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The criticality of risk management is evident when considering the information society of today, and the emergence of Future Internet technologies such as Cloud services. Information systems and services become ever more complex, heterogeneous, dynamic and interoperable, and many different stakeholders increasingly rely on their availability and pr...
Citations
... The approach is applied to a case study in the petroleum domain. The authors of [10] introduce an approach for compositional risk modeling, through a notion of risk model encapsulation, for which internal details of a risk model are hidden. This is achieved by defining a risk model interface that contains all and only the information that is needed for composing the individual risk models to derive the overall risk picture. ...
Accidents on petroleum installations can have huge consequences, to mitigate the risk, a number of safety barriers are devised. Faults and unexpected events may cause barriers to temporarily deviate from their nominal state. For safety reasons, a work permit process is in place: decision makers accept or reject work permits based on the current state of barriers. However, this is difficult to estimate, as it depends on a multitude of physical, technical and human factors. Information obtained from different sources needs to be aggregated by humans, typically within a limited amount of time. In this paper we propose an approach to provide an automated decision support to the work permit system, which consists in the evaluation of quantitative measures of the risk associated with the execution of work. The approach relies on state-based stochastic models, which can be automatically composed based on the work permit to be examined.
A thorough understanding of the safety risks of a system requires an understanding of its human and organizational factors, as well as its technical components. Analysis approaches that focus only on the latter without considering, for example, how human decision makers may respond to a technical failure, are not able to adequately capture the wide variety of safety risk scenarios that need to be considered. In this paper, we propose a model-based analysis approach that allows analysts to interpret humans and organizations in terms of components and their behavior in terms of failure logic. Our approach builds on top of CHESS-FLA, which is a tool-supported failure logic analysis technique that supports analysis of component-based system architectures to understand what can go wrong at the system level and to identify the causes (i.e. Faulty components). However, CHESS-FLA currently deals only with hardware and software components and thus it is not adequate to reason about socio-technical systems. We therefore provide an extension based on a pre-existing classification of socio-failures and combine it with the one used in CHESS-FLA for technical failures, thereby giving birth to a novel approach to analysis of socio-technical systems. We demonstrate our approach on an example from the petroleum domain.
