English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Human error plays a pivotal rule in all aspects of engineering activities such as operation, maintenance, design, inspection and installation. Industries are faced up to various significant human errors and consequently irrecoverable loss each year, but still there is a lack of heeds to qualify as well as quantify such errors. This paper tries to estimate the probability of failure in lifting of light structures in sea by considering human errors. To do this, a strong qualifying tool such as Functional Resonance Analysis Method (FRAM) is applied to develop high risk accident scenario by considering non-linear socio-technical interaction in system. Afterwards, human error probability is calculated for each activity using the Success Likelihood Index Method (SLIM) based on resonance that is carried out in FRAM network. Then Event Tree (ET) is conducted to assess consequences. The present study is aimed to interpret the importance of attentions to qualitative methods in implementing quantitative risk analyses to consider human error in calculation. The final outcome depicts that considering human error in the process of risk assessment will result in more accuracy and reliability in final Risk Probability Number (RPN). The developed methodology has been applied to a case study of an offshore installation.

Developing a Risk-Based Approach for Optimizing Human Reliability Assessment in an Offshore Operation