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Human reliability analysis of offshore high integrity pressure protection system based on improved CREAM and HCR integration method.
- Source :
-
Ocean Engineering . Sep2024, Vol. 307, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- Control room operators on offshore platforms play an important role in realizing the safety instrumentation functions of the high integrity pressure protection system (HIPPS) during overpressure emergencies. Human reliability analysis is critical to the overpressure operation of offshore HIPPS, yet there are few studies. To remedy this gap, the paper proposes an integrated human reliability analysis method to analyse the impact of human intervention on offshore HIPPS safety. Considering the effects of context and cognitive performance on human reliability comprehensively, the improved cognitive reliability and error analysis model (CREAM) is established; The correction effect of external environmental factors on response failure probability is quantified, and the improved human cognitive reliability (HCR) model is developed; The two improved models are organically combined to form an integrated methodology. Based on the behaviour characteristics of personnel emergency response, human error probability is calculated in stages to analyse human reliability. The findings indicate that the overall human error probability for HIPPS overpressure operations is 0.124 and particular attention needs to be paid to observation and decision-making operations. Besides the theoretical background, the paper provides practical contributions to personnel training, mission planning, and risk management of HIPPS to minimize the possibility of human error. • An integrated human reliability analysis method for offshore HIPPS is proposed. • The cognitive performance correction coefficient is introduced to improve CREAM. • The modification effect of external environmental factors is quantified to improve the HCR model. • Human error probabilities are calculated in stages based on personnel task characteristics. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00298018
- Volume :
- 307
- Database :
- Academic Search Index
- Journal :
- Ocean Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 177870712
- Full Text :
- https://doi.org/10.1016/j.oceaneng.2024.118153