Risk and safety in large-scale socio-technological (military) systems: a literature review

Bakx, Gwendolyn C.H.; Nyce, James M.

doi:10.1080/13669877.2015.1071867

Cited by 9 publications

(4 citation statements)

References 42 publications

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“…Among the many methods, which can be expressed in hundreds of ways, risk assessment decision matrices are the most popular because of their broad and easy-to-understand application areas (Gul & Ak, 2018). The method, which aims to rank risks, risk sources, or risk treatments according to risk level, was initially used in military systems and later became widespread, being preferred primarily in many sectors (Bakx & Nyce, 2017).…”

Section: Methodsmentioning

confidence: 99%

Occupational health and safety in flour Mills: A research and risk assessment

Özbakır

2024

International Journal of Agriculture Environment and Food Sciences

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Flour mills are one of the workplaces with occupational health hazards due to irregular workplaces and environments where insufficient attention is paid to workers’ safety. In this context, considering the extent of difficulties faced by workers in flour mills, hazards and risks that could affect the health and occupational safety of workers were investigated in a sample of flour mills in Iğdır province. The data obtained as a result of the research was ranked using the matrix method. The study identified 68 specific risks, of which 38% were identified as unacceptable risks requiring immediate action and 33% as risks requiring medium-term action. The results show that among the factors negatively affecting the health of workers, the respiratory hazard level of wheat dust with RS:15 (l:3, s:5) and the explosion hazard with RS:20 (l:4, s:5) occupy significant positions. Despite the emphasis on the importance of hygiene standards, serious deficiencies were identified, such as RS:20, which is considered high risk. In addition, the presence of many machines, such as conveyors, silos, compressors and rollers, was found to increase the risks on the system in the range of RS:20-25, which could lead to serious injury or death. Bacteria and microorganisms, such as RS:16-18, proliferate due to the low availability of personal hygiene facilities in the factory. For each identified risk, the necessary control measures are proposed and it is emphasized that protective measures should also be taken even after the implementation of these measures. Among the factors that negatively affect the health of workers in flour mills are the lack of use of personal protective equipment, working in dirty conditions, the presence of elements that can cause respiratory problems, as well as injuries related to carrying heavy loads on slippery floors and using unprotected machinery.

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Section: Methodsmentioning

confidence: 99%

Occupational health and safety in flour Mills: A research and risk assessment

Özbakır

2024

International Journal of Agriculture Environment and Food Sciences

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“…In addition, Resilience Engineering (RE), an effective tool for risk management with the consideration of an inherent complexity of system [ 86 ], can be adopted for E&M RMAA research. Safety and risk management research works involve in-depth investigation of how systems perform, and the interactions between agents, rather than individual agents [ 87 ]. RE has been regarded as a safety management paradigm that is suited to the nature of complex socio-technical systems (CSTSs).…”

Section: Limitations and Area For Future Researchmentioning

confidence: 99%

A Bayesian Network Model for Reducing Accident Rates of Electrical and Mechanical (E&M) Work

Chan

Wong

Hon

et al. 2018

IJERPH

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Accidents in Repair, Maintenance, Alteration, and Addition (RMAA) work have become a growing concern, in recent years. The repair and maintenance works of electrical and mechanical (E&M) installations involves a variety of trades, a large number of practitioners and a series of high-risk activities. The uniqueness of E&M work, in the RMAA sector, requires a discrete and specific research to improve its safety performance. Understanding the causal relationships between safety factors and the number of accidents becomes crucial to develop a more effective safety management strategy. The Bayesian Network (BN) model is proposed to establish a probabilistic relational network between the causal factors, including both safety climate factors and personal experience factors that have influences on the number of accidents related to E&M RMAA work. The data were collected using a survey questionnaire, involving a hundred and fifty-five E&M practitioners. The BN results demonstrated that safety attitude and safety procedures were the most important factors to reduce the number of accidents. The proposed BN provides the ability to find out the most effective strategy with the best utilization of resources, to reduce the chance of a high number of E&M accidents, by controlling a single factor or simultaneously controlling, both, the safety climate and personal factors, to improve safety performance.

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Section: Introductionmentioning

confidence: 99%

“…In response to rising concerns about the technology and its risks, technology risk management has been considered in various branches of science, industry, and policymaking. 9 Scheer 10 investigated the risk government considering the issue of emerging technologies. Hellstorm, 11 explaining the factors such as the speed of technological change, the changing nature of accidents, and extension of the scope of risk consequences, stressed the need for developing a new generation of risk assessment methods in the field of technology assessment.…”

Section: Introductionmentioning

confidence: 99%

Forward and backward risk assessment throughout a system life cycle using dynamic Bayesian networks: A case in a petroleum refinery

Ashrafi

2020

Quality & Reliability Eng

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In this paper, risk modeling was conducted based on the defined risk elements of a conceptual risk framework. This model allows for the estimation of a variety of risks, including human error probability, operational risk, financial risk, technological risk, commercial risk, health risk, and social and environmental risks. Bayesian network (BN) structure learning techniques were used to determine the relationships among the model variables. By solving a bi‐objective optimization problem applying the genetic algorithm (GA) with the Pareto ranking approach, the network structure was learned. Then, risk modeling was performed for a petroleum refinery focusing on HydroDeSulfurization (HDS) technology throughout its life cycle. To extend the model horizontally and make it possible to evaluate the risk trend throughout the technology life cycle, we developed a dynamic Bayesian network (DBN) with three‐time slices. A two‐way forward and backward approach was used to analyze the model. The model validation was performed by applying the leave‐one‐out cross‐validation method.

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Risk and safety in large-scale socio-technological (military) systems: a literature review

Cited by 9 publications

References 42 publications

Occupational health and safety in flour Mills: A research and risk assessment

Occupational health and safety in flour Mills: A research and risk assessment

A Bayesian Network Model for Reducing Accident Rates of Electrical and Mechanical (E&M) Work

Forward and backward risk assessment throughout a system life cycle using dynamic Bayesian networks: A case in a petroleum refinery

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