Performance measure of maintenance practices for F-16 fighter jets by data envelopment analysis

Abstract

Purpose

The purpose of this study is to provide the benchmarking guideline to improve managing maintenance man-hour in producing sorties of fighter jet aircraft in the Korean Air Force by measuring relative efficiency of aircraft in a fleet.

Design/methodology/approach

Using actual operational data from 2014 to 2018, this paper measures the relative efficiencies of aircraft by data envelopment analysis (DEA) model. To analyze the efficiencies across different operational units and among aircraft with different attributes, non-parametric statistical techniques and tobit regression are employed.

Findings

The overall management of maintenance man-hour turns out to be 63.2% efficient compared to the best practice. Operational unit possessing aircraft with different configurations shows the poorest performance implying efficiency depends on the complexity of job processes. Identification of aircraft on the best-practice frontier indicates the efficiency is closely related with the reliability of components and the age of aircraft.

Practical implications

Performance of aircraft maintenance has a tremendous impact on military readiness, utilization of work force, and the quality and safety of flight operations. This study confirmed there exists plenty of room for performance enhancement and presents a reference to find a balance in the performances of maintenance practices across different installations as well as among different types of aircraft.

Originality/value

Application of DEA to engineering systems has been limited in literature, especially in military operations. Thus, this study presents meaningful guidelines to which fleet manager can refer to when establishing strategic maintenance plans to balance the utilization of manpower.

Citation

Hur, M., Joo, S.-J. and Cho, J. (2022), "Performance measure of maintenance practices for F-16 fighter jets by data envelopment analysis", International Journal of Quality & Reliability Management, Vol. 39 No. 1, pp. 280-296. https://doi.org/10.1108/IJQRM-08-2020-0272