Manufacturing processes involving chemical agents are evolving at great speed. In this context, managing chemical risk is especially important towards preventing both occupational accidents and major accidents. Directive 89/391/EEC and Directive 2012/18/EU, respectively, are enforced in the European Union (EU) to this end. These directives may be further complemented by the recent ISO 45001:2018 standard regarding occupational health and safety management systems. These three management systems are closely related. However, scientific literature tackles the researching of these accidents independently. Thus, the main objective of this work is to identify and analyse the links and transitional spaces between the risk management of both types of accident. Among the results obtained, three transitional spaces can be pointed out which result from the intersection of the three systems mentioned. Similarly, the intersection of these spaces gives shape to a specific transitional space defined by the individual directives linked to Directive 89/391/EEC. These results are limited from a regulatory and technical perspective. Thus, the results are a starting point towards developing models that integrate the management systems studied.@en

Inherent safety design principles have been used extensively to design safer plants. However, to date their application is merely limited to technical changes in the process. An unexplored area of ISD is related to all the non-technical aspects linked to the safety of industrial plants, such as the Human and Organizational Factors, often referred to as HOFs. This study presents an Inherent Safety Decision Making framework (ISDDM), with the objective to provide a structured tool that can be easily used by industrial practitioners. The novelty of the ISDDM is the provision of a structured framework where purely technical and non-technical ISD alternatives are categorized and analyzed, to check if possible interactions exist among the alternatives proposed. To prove the usefulness of the model, a case-study addressing a carbon capture plant is carried out. This technology will play an important role in the reduction of CO2 emission in carbon-intense industrial processes, implying a rapid scale-up of these plants in the next years, therefore justifying the analysis of this green technology. Adopting the proposed ISDDM, the improvements in terms of safety from the base case ranged from 58% to around 70% for the best design solution, while from an economic perspective, cost variations were comprised between 16% and 22%. The results of the study demonstrate that the framework can be rigorously implemented and that it provides a considerable number of additional alternatives due to the inclusion of HOFs in the analysis. In conclusion, an improved and adequate ISD is a key to environmental sustainability.@en

In this article, an extensive literature review has been carried out about process safety education. We drafted a process safety model able to systematize the literature review and investigated scientific papers as well as professional articles and so-called grey literature. The presence of a common background emerged, although possibilities for optimization of university curricula are possible, as well as harmonization within universities in different countries and between universities and industry. More collaboration in the field of process safety education is recommended, thereby also involving government agencies and/or control authorities and inspection bodies. In the light of the prevention of major accidents in the chemical industry, the process safety education topic deserves to receive more attention from all parties involved, that is, academia, industry and authorities.@en

In this article, an extensive literature review has been carried out about process safety education. We drafted a process safety model able to systematize the literature review and investigated scientific papers as well as professional articles and so-called grey literature. The presence of a common background emerged, although possibilities for optimization of university curricula are possible, as well as harmonization within universities in different countries and between universities and industry. More collaboration in the field of process safety education is recommended, thereby also involving government agencies and/or control authorities and inspection bodies. In the light of the prevention of major accidents in the chemical industry, the process safety education topic deserves to receive more attention from all parties involved, that is, academia, industry and authorities.@en

In this article, an extensive literature review has been carried out about process safety education. We drafted a process safety model able to systematize the literature review and investigated scientific papers as well as professional articles and so-called grey literature. The presence of a common background emerged, although possibilities for optimization of university curricula are possible, as well as harmonization within universities in different countries and between universities and industry. More collaboration in the field of process safety education is recommended, thereby also involving government agencies and/or control authorities and inspection bodies. In the light of the prevention of major accidents in the chemical industry, the process safety education topic deserves to receive more attention from all parties involved, that is, academia, industry and authorities.@en

Securing critical infrastructures is a complex task. Required information is usually scarce or inexistent, and experts’ judgments may be inaccurate and biased. In this paper, two methodologies dealing with data scarcity, imprecision, and uncertainty are presented: Evidential network and Credal network. Evidential network is a graphical technique based on Dempster-Shafer Theory to explicitly model the propagation of epistemic uncertainty among variables while Credal network is an extension of Bayesian network to deal with sets of probabilities, known as Credal sets, based on experts’ judgments. Both methodologies constitute robust frameworks to account for high degree of imprecision on data, producing informative results despite the low-informative input. In the present study, the power in expressing uncertainty of these two methodologies have been showed, and their differences have been described through their application to a case study of security vulnerability assessment. Results demonstrate the substantial equivalence of the two methodologies in prognostic analysis, thus, an approximate updating procedure of Evidential network through equivalent Credal network has been proposed, to overcome the lack of possibility to compute updating in the context of Dempster-Shafer Theory.@en

Securing critical infrastructures is a complex task. Required information is usually scarce or inexistent, and experts’ judgments may be inaccurate and biased. In this paper, two methodologies dealing with data scarcity, imprecision, and uncertainty are presented: Evidential network and Credal network. Evidential network is a graphical technique based on Dempster-Shafer Theory to explicitly model the propagation of epistemic uncertainty among variables while Credal network is an extension of Bayesian network to deal with sets of probabilities, known as Credal sets, based on experts’ judgments. Both methodologies constitute robust frameworks to account for high degree of imprecision on data, producing informative results despite the low-informative input. In the present study, the power in expressing uncertainty of these two methodologies have been showed, and their differences have been described through their application to a case study of security vulnerability assessment. Results demonstrate the substantial equivalence of the two methodologies in prognostic analysis, thus, an approximate updating procedure of Evidential network through equivalent Credal network has been proposed, to overcome the lack of possibility to compute updating in the context of Dempster-Shafer Theory.@en

Securing critical infrastructures is a complex task. Required information is usually scarce or inexistent, and experts’ judgments may be inaccurate and biased. In this paper, two methodologies dealing with data scarcity, imprecision, and uncertainty are presented: Evidential network and Credal network. Evidential network is a graphical technique based on Dempster-Shafer Theory to explicitly model the propagation of epistemic uncertainty among variables while Credal network is an extension of Bayesian network to deal with sets of probabilities, known as Credal sets, based on experts’ judgments. Both methodologies constitute robust frameworks to account for high degree of imprecision on data, producing informative results despite the low-informative input. In the present study, the power in expressing uncertainty of these two methodologies have been showed, and their differences have been described through their application to a case study of security vulnerability assessment. Results demonstrate the substantial equivalence of the two methodologies in prognostic analysis, thus, an approximate updating procedure of Evidential network through equivalent Credal network has been proposed, to overcome the lack of possibility to compute updating in the context of Dempster-Shafer Theory.@en

Securing critical infrastructures is a complex task. Required information is usually scarce or inexistent, and experts’ judgments may be inaccurate and biased. In this paper, two methodologies dealing with data scarcity, imprecision, and uncertainty are presented: Evidential network and Credal network. Evidential network is a graphical technique based on Dempster-Shafer Theory to explicitly model the propagation of epistemic uncertainty among variables while Credal network is an extension of Bayesian network to deal with sets of probabilities, known as Credal sets, based on experts’ judgments. Both methodologies constitute robust frameworks to account for high degree of imprecision on data, producing informative results despite the low-informative input. In the present study, the power in expressing uncertainty of these two methodologies have been showed, and their differences have been described through their application to a case study of security vulnerability assessment. Results demonstrate the substantial equivalence of the two methodologies in prognostic analysis, thus, an approximate updating procedure of Evidential network through equivalent Credal network has been proposed, to overcome the lack of possibility to compute updating in the context of Dempster-Shafer Theory.@en

In this paper, a conceptual framework is developed to improve NaTech safety in the chemical industry. The concept is called EPIC, indicating that emphasis should be put on Education, learning and training, Proactive risk minimization and safety innovation, Intensified informed inspection and analysis, and Cooperation and transparency. Concrete initiatives addressing NaTech for every domain of the EPIC conceptual framework are given. The innovativeness of the EPIC framework resides in the potential of the simultaneous application of initiatives within the four areas of improvement (E, P, I, and C) to make chemical clusters much more resilient with respect to nature-related disasters. As such, the proposed EPIC framework may lead to a much-needed revolution of NaTech safety in the chemical industry.@en

In this paper, a conceptual framework is developed to improve NaTech safety in the chemical industry. The concept is called EPIC, indicating that emphasis should be put on Education, learning and training, Proactive risk minimization and safety innovation, Intensified informed inspection and analysis, and Cooperation and transparency. Concrete initiatives addressing NaTech for every domain of the EPIC conceptual framework are given. The innovativeness of the EPIC framework resides in the potential of the simultaneous application of initiatives within the four areas of improvement (E, P, I, and C) to make chemical clusters much more resilient with respect to nature-related disasters. As such, the proposed EPIC framework may lead to a much-needed revolution of NaTech safety in the chemical industry.@en

In this paper, a conceptual framework is developed to improve NaTech safety in the chemical industry. The concept is called EPIC, indicating that emphasis should be put on Education, learning and training, Proactive risk minimization and safety innovation, Intensified informed inspection and analysis, and Cooperation and transparency. Concrete initiatives addressing NaTech for every domain of the EPIC conceptual framework are given. The innovativeness of the EPIC framework resides in the potential of the simultaneous application of initiatives within the four areas of improvement (E, P, I, and C) to make chemical clusters much more resilient with respect to nature-related disasters. As such, the proposed EPIC framework may lead to a much-needed revolution of NaTech safety in the chemical industry.@en

In this paper, a conceptual framework is developed to improve NaTech safety in the chemical industry. The concept is called EPIC, indicating that emphasis should be put on Education, learning and training, Proactive risk minimization and safety innovation, Intensified informed inspection and analysis, and Cooperation and transparency. Concrete initiatives addressing NaTech for every domain of the EPIC conceptual framework are given. The innovativeness of the EPIC framework resides in the potential of the simultaneous application of initiatives within the four areas of improvement (E, P, I, and C) to make chemical clusters much more resilient with respect to nature-related disasters. As such, the proposed EPIC framework may lead to a much-needed revolution of NaTech safety in the chemical industry.@en

Process accidents in the early 1980s have drawn process safety into the main stream. In the 1990s, risk-based approaches were developed to bring safety into design as well as economic considerations. In the 2000s, the inherent safety approach began to be practiced on a limited basis, and process safety evolution made significant progress. As process systems continue to become more complex and operations move into remote and harsh environments, traditional risk analysis may no longer be sufficient. Dynamic risk assessment is the basis for the next generation of risk and management approaches that help to enable safer complex process systems operating in extreme environments. This article investigates the main contributions in the area of dynamic risk assessment. Then, an overall framework for dynamic risk management of process facilities is proposed.@en

The authors regret that an imprecise statement was made in this article, and wish to offer this Corrigendum as clarification. The authors would like to apologise for any inconvenience caused. Imprecise statement: Misuri et al. (2018, pp. 70) state in their work: “Differently from EN [evidential network], CN [credal network] can be used both to conduct forward analysis and to update probabilities”. This statement implies that EN cannot be used for belief updating and should be mapped into a corresponding CN for that purpose. Correction: The foregoing statement may be correct for conventional ENs that are based on Dempster's combination rule, but does not hold true for the EN developed by Simon and co-workers (2008, 2009) based on Bayesian network (BN) inference algorithms (herein, BN-based EN). Simon and Weber (2009) explicitly mention in their work that the developed EN can be used for belief updating: “The computation mechanism is based on the Bayes theorem, which is extended to the representation of uncertain information according to the framework of Dempster-Shafer theory. Specific evidence (Hard evidence) is modeled by a mass of 1 on one of the focal elements of the frame of discernment. Non-specific evidence (Soft evidence) corresponds to a mass distribution on the focal elements of the frame of discernment.” Proof: Fig. 1 displays the BN-based EN developed in Misuri et al. (2018) for security vulnerability assessment of a process plant where the belief masses have been updated given the evidence “Attack = Success”. Misuri et al. (2018) used the BN-based EN for predicting the probability of a successful attack (forward analysis), but to update the probabilities (backward analysis) they mapped the BN-based EN into an equivalent CN and calculated the updated probabilities given “Attack = Success”. They used two packages, JavaBayes and GL2U, to implement the CN, concluding that JavaBayes results in more consisting updated probabilities with regard to the evidence (the 2nd column in Table 1). In the present corrigendum, we used the BN-based EN (Fig. 1) for belief updating given “Attack = Success”. The updated beliefs were subsequently used to calculate updated probability intervals (the 3rd column in Table 1), showing a good agreement between the results of CN and BN-based EN. Conclusion: The EN developed by Simon and co-workers (2008, 2009) based on BN can be used for belief mass updating the same way BN can be used for probability updating, with no need for using CN.@en

Offshore Oil&Gas facilities are attractive targets of intentional malicious attacks (security attacks) that may trigger cascading events (e.g., the release and dispersion of hazardous material and/or energy, fires, explosions) with consequences on people, environment, and assets. The severity of these consequences is potentially similar to those arising from major accident scenarios originated by conventional safety-related causes. Current practice in managing the risk of security attacks mostly relies on qualitative or semi-quantitative procedures developed over the years in the offshore Oil&Gas industry. In the present study, a systematic quantitative procedure is developed, based on a Bayesian Network (BN) approach, for calculating the probability of success of physical security attacks, taking into account both preventive and mitigative security intervention strategies. The procedure addresses the specific framework of the offshore Oil&Gas industry. A case study concerning an offshore fixed Oil&Gas platform allowed us to demonstrate the quality of the results that can be achieved and their potential towards the improvement of the security of the installations considered.@en

Fire is one of the main accident scenarios occurring in chemical and process plants, and it can lead to domino effects due to thermal radiation. Emergency response is necessary to prevent fire escalation, in addition to safety barriers. In major industrial fire accidents, backup is usually required in emergency response, due to the lack of emergency response capacity of a single emergency response department. A method addressing the optimal allocation of emergency response forces, specifically considering the front-line departments, is developed in the present study. The emergency response of the front-line departments can reduce the thermal radiation received by the equipment adjacent to the primary fire and thus prolong the time to failure of the equipment, such that the backups have more time to get to the fire scene. The allocation analysis of emergency response teams is carried out considering the dynamic ttf of an adjacent equipment item resulting from the change in time of the thermal radiation received. A timed colored hybrid Petri-net (TCHPN) approach is proposed to model the emergency response process. The probability of preventing fire escalation is obtained from the TCHPN model and the optimal allocation of firefighting forces is determined. A case study illustrates the proposed approach, two scenarios are compared and results show that if a request for backup can be issued immediately according to the fire state, fewer emergency forces can be deployed on the front line department, such as the reduction from 6 emergency response teams to 3 teams to maintain the success probability of 0.91. The influence of other factors such as the position of fire departments and the layout of tanks on the allocation of emergency forces is also discussed.@en