Reliability and mission abort strategy for a multi-state k-out-of-n: F system in a dynamically changing shock environment

Some mission-oriented systems run in the complex shock environment, and the shock environment may change multiple times. Most existing studies focusing on the mission abort strategies did not consider the effect of the changing environment on the optimization of mission abort policies, which is inconsistent with the engineering practice. In addition, when studying mission abort strategies, prior research on multi-state systems composed of multi-state components has not fully utilized the state information of the components. To fill the existing research gap, this paper investigates the reliability and mission abort strategies of a multi-state k-out-of-n: F system operating in a dynamic shock environment. The proposed system runs in the dynamically varying shock environment, and the changes between different shock environments follow a Markov process. When the proposed system runs in distinct shock environments, its degradation process and the failure criterion differ, which are associated with the shock environment. Competing mission termination criteria are proposed by incorporating the information of various environments. These criteria trigger the task termination based on the numbers of components in specific state intervals in the system. Markov process imbedding method is applied to derive reliability and cost indicators. Moreover, two optimization models are established to determine the optimal mission abort policy. Finally, an application based on an unmanned aerial vehicle system for executing tasks is presented, demonstrating the applicability of the proposed reliability model and mission abort strategy.