Title: HRA of offshore wind turbine installation based on the improved CREAM method

Authors: Yanying Yu; Xiaoyan Su

Addresses: School of Automation Engineering, Shanghai University of Electric Power, Shanghai, 200090, China ' School of Automation Engineering, Shanghai University of Electric Power, Shanghai, 200090, China

Abstract: The offshore wind power industry is developing rapidly, yet accidents during the installation of offshore wind turbines occur frequently due to its complexity. Human reliability analysis (HRA) is vital to reduce the human error probability (HEP) in the field of offshore wind turbine installation. HRA method, like cognitive reliability and error analysis method (CREAM), integrates multidisciplinary theories and emphasises the impact of human behaviour. CREAM has been widely used in offshore risk assessment, but the traditional model is insufficient to effectively consider the relationship between levels of common performance conditions (CPC). Therefore, we introduce the Dempster-Shafer evidence theory and ordered distance to improve the modelling of CPC and determine expert evaluation credibility through the weighted average method, thus providing a more comprehensive assessment of HEP. This method prevents both overestimation and underestimation of HEP, thereby enhancing the comprehensiveness and objectivity of the assessment, which in turn improves safety in offshore wind turbine installations.

Keywords: offshore wind turbines; cognitive reliability and error analysis method; CREAM; human reliability analysis; HRA; Dempster-Shafer evidence theory.

DOI: 10.1504/IJOSM.2025.150833

International Journal of Ocean Systems Management, 2025 Vol.2 No.2, pp.209 - 228

Received: 14 Mar 2025
Accepted: 21 Apr 2025
Published online: 23 Dec 2025 *

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