Purpose – The purpose of this research is to explore the utility of autonomous transport across two independent airframe maintenance operations at a single location. Design/methodology/approach – This study leveraged discrete event simulation that encompassed real-world conditions on a United States Air Force flight line. Though the Theory of Constraints (TOC) lens, a high-demand, human-controlled delivery asset is analyzed and the impact of introducing an autonomous rover delivery vehicle is assessed. The authors’ simulations explored varying numbers and networks of rovers as alternative sources of delivery and evaluated these resources’ impact against current flight line operations. Findings – This research indicates that the addition of five autonomous rovers can significantly reduce daily expediter delivery tasks, which results in additional expertise necessary to manage and execute flight line operations. The authors assert that this relief would translate into enhancements in aircraft mission capable rates, which could increase overall transport capacity and cascade into faster cargo delivery times, systemwide. By extension, the authors suggest overall inventory management could be improved through reduction in transportation shipping time variance, which enhances the Department of Defense’s overall supply chain resilience posture. Originality/value – When compared against existing practices, this novel research provides insight into actual flight line movement and the potential benefits of an alternative autonomous delivery system. Additionally, the research measures the potential savings in the workforce and vehicle use that exceeds the cost of the rovers and their employment.
Journal of Defense Analytics and Logistics
Stanton, M. A., Anderson, J., Dickens, J. M., & Champagne, L. (2022). Supply chain resilience: how autonomous rovers empirically provide relief to constrained flight line maintenance activities. Journal of Defense Analytics and Logistics, 6(1), 2–20. https://doi.org/10.1108/JDAL-10-2021-0013