A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors.
BACKGROUND
Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships.


METHODS
The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event.


RESULTS
This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific.


CONCLUSIONS
"Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.
Ren
J
J
School of Engineering, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.
Jenkinson
I
I
Wang
J
J
Xu
D L
DL
Yang
J B
JB
D000062:Accidents, Occupational / Q000517:prevention & control; D001499:Bayes Theorem; D004777:Environment; D006804:Ergonomics; D006801:Humans; D017146:Models, Organizational; D009784:Occupational Diseases / Q000517:prevention & control; D016272:Occupational Health; D009792:Oceans and Seas; D015279:Organizational Culture; D012106:Research; D018570:Risk Assessment; D017751:Safety Management