Human-Centric Reliability Prediction for IoT-Enabled Human-Machine Systems Considering Component Hierarchical Dependency

The Internet of Things (IoT) technology can improve the efficiency of human-machine collaboration (HMC) systems. However, the presence of collaboration mechanisms introduces dynamic human-machine interaction for the mission reliability modeling. This paper develops a cloud edge-based dynamic mission reliability prediction method for HMC systems. Firstly, a dynamic human reliability analysis method is proposed based on the IoT-driven common performance condition and attention curve. Secondly, based on hierarchy and dependency of remotely operated vehicle (ROV) components, a hierarchical dependency Markov process is proposed for component reliability modeling. In addition, IoT-driven proactive maintenance for ROV components is developed. Afterwards, the dynamic human reliability and ROV reliability is corrected based on the impact of collaboration mechanisms, and the mission reliability model of the IoT-enabled HMC system is developed. Finally, a case study of the IoT-enabled HMC system for an underwater search and rescue mission is conducted to validate the proposed method.