Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.

Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.

Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.

The complexity of industrial systems, the use of dangerous chemical substances have dreadfully increased the potential accident destruction especially in the field of chemical industry. The technical analysis f accident scenarios are essential not only in learning lessons from unfortunate events in the chemical industry but also in preventing the occurrence of such events in the future. In this paper we propose an approach for analyzing the scenarios of an accident related to a chemical process, we consider the case of a chemical reactor for the application of this approach. This approach is based on four steps, risk analysis, study of top event, accident scenarios, and study of system evolution.

The complexity of industrial systems, the use of dangerous chemical substances have dreadfully increased the potential accident destruction especially in the field of chemical industry. The technical analysis f accident scenarios are essential not only in learning lessons from unfortunate events in the chemical industry but also in preventing the occurrence of such events in the future. In this paper we propose an approach for analyzing the scenarios of an accident related to a chemical process, we consider the case of a chemical reactor for the application of this approach. This approach is based on four steps, risk analysis, study of top event, accident scenarios, and study of system evolution.

The complexity of industrial systems, the use of dangerous chemical substances have dreadfully increased the potential accident destruction especially in the field of chemical industry. The technical analysis f accident scenarios are essential not only in learning lessons from unfortunate events in the chemical industry but also in preventing the occurrence of such events in the future. In this paper we propose an approach for analyzing the scenarios of an accident related to a chemical process, we consider the case of a chemical reactor for the application of this approach. This approach is based on four steps, risk analysis, study of top event, accident scenarios, and study of system evolution.