Providing a piece of the puzzle: insights into the aircraft availability conundrum

Q3 Decision Sciences
J. Ritschel, Tamiko L. Ritschel, Nicole B. York
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引用次数: 2

Abstract

Purpose Aircraft availability (AA) is a key metric for assessing operational readiness. The declining trend in AA is a documented concern for senior Air Force leaders. This paper aims to investigate the components of non-available time and subsequently focuses on the largest and fastest growing category: not mission capable maintenance unscheduled (NMCMU). Then, utilization of aircraft platforms is examined to determine the readiness benefits of increasing available hours. Design/methodology/approach Stepwise regression is conducted on a data set of 30 aircraft platforms, consisting of 542 observations from 1998 to 2017, to reveal drivers of NMCMU. Next, utilization of aircraft platforms is examined through regression and correlation analysis of aircraft platforms and sorties or hours flown. Findings Regression analysis reveals drivers of NMCMU include platform type, average age of aircraft, fleet size, breaks and cannibalization. These factors explain 80.6 per cent of the variance in the data set when predicting NMCMU. Additionally, the utilization results show that when more hours are made available, 5 per cent of each new hour is used for flying. Further analysis at the individual platform level finds a strong or moderate correlation between available hours and sorties flown for 93 per cent of the platforms. Originality/value Implications from the regression analysis demonstrate there are remedies to increase AA, but many of these remedies may be costly. The utilization analysis expresses the potential readiness benefits of increasing available hours.
提供了一个难题:洞察飞机可用性难题
飞机可用性(AA)是评估作战准备状态的关键指标。机管局的下降趋势引起了空军高级领导人的关注。本文旨在研究非可用时间的组成部分,随后将重点放在最大和增长最快的类别:非任务能力维护计划外(NMCMU)。然后,考察了飞机平台的利用率,以确定增加可用时数的战备效益。设计/方法/方法对1998 - 2017年30个飞机平台的542次观测数据进行逐步回归分析,揭示NMCMU的驱动因素。其次,通过飞机平台与飞行架次或飞行时数的回归和相关分析来检验飞机平台的利用情况。回归分析显示,NMCMU的驱动因素包括平台类型、飞机平均机龄、机队规模、停运和同类相拆。在预测NMCMU时,这些因素解释了数据集中80.6%的方差。此外,利用结果表明,当有更多的时间可用时,每增加一个小时,就有5%用于飞行。在单个平台层面的进一步分析发现,93%的平台的可用小时数和飞行架次之间存在很强或适度的相关性。原创性/价值回归分析的含义表明,有一些补救措施可以提高AA,但其中许多补救措施可能代价高昂。利用率分析表达了增加可用时间的潜在准备收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
5
审稿时长
12 weeks
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