Multistate UAV system reliability modelling and analysis with a random mission plan

The study and modeling of aerospace systems have been conducted by various researchers. The success of missions and related costs has always been one of the concerns of researchers and due to the sensitivity of the operations and the variety of missions, this issue is more important today. In the past, aerospace equipment issues such as subsystem and component design, consumables, operation planning, maintenance, and depreciation were considered independently for each aircraft. In the past decade, due to the increasing use of drones and their impact on various military and civilian operations, the subject of operations and their impact on each other, and ultimately the impact on the quantity and quality of air operations, these parameters have been modeled together. In this research, an Unmanned Air Vehicle (UAV) system that includes several UAVs that has a parallel structure and able to perform different missions to detect, follow and attack based on user needs, has been considered. UAVs do not have a fixed failure rate and are so-called multi-state, and the quality of operations and its success rate are defined according to the UAV conditions, the amount of failure, and the type of failure. It is also assumed that each UAV has the ability to perform different operations, but the missions are randomly assigned, so in this study, universal generation function and Markov chain methods for modeling are developed. A UAV system has been considered, the ability and accuracy of these methods in predicting system success are demonstrated.