Risk assessment of chemical process considering dynamic probability of near misses based on Bayesian theory and event tree analysis

Chen, Fanghao; Wang, Cangtian; Wang, Jinghong; Zhi, Youran; Wang, Zhirong

doi:10.1016/j.jlp.2020.104280

Cited by 26 publications

(9 citation statements)

References 21 publications

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“…Despite strenuous efforts to manage IMAs in the CP project, its durability planning is still alarmingly poor, with ineffective strategy and not engaging critical decisions which is influenced by warehouse-wide overpressure exposure or radiant heat and chemical attributes of DNB over physical hazards. Estimated workplace fatalities and serious injuries for Amuay CP projects involving IMAs range from 57 to 84% of accidents that are associated with vapour cloud explosion or unsafe condition (domino effects) induced by loss of containment and work environment (Chen et al , 2020a, b, c). Edwards (2018) reported that IMAs experienced 60% of the injuries and fatalities in 2015–2018, which were due to source of ignition and vapour cloud dispersion, due to the release of vinyl chloride inside the plant accounting for a further 16%.…”

Section: Imperfect Maintenance Actions In Chemical Plant Projectsmentioning

confidence: 99%

Implementation of automation system-based model checking for managing imperfect maintenance actions in chemical plant projects

Ismail

2022

IMDS

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PurposeThe chemical plant (CP) maintenance industry has been under increasing pressure by process designers to demonstrate its evaluation and information management of model checking (MC) on the durability’s performance and design of plant control instrument. This main problem has been termed as imperfect maintenance actions (IMAs) level. Although IMAs have been explored in interdisciplinary maintenance environments, less is known about what imperfect maintenance problems currently exist and what their causes are, such as the recent explosion in the Beirut city (4 August 2020, about 181 fatalities). The aim of this paper is to identify how CP maintenance environments could integrate MC within their processes.Design/methodology/approachTo achieve this aim, a comprehensive literature review of the existing conceptualisation of MC practices is reviewed and the main features of information and communication technology tools and techniques currently being employed on such IMA projects are carried out and synthesised into a conceptual framework for integrating MC in the automation system process.FindingsThe literature reveals that various CP designers conceptualise MC in different ways. MC is commonly shaped by long-term compliance to fulfil the requirement for maintaining a comfortable durability risk on imperfect maintenance schemes of CP projects. Also, there is a lack of common approaches for integrating the delivery process of MC. The conceptual framework demonstrates the importance of early integration of MC in the design phase to identify alternative methods to cogenerate, monitor and optimise MC.Originality/valueThus far, this study advances the knowledge about how CP maintenance environments can ensure MC delivery. This paper highlights the need for further research to integrate MC in CP maintenance environments. A future study could validate the framework across the design phase with different CP project designers.

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Section: Imperfect Maintenance Actions In Chemical Plant Projectsmentioning

confidence: 99%

Implementation of automation system-based model checking for managing imperfect maintenance actions in chemical plant projects

Ismail

2022

IMDS

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“…In addition to the above methods, as a disaster, the assessment method of epidemic risk can also make reference to some common risk assessment methods, such as risk probability-based modeling and assessment [43], risk modeling and assessment based on index system [44], [45], risk modeling and assessment based on GIS(Geographic Information System) [46], [47], etc. However, these methods all need to establish a special risk assessment model.…”

Section: B the Assessment Of Epidemic Riskmentioning

confidence: 99%

Research on Risk Assessment Model of Epidemic Diseases in a Certain Region Based on Markov Chain and AHP

Yang

Xie

et al. 2021

IEEE Access

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Epidemic risk has great uncertainty and harmfulness, which poses a potential threat to public health in a certain region. Establishing a special risk assessment system to assess and predict the potential epidemic risk of a region can effectively avoid or reduce the impact of epidemic risk. Therefore, this paper combs the related factors that affect the epidemic risk, and proposes an epidemic risk assessment model based on 12 indicators by combining Markov chain and AHP. The model can assess the epidemic situation in a certain region from four aspects: the probability of risk occurrence, the probability of loss, the possibility of risk disappearance and risk duration, so as to provide detailed data for the risk management and control of epidemic in the region, and help the epidemic prevention work to be carried out in a targeted way. Finally, the case analysis and method comparison are carried out,and the results show that the model proposed in this paper is reasonable and feasible.

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“…e safety evaluation based on the Bayesian algorithm can not only explain the safety evaluation process quantitatively, but also embody the accumulation and continuity of safety evaluation [7][8][9]. erefore, the information security quantitative model based on the Bayesian algorithm can fully taking into account the subjective judgment data of various decision makers, and it can also prove the continuity and accumulation of safety assessment.…”

Section: Introductionmentioning

confidence: 99%

Application of Bayesian Algorithm in Risk Quantification for Network Security

Lei

2022

Computational Intelligence and Neuroscience

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Network security risk quantification involves both technical and management aspects. Risk quantification has great uncertainty and cannot be fully quantified. Therefore, the fully objective realization of network information security risk quantification is not yet mature. This paper analyzes and quantifies the network security risks caused by various threat sources through a network security risk quantification model based on the Bayesian algorithm. By combining expert knowledge, the conditional probability matrix under the inference rule of the Bayesian algorithm is clarified, and the subjective judgment information of experts on the damage degree of the target information system is synthesized into the prior information system of network security threat. The Bayesian algorithm is used to realize the observation node of objective assessment information and combining subjective security threat levels to achieve continuity and accumulation of security assessments. The error is about 3%, which has a very good effect on the quantification of network security risk.

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Risk assessment of chemical process considering dynamic probability of near misses based on Bayesian theory and event tree analysis

Cited by 26 publications

References 21 publications

Implementation of automation system-based model checking for managing imperfect maintenance actions in chemical plant projects

Implementation of automation system-based model checking for managing imperfect maintenance actions in chemical plant projects

Research on Risk Assessment Model of Epidemic Diseases in a Certain Region Based on Markov Chain and AHP

Application of Bayesian Algorithm in Risk Quantification for Network Security

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