This research investigates the impact of aging critical assets on operational reliability and investment planning within energy infrastructure, with a specific focus on the boil-off gas (BOG) compression system at a liquefied natural gas (LNG) regasification facility. The Asset Health Index (AHI) methodology is employed to evaluate compressor degradation and its influence on the probability of failure (PoF) and overall system reliability. A case study involving four BOG compressors is presented, in which thirteen operational scenarios—representative of the plant’s actual operating modes—are modeled to assess system performance under real-world conditions. The integration of AHI with probabilistic modeling and decision-support tools such as the Asset Investment Project (AIP) enables more effective maintenance strategies and investment prioritization, thereby supporting service continuity and long-term economic viability. Our results highlight how this approach helps anticipate failures, justifying timely interventions, and enhancing life cycle cost (LCC) analysis frameworks.

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Reliability and Risk Assessment in Compressors: Impact of the Asset Health Index (AHI) on Maintenance Management and Investment Planning

  • Sonia Liñán García,
  • Antonio De la Fuente Carmona,
  • Javier Serra Parajes,
  • Adolfo Crespo Márquez

摘要

This research investigates the impact of aging critical assets on operational reliability and investment planning within energy infrastructure, with a specific focus on the boil-off gas (BOG) compression system at a liquefied natural gas (LNG) regasification facility. The Asset Health Index (AHI) methodology is employed to evaluate compressor degradation and its influence on the probability of failure (PoF) and overall system reliability. A case study involving four BOG compressors is presented, in which thirteen operational scenarios—representative of the plant’s actual operating modes—are modeled to assess system performance under real-world conditions. The integration of AHI with probabilistic modeling and decision-support tools such as the Asset Investment Project (AIP) enables more effective maintenance strategies and investment prioritization, thereby supporting service continuity and long-term economic viability. Our results highlight how this approach helps anticipate failures, justifying timely interventions, and enhancing life cycle cost (LCC) analysis frameworks.