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Reliability engineering benefits asset management from many aspects. Currently, the consideration of reliability becomes more critical but difficult since the interaction among physical, digital, and human dimensions becomes more complex. Prognostics and Health Management is regarded having more benefits at both component and system levels, and is able to provide dynamic and predictive maintenance strategies. In this study, reliability analysis tools are embedded in a data-driven PHM framework in the case that the turbofan engine is considered as a complex system. Multiple degradation modes are analyzed by exploring systems’ fault conditions. The results show the benefit of combining reliability analysis tools with data-driven PHM approaches, as well as the advantages in the decision-making process.

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Data-Driven Prognostics and Health Management Solutions in the Case of Multiple Degradations in Complex Systems

  • 会议论文

  • 发表日期：

    2025年

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  • Huxiao Shi,
  • Shuo Yang,
  • Jie Geng,
  • Gabriele Baldissone,
  • Micaela Demichela

摘要

Reliability engineering benefits asset management from many aspects. Currently, the consideration of reliability becomes more critical but difficult since the interaction among physical, digital, and human dimensions becomes more complex. Prognostics and Health Management is regarded having more benefits at both component and system levels, and is able to provide dynamic and predictive maintenance strategies. In this study, reliability analysis tools are embedded in a data-driven PHM framework in the case that the turbofan engine is considered as a complex system. Multiple degradation modes are analyzed by exploring systems’ fault conditions. The results show the benefit of combining reliability analysis tools with data-driven PHM approaches, as well as the advantages in the decision-making process.