Safety and dependability are major design objectives for offshore operations such as the construction of wind farms or oil and gas exploration. Today processes and related risks are typically described informally and process specification are neither reusable nor suitable for risk assessment. Here, we propose to use a specification language for processes. We integrate this specification language in a generic modeling approach in combination with an analysis tool and a tool to construct health, safety and environment (HSE) plans — a mandatory document for granting a construction/operation permit. Specifically, for each planned scenario a process is modeled, describing the detailed operation of the involved actors as well as the interaction with resources and environmental conditions. We enrich this process model with hazardous events which is facilitated by integration with an offshore operation generic hazard list, thereby giving access to expert knowledge for the specific situation to be planned. This in turn allows us to perform an automatic quantitative risk assessment using fault tree analysis. We exemplify our approach on a standard offshore operation of personnel transfer from an offshore building to another naval unit by modeling, annotating with hazards, performing the fault-tree analysis, and finally generating HSE plans.

Real world events are observed by sensors since decades, for instance in the logistics where packages are identified and tracked. This information result in an information flow. This information flow is used to control the physical material flow. Hence, the information flow is a digital representation of the physical material flow. However, to guarantee that the digital representation is in alignment to the physical world is a challenging task. Especially for scenarios with manual operations, the representation is vulnerable for errors. This paper proposes a generic approach to assure consistency between digital and physical world. The paper presents a methodology to model the monitoring of physical entities and to analyse the model to evaluate the risk of unreliable digital representation.