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 must be designed, built and operated to meet tolerable risk level as required regulatory agencies. This requirement is closely related to their probabilistic performance measures which are either their average probability of dangerous failure on demand (PFDavg) or their average frequency of failure (PFH: Probability of Failure per Hour). The object of this work is the SIS performances evaluation taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC), etc. This leads to an accurate and therefore safe assessment of the safety integrity level (SIL) inherent to safety functions performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. In this paper we first explain in detail the IEC 61508 approach for handling uncertainty. Afterwards, we propose an approach that combines (i) Monte Carlo analysis (MCA) and (ii) fuzzy sets. Indeed, the first method is appropriate when representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code developed under the MATLAB environment.

Purpose – Ballast water of merchant ship is a source of introduction of invasive species around the globe. The purpose of this paper is to present a quantitative risk assessment applied to a model port, the Port of Arzew in Algeria, and based on an analysis of this port’s shipping traffic. Design/methodology/approach – The risk assessment for introduction of invasive species is interpreted in the form of a probabilistic process, with a combination of two probabilities. The first probability is related to the ability of a species to arrive to the destination (recipient port), depending on the quantity of water ballast discharged and the duration of voyage. The second one is based on the species ability to survive in their new environment, which depends on the environmental similarity between donor port and Arzew port. Findings – This assessment’s outcome consists on a classification of scenarios regarding their acceptability. Consequently, it helped to classify donor ports according to a risk scale, from low risk to high-risk donor ports. Research limitations/implications – The phenomenon of invasion of aquatic species is a complex process. Factors such as adaptation and tolerance of species, the attendance or absence of predators, were not taken into account in this study. Practical implications – This study could be used by the maritime administration as a decision-making tool regarding the issue of exemptions under the IMO International Convention on the Management of Ballast Water and Sediments 2004. Originality/value – This is one of the first known studies in Algeria and dealing with ballast water management. The results of this assessment provide useful information to policy makers, in order to develop a national strategy to reduce the impact of shipping pollution on the marine environment.

This paper presents a statistical analysis of reported accidents related to the Skikda's Oil and Gas Refinery that led to a major explosion and loss of life. A historical review of fire, explosion and toxic release incidents that occurred during the period between 2002 and 2013 is presented. A brief description of each accident/incident is provided with the fatalities and personal injuries that resulted being described. These case studies have been analyzed with a view to understand the common causes including errors, which have led to catastrophic events. Accident frequency analysis has been applied to various types of primary accidental events such as fire, explosion and toxic gas releases to assess the potential damage of such events and the likelihood of such damage occurring. The basic principles of such analysis is to utilize the available information and use the most detailed elements to illustrate what the industry should learn from these accidents so that it can learn from them and hopefully prevent future major accidents.

Port approach for merchant ships (regarding docking) is a special event related to the safety of ships and port facilities. This maneuvre is for emergency situations, and the consequences can be very damaging because there is a high risk of occurrence and severity can be high. In Algeria, 90% of foreign trade depends on shipping, and commercial vessels must dock in the port safely. This study aims to contribute to the management of risks associated with port operations by designing a matrix for specific assessment of this type of risk based on analysis of several incidents and accidents regarding maneuvring ships in Algerian ports. The design of the evaluation matrix of risks associated with port operations in Algeria is done in the context of the application of the Formal Safety Assessment methodology for improved performance of this method regarding precision and accuracy of results.

Safety Instrumented Systems (SIS) constitute an indispensable element in the process of risk reduction for almost all of nowadays' industrial facilities. The main purpose of this paper is to develop a set of generalized and simplified analytical expressions for two commonly employed metrics to assess the performance of SIS in terms of safety integrity, namely: the Average Probability of Failure on Demand (PFD_avg) and the Probability of Dangerous Failure per Hour (PFH). In addition to the capability to treat any K-out-of-N architecture, the proposed formulas can smoothly take into account the contributions of Partial Stroke Testing (PST) and Common Cause Failures (CCF). The validity of the suggested analytical expressions is ensured through various comparisons that are carried out at different stages of their construction.

This article aims to propose a model for analyzing work situations. In this context, we focus our interest on the simplification of procedures for working where the proposed model is used to analyze human behavior in response to non-compliance of work procedures. From this analysis, ways to improve work processes will be identified.

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.