Clarifying the concept of operational risk assessment in the oil and gas industry

Yang, Xue; Haugen, Stein; Paltrinieri, Nicola

doi:10.1016/j.ssci.2017.12.019

Cited by 55 publications

(27 citation statements)

References 66 publications

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“…Another drawback is that traditional static analysis is too static and not regularly updated, thereby being unable to capture the changes in the process and plan [50], [51]. The drawbacks of the traditional methods of risk assessment need improvement under dynamic risk [52]. Passenger safety, security and risk management are the primary goals of railway systems, and managing and enhancing safety and ensuring reliable environments within a railway station are one of the most significant challenges.…”

Section: Railway Station Safety and MLmentioning

confidence: 99%

Learning From Accidents: Machine Learning for Safety at Railway Stations

Alawad

Kaewunruen

2020

IEEE Access

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Section: Railway Station Safety and MLmentioning

confidence: 99%

Learning From Accidents: Machine Learning for Safety at Railway Stations

Alawad

Kaewunruen

2020

IEEE Access

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“…Conceptually, a process deviation can lead to a hazardous consequence if not interrupted by the successful operation of the safeguard layer [38][39][40]. The "Norsk Sokkels Konkuranseposisjon" (NORSOK) standards are developed by the Norwegian petroleum industry to ensure adequate safety with a balanced cost for petroleum industry developments and operations through the guideline Z-013 [41][42][43]. The Netherlands advisory council of dangerous substances issued several publications from the old CPR (Commissie voor de Preventie van Rampenthat, still called CPR guidelines [44], being the most important the CPR18E or "Purple Book", analyzing the loss of containment events in chemical processes and the modeling of the associated flammable clouds, their dispersion, and toxic effects, and finally the EN 16,991:2018, a standard based on the concept of Risk Based Inspection and Maintenance issued for chemical and power generation, chemical processes, and manufacturing facilities providing guidance for risk evaluation of equipment in parallel to the inspection and maintenance operations [45,46].…”

Section: Gtmentioning

confidence: 99%

Analysis and Characterization of Risk Methodologies Applied to Industrial Parks

et al. 2020

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It is important to evaluate the risks in industrial parks and their processes due to the consequences of major accidents and especially the domino effect. Scientific works present a wide possibility of models to deal with these situations. In this work, based on the information extracted from the scientific literature, six groups of risk methodologies are defined, analyzed, and characterized with methods that cover the standards, preventive, probabilistic, traditional, modern, and dynamic evaluation that are applied or could be used in industrial parks. It also tries to achieve the objective of determining which are more appropriate if the possible situations and causes that can produce an accident are taken into account, identifying and evaluating them with characteristics of simultaneity and immediacy, determining the probability of an accident occurring with sufficient advance in time to avoid it under the use of a working operational procedure. There is no definitive methodology, and it is necessary that they complement each other, but considering the proposed objective, the integrated application of traditional methodologies together with the management of safety barriers, the dynamic evaluation of risks, and the inclusion of machine learning systems could fulfill the proposed objective.

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“…Thus, during the last few years, new approaches and methodologies have been developed for risk assessment and management considering the dynamic evolution of risk [68]. The main objective of the dynamic risk assessment is to provide an estimate of the risk over time that reflects the current condition of the system, considering for it the integration of the effective aggregation of heterogeneous information [69].…”

Section: Dynamic Management Industry 40 Provides Digital Managementmentioning

confidence: 99%

Emerging Risk Management in Industry 4.0: An Approach to Improve Organizational and Human Performance in the Complex Systems

et al. 2019

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Industry 4.0 in the contemporary operating context carries important sources of complexity. This context generates both traditional risks and emerging risks that must be managed. The management of these risks includes both industrial risks and occupational risks, since they are heavily interlinked. The human factor can be considered the main link between both types of risks. Thus, understanding risks originating from human errors and organizational weaknesses as causes of accidents and other disruptions in complex systems requires elaborating sophisticated modeling approaches. Therefore, the objective of this paper is to propose an organizational and human performance approach to improve the emerging risk management linked to the complex systems, like as Human-Machine Interactions (HMI) and Human-Robot Interaction (HRI). To fulfill this objective, we first introduce the concept of emerging risk linked to human factor. Then, we introduce the concept of emerging risk management in the Industry 4.0 context. Under this complex context, we expose the concept considering the current models of risk management. Finally, we discuss how enhancing human and organizational performance can be achieved through risk management in complex systems linked to Industry 4.0. Therefore, we conclude that while Industry 4.0 brings numerous advantages, it must contend with emerging risks and challenges associated with organizational and human factors. These emerging risks include industrial risks as well as occupational risks. Moreover, the human factor aspect of Industry 4.0 is directly linked to industrial emerging and occupational emerging via context of operations. To cope with these new challenges, it is necessary to develop new approaches. One of such approaches is Complex System Governance. This approach is discussed along with the need for adequate organizational and human performance models dealing with, for example, experience from other domains such as nuclear, space, aviation, and petrochemical.

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Clarifying the concept of operational risk assessment in the oil and gas industry

Cited by 55 publications

References 66 publications

Learning From Accidents: Machine Learning for Safety at Railway Stations

Learning From Accidents: Machine Learning for Safety at Railway Stations

Analysis and Characterization of Risk Methodologies Applied to Industrial Parks

Emerging Risk Management in Industry 4.0: An Approach to Improve Organizational and Human Performance in the Complex Systems

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