Date of Award

9-1991

Document Type

Thesis

Degree Name

Master of Science

First Advisor

Phillip E. Miller, PhD

Abstract

This research analyzed twenty-three maintenance constraint and three production output performance measures for nine SAC aircraft systems. SAS System for Elementary Statistical Analysis is used to analyze twenty-one months of ex post facto maintenance data. Correlation analysis is used to identify maintenance constraints that assist in explaining aircraft maintenance production capability. Forward stepwise regression is used to build predictive models of maintenance production capability for each of the nine aircraft systems. The twenty-three maintenance constraint measures are regressed against three productivity output measures: Mission Capable Rate, Total Not Mission Capable Supply Rate and Total Not Mission Capable Maintenance Rate. The regression models and validation results indicate regression models selection of maintenance constraints is not consistent between aircraft and prediction accuracy is erratic. The findings indicate performance measures may not be generalizable across all aircraft and key performance measures for one aircraft may not be important for another. Production capability assessment based on a few productivity measures generalized across all aircraft types may lead maintenance managers to formulate wrong conclusions about maintenance performance and capability. The validity of these findings is limited by the relatively small number of observations for each aircraft.

AFIT Designator

AFIT-GLM-LSM-91S-35

DTIC Accession Number

ADA246720

Comments

The author's Vita page is omitted.

Presented to the Faculty of the School of Systems and Logistics of the Air Force Institute of Technology, Air University, in Partial Fulfillment of the Requirements for the Degree of Master of Science

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