Abstract
PurposeForecasting techniques improve supply chain resilience by ensuring that the correct parts are available when required. In addition, accurate forecasts conserve precious resources and money by avoiding new start contracts to produce unforeseen part requests, reducing labor intensive cannibalization actions and ensuring consistent transportation modality streams where changes incur cost. This study explores the effectiveness of the United States Air Force’s current flying hour-based demand forecast by comparing it with a sortie-based demand forecast to predict future spare part needs.Design/methodology/approachThis study employs a correlation analysis to show that demand for reparable parts on certain aircraft has a stronger correlation to the number of sorties flown than the number of flying hours. The effect of using the number of sorties flown instead of flying hours is analyzed by employing sorties in the United States Air Force (USAF)’s current reparable parts forecasting model. A comparative analysis on D200 forecasting error is conducted across F-16 and B-52 fleets.FindingsThis study finds that the USAF could improve its reparable parts forecast, and subsequently part availability, by employing a sortie-based demand rate for particular aircraft such as the F-16. Additionally, our findings indicate that forecasts for reparable parts on aircraft with low sortie count flying profiles, such as the B-52 fleet, perform better modeling demand as a function of flying hours. Thus, evidence is provided that the Air Force should employ multiple forecasting techniques across its possessed, organically supported aircraft fleets. The improvement of the forecast and subsequent decrease in forecast error will be presented in the Results and Discussion section.Research limitations/implicationsThis study is limited by the data-collection environment, which is only reported on an annual basis and is limited to 14 years of historical data. Furthermore, some observations were not included because significant data entry errors resulted in unusable observations.Originality/valueThere are few studies addressing the time measure of USAF reparable component failures. To the best of the authors’ knowledge, there are no studies that analyze spare component demand as a function of sortie numbers and compare the results of forecasts made on a sortie-based demand signal to the current flying hour-based approach to spare parts forecasting. The sortie-based forecast is a novel methodology and is shown to outperform the current flying hour-based method for some aircraft fleets.
Highlights
Predicting future needs for aircraft spare parts is a critical issue within the United States Air Force (USAF)
This study showed that aircraft spare part demand is not always strongly correlated to the number of hours that are flown
37.1% of the F-16 items from 2004 to 2018 had demand that was more correlated to the number of sorties flown
Summary
Predicting future needs for aircraft spare parts is a critical issue within the United States Air Force (USAF). In the USAF’s complex multi-echelon, multi-indenture supply repair cycle, an inaccurate demand forecast may result in improper work schedules at the repair depots, incorrect operating stock levels at base supply warehouses and incorrect stock levels in aircraft deployment readiness kits. The consequences of such inaccuracy include a spare part. Accurate aircraft spare part forecasts empower the Air Force with the robustness and agility (Wieland and Wallenburg, 2013) required to meet its core competency in support of national defense
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