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Reliability evaluation method for complex system incorporating human–machine interaction
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AI
DOI：10.1016/j.eswa.2026.132576.png)
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Abstract
En 中文
The blowout preventer (BOP) is a safety–critical device in offshore oil and gas production, and the electrical control system (ECS) of it is essential for safe operation. Reliable assessment of the ECS is therefore of great importance. Existing methods mainly rely on precise modeling of hardware degradation to achieve accurate reliability evaluation. However, they generally neglect the influence of human factors on equipment, leading to discrepancies between theoretical predictions and practical conditions. To address this limitation, a reliability assessment method integrating human–machine interaction is proposed. Through a multi-scenario human reliability assessment model, external environmental factors and operator-related factors are simultaneously incorporated. Through a hardware reliability model, multi-state degradation, hardware redundancy, and hierarchical dependency relationships are simultaneously described. A human–machine interaction is established to represent the influence of human-factor states on hardware reliability and the feedback effect of equipment states on human reliability. A subsea BOP in the South China Sea is used as a case study to validate the proposed method. The results indicate that incorporating human reliability yields more realistic and reliable reliability assessment results.
Keywords:
Reliability assessment
Human–machine interaction
Offshore oil and gas production
Electrical control system
Blowout preventer
Journal
IF:
7.5
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2.9W
Citations:
10.2W
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