Industrial systems with protective devices (PDs) perform essential tasks but face significant failure risks. Under certain conditions, missions should be aborted to initiate rescue processes, balancing the system survivability and the task success probability. However, the task abort strategy for systems assembled with PDs is understudied. To bridge this research gap, this paper establishes a reliability model for the mission-oriented k -out-of- n : F system with multiple subsystems assembled with PDs in a shock environment and optimizes a policy for guiding its mission termination. Each subsystem is assigned to complete a certain proportion of the entire missions and the mission completion speed of different subsystems varies. New task abort criteria are built by integrating the state information of subsystems and their PDs. Mission success is defined by the proportion of subsystems achieving their subtasks, meeting a threshold. A comprehensive method mixing Markov process and universal generating function is built to derive reliability and mission related indexes. Two optimization models with different objective functions are built and solved to derive the optimum mission abort policy. Finally, a case study with Automated Guided Vehicles verifies the research results and model applicability.
Wang et al. (Thu,) studied this question.