • Robert A. Heinlein

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Business Administration
  • Control Systems
  • Data Analysis
  • Data Science
  • Databases
  • Fire Control Systems
  • Information Processing
  • Information Science
  • Logistics
  • Maintenance
  • Maintenance Management
  • Management Personnel
  • Personnel Management
  • Statistical Analysis
  • Statistical Sampling

Readers

  • Aerospace logistics and air mobility.
  • Computational Modeling and Simulation
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.