A Bayes-SLIM based methodology for human reliability analysis of lifting operations

Abstract Investigations have shown that human error (HE) is the most common cause of accidents involving lifting operations. So it is essential to conduct human reliability analysis (HRA) in lifting operations. The estimation of human error probabilities (HEPs) is a key to HRA. In this paper, five useful performance shaping factors (PSFs) of lifting operations were introduced and an approach to combine Bayesian methodology and the success likelihood index method (SLIM) was applied to determine the HEPs of various lifting operation errors. A numerical example was used to illustrate the application of the proposed methodology. Relevance to industry Reliability analysis of crane lifting operation has traditionally been difficult without considering human error. The present study suggests that managers could use the Bayesian-SLIM methodology to conduct human reliability analysis and minimize human error in crane lifting operation.

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