No abstract

The recent growing trend to develop large-scale satellite constellations (i.e., mega-constellation) with low-cost small satellites has brought the need for an efficient and scalable maintenance strategy decision plan. Traditional spare strategies for satellite constellations cannot handle these mega-constellations due to their limited scalability in the number of satellites and/or frequency of failures. In this paper, we propose a novel spare strategy using an inventory management approach. We consider a set of parking orbits at a lower altitude than the constellation orbits for spare storage, and model the satellite constellation spare strategy problem using a multi-echelon (s,Q)-type inventory policy, viewing the Earth's ground as a supplier, the parking orbit spare stocks as warehouses, and the in-plane spare stocks as retailers. The accuracy of the proposed analytical model is assessed using simulations via Latin Hypercube Sampling. Furthermore, based on the proposed model, an optimization formulation is introduced to identify the optimal spare strategy, comprising the parking orbits' characteristics and all locations' policies, to minimize the maintenance cost of the system given performance requirements. The proposed model and optimization method are applied to a real-world satellite mega-constellation case to demonstrate their value. Nomenclature cap launch = Launch capacity (number of possible satellites per rocket), in units of satellites D plane = Demand for in-plane spares, in units of satellites D parking = Demand for parking spares, in units of batches Q plane E S plane = Expected number of backorders for in-plane spares over a replenishment cycle, in units of satellites