Modeling Combat Aircraft Training and Readiness
(Room S320F)
29 Nov 17
4:30 PM
-
5:00 PM
The simulation of combat aircraft operations has been evolving for over thirty years, with myriad applications, ranging from optimizing aircraft maintenance policies to predicting a developmental aircraft’s combat reliability. The problem asks the modeler to represent multiple, independent aircraft—sometimes operating from different bases—and the required aircraft maintenance that follows each flight.
Methods vary in their complexity, but most have measured success in terms of total sorties generated or flight hours flown. In other words, all sorties are considered equally valuable. While this assumption has some applications, a combat squadron spends most of its time and resources on advanced training (or, “workup”) for combat, which requires pilots to execute a defined sequence of training events. Success, in other words, requires more than simply generating a sortie; the squadron must generate a sortie, with the right pilot, flying the right event, at the right time. This presents a dilemma: some sorties have more training value than others, but they all incur the same maintenance cost. Squadron leaders manage this dilemma through policies and priorities that seek to optimize training and minimize maintenance. Complicating matters are pilot turnover and resources that are shared between multiple squadrons.
This paper examines the squadron workup process within the requirements and constraints of the Marine Corps F/A-18 Hornet community—a particularly complex case. The model makes significant additions to previous successful models by adding the event dependency that characterizes the workup process, as well as an agent-based element that incorporates the priorities made by the squadron leadership. The model is driven by and evaluated against ten years of detailed flight, failure, and maintenance statistics, and offers the ability to more accurately evaluate the effects of management priorities, resource allocations, and policy decisions—such as the rate of pilo