Comparison of Spares Logistics Analysis Techniques for Long Duration Human Spaceflight

As the durations and distances involved in human exploration missions increase, the logistics associated with the repair and maintenance becomes more challenging. Whereas the operation of the International Space Station (ISS) depends upon regular resupply from the Earth, this paradigm may not be feasible for future missions. Longer mission durations result in higher probabilities of component failures as well as higher uncertainty regarding which components may fail, and longer distances from Earth increase the cost of resupply as well as the speed at which the crew can abort to Earth in the event of an emergency. As such, mission development efforts must take into account the logistics requirements associated with maintenance and spares. Accurate prediction of the spare parts demand for a given mission plan and how that demand changes as a result of changes to the system architecture enables full consideration of the lifecycle cost associated with different options. In this paper, we utilize a range of analysis techniques – Monte Carlo, semi-Markov, binomial, and heuristic – to examine the relationship between the mass of spares and probability of loss of function related to the Carbon Dioxide Removal System (CRS) for a notional, simplified mission profile. The Exploration Maintainability Analysis Tool (EMAT), developed at NASA Langley Research Center, is utilized for the Monte Carlo analysis. We discuss the implications of these results and the features and drawbacks of each method. In particular, we identify the limitations of heuristic methods for logistics analysis, and the additional insights provided by more in-depth techniques. We discuss the potential impact of system complexity on each technique, as well as their respective abilities to examine dynamic events. This work is the first step in an effort that will quantitatively examine how well these techniques handle increasingly more complex systems by gradually expanding the system boundary.