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<p>This study proposes a resilience-integrated failure mode and effect analysis (Res-FMEA) method to identify critical failures in deep-sea mining hydraulic lifting systems (HLS), considering the impact of system resilience under extreme operating conditions. An uncertainty assessment model is introduced based on the fuzzy hierarchical analysis and entropy weight method, aiming to calculate expert weights and reduce the inherent subjectivity of expert judgment. Key resilience indicators, including mean time to repair (MTTR) and preventative maintenance costs, are developed and integrated into the traditional risk priority number (RPN), resulting in a novel resilience risk priority number (Res-RPN). This integration enables FMEA to dynamically quantify the operational risks of the HLS and its recover ability. The presented Res-FMEA method identifies the top ten failure scenarios and provides corresponding risk control measures to cut off failure propagation paths. The results reveal that maintenance efficiency and economic thresholds have a substantial impact on the risk level.</p>

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Resilience Integrated Failure Analysis for Hydraulic Lifting System of Deep-sea Mining

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Yingnuo Guo,
  • Zhuang Kang,
  • Yu Sun,
  • Hui Zhang,
  • Jiancheng Liu,
  • Jichuan Kang

摘要

This study proposes a resilience-integrated failure mode and effect analysis (Res-FMEA) method to identify critical failures in deep-sea mining hydraulic lifting systems (HLS), considering the impact of system resilience under extreme operating conditions. An uncertainty assessment model is introduced based on the fuzzy hierarchical analysis and entropy weight method, aiming to calculate expert weights and reduce the inherent subjectivity of expert judgment. Key resilience indicators, including mean time to repair (MTTR) and preventative maintenance costs, are developed and integrated into the traditional risk priority number (RPN), resulting in a novel resilience risk priority number (Res-RPN). This integration enables FMEA to dynamically quantify the operational risks of the HLS and its recover ability. The presented Res-FMEA method identifies the top ten failure scenarios and provides corresponding risk control measures to cut off failure propagation paths. The results reveal that maintenance efficiency and economic thresholds have a substantial impact on the risk level.