Crew time is one of the most valuable and limited resources during long-duration space missions. Crew time requirements fluctuate depending on variations in crew performance. The limited number of crewmembers, resources, and the myriad of tasks to be performed leave a tight schedule for crewmembers during long-duration space missions. This schedule needs to account for potential interventions (stress events) that may alter predicted performance and thus scheduling. A dynamic crew model using a stochastic Auto Regressive Integrated Moving Average (ARIMA) model of interrupted time series was developed to account for the effects of potential stress events on crew performance. This model aids in estimating crew time requirements for varying mission scenarios and for evaluating stress event effects on crew performance.
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