Building the Mobility Aircraft Availability Forecasting (MAAF) Simulation Model

The Mobility Aircraft Availability Forecasting (MAAF) model requirements definition research effort was initiated to help the United States Air Force, Air Mobility Command (AMC) answer the question, “How can we accurately predict mission capable (MC) rates?” Unfortunately, getting a perfect prediction of aircraft MC rates is not possible, either now or anytime in the foreseeable future. Fortunately, there are viable alternatives to prediction, and these alternatives are what the MAAF effort sought to determine. The mission of the AMC is to provide airlift, air refueling, special air mission, and aeromedical evacuation for the U.S. forces. AMC also supplies forces to theater commands to support wartime tasking. Currently, the AMC does not possess the capability to forecast, assess or evaluate alternatives impacting aircraft availability, which is key to the AMC decision-making process. Current methods utilize “after the fact” analyses and user opinion. This deficiency makes it difficult to perform quick, accurate, and effective analyses of potential limiting factors, and policy changes. This paper describes the MAAF simulation model built as the analytical component of a prototype decision support system aimed at providing AMC managers the dynamic, predictive tools needed to better forecast aircraft availability. This simulation featured new capabilities for mobility modeling to include dynamic definition of the airbases within a mobility system, a dynamic definition of the capabilities of the individual airbases within the mobility system, improved representation of the aircraft objects within the model, and a new approach to modeling aircraft maintenance to include a first ever motion of partially mission capable aircraft. The development efforts and experimental results are recounted in this paper.