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Current aircraft forecasting methods of the Air Mobility Command (AMC) Directorate of Logistics rely on the experience of personnel and lead to after the fact, labor-intensive analysis. These deficiencies led AMC to the development of a Mobility Aircraft Availability Forecasting (MAAF) model. The purpose of the MAAF model is threefold: predict aircraft availability in order to provide the Tanker Airlift Control Center (TACC) with a forecast of aircraft that will be available for AMC mission requirements, provide what if capabilities that analyze the effects of tasking and policy changes, and to provide foresight into problems associated with aircraft availability (Briggs, 2003b). This research uses Arena simulation to model C-17 aircraft generation at a major enroute location to determine how significant the factors of crew chief manning and spares levels affect aircraft throughput and turn-times. From the simulation, ANOVA statistical techniques are applied to determine factor significance. In addition, a hierarchical structure of aircraft generation is generated to include the variability of unscheduled maintenance actions. This provides a more precise analysis of expected turn-time duration, which leads to overall throughput of the system. Ultimately, this research provides an key input to the MAAF project that will enable AMC to predict aircraft availability and provide the TACC with a monthly forecast of the number of aircraft that will be available to fulfill AMC mission requirements.