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![The framework for tolerability of risk, in light of the safety guidelines of HSE (2001) [23].](publication/355904120/figure/fig2/AS:1086397654007808@1636028793040/The-framework-for-tolerability-of-risk-in-light-of-the-safety-guidelines-of-HSE-2001.png)
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The utilization of risk acceptance criteria (RAC) can help a business to judge whether the risk level concerning any process involved in its working environment is acceptable or not, especially when the risk has a significant societal impact. Thus, the main intention of this study is to make known the current state-of-the-art concerning RACs and to...
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Context 1
... notions of "risk tolerance" and/or "risk tolerability" are preferred instead of "risk acceptance" [5]. Figure 2 can give the graphical support for the comprehension of the risk-tolerability framework. afety2021, 7, x FOR PEER REVIEW Figure 1. ...
Context 2
... that the elimination of all risks is unfeasible, several firms to use the term tolerable residual-risks, with the result that the terminology has cha The notions of "risk tolerance" and/or "risk tolerability" are preferred instead of acceptance" [5]. Figure 2 can give the graphical support for the comprehension risk-tolerability framework. ...
Context 3
... most common and flexible framework used for risk criteria divides risks into the above referred three bands of "unacceptable region", "ALARP region," and the "acceptable region" [23,24], and is exposed in Figure 2. ...
Context 4
... general, Figures 9-13 contribute significantly (with their statistical results)to answer (and/or elucidate) a number of significant questions (SQ) or issues associated with RACs, i.e., the SQ #1-SQ #10 that are designated in the last section of this study. Additionally, as far as the pie chart of Figure 12c is concerned, we clarify the following about the ways of generating RACs, as presented in the scientific literature; (i) the term "theoretical" characterizes any method that develops a consistent theoretical framework (e.g., with a mathematical background) to generate RACs, (ii) the expression "algorithmic" refers to the ones that involve a reliable algorithmic framework (e.g., with flow charts) in order to derive RACs, (iii) the designation "graphical" pertains to the methods that produce specific graphs to determine the different risk areas (e.g., acceptable, ALARP, etc.) that are essential for the RACs (as in Figures 2, 3, 6 and 7), (iv) the appellation "statistical" illustrates any method that, among other issues, incorporates a statistical analysis of OHS accident data to define the risk regions necessary for the RACs (such as the article referred to in Figure 5), and (v) the category "case study" includes the techniques that yield RACs, which relied on the study of various OHS systems (such as the one of an energy-production industry in Figure 5). Hence, the main categories regarding OHSRACs are the "quantitative" (with 74%) and "qualitative" (with 25%) ones, and on the other side, the primary types of them are the RACs of "SR" (40%), "IR" (27%), "CB" (21%), and "ENV"(5%). ...
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The data science era is characterized by data-driven automated decision systems (ADS) enabling, through data analytics and machine learning, automated decisions in many contexts, deeply impacting our lives. As such, their downsides and potential risks are becoming more and more evident: technical solutions, alone, are not sufficient and an interdis...
Citations
... In addition to a large corpus of industry-specific literature, many reports survey the use of risk thresholds across industries and jurisdictions (e.g. CCPS, 2009;Ehrhart et al., 2020;Flamberg et al., 2016;Linkov et al., 2011;Marhavilas & Koulouriotis, 2021). ...
Frontier artificial intelligence (AI) systems could pose increasing risks to public safety and security. But what level of risk is acceptable? One increasingly popular approach is to define capability thresholds, which describe AI capabilities beyond which an AI system is deemed to pose too much risk. A more direct approach is to define risk thresholds that simply state how much risk would be too much. For instance, they might state that the likelihood of cybercriminals using an AI system to cause X amount of economic damage must not increase by more than Y percentage points. The main upside of risk thresholds is that they are more principled than capability thresholds, but the main downside is that they are more difficult to evaluate reliably. For this reason, we currently recommend that companies (1) define risk thresholds to provide a principled foundation for their decision-making, (2) use these risk thresholds to help set capability thresholds, and then (3) primarily rely on capability thresholds to make their decisions. Regulators should also explore the area because, ultimately, they are the most legitimate actors to define risk thresholds. If AI risk estimates become more reliable, risk thresholds should arguably play an increasingly direct role in decision-making.
... As seen in Fig. 3, the risk tolerance criteria for most countries fall below the Hong Kong's landslide risk criteria with the exception of Malaysia, Vietnam and the UK. Vietnam, a developing country, advocated a highly liberal risk criterion for floods, whereas [39,43,[44][45][46]. ...
... A comprehensive survey regarding the application of risk acceptance criteria to risk assessment in occupational health and safety can be found in the study of [16]. ...
Road building sites are no exception to the fact that construction is one of the most dangerous businesses in the world. There are a number of concerns about the health and safety of the workers at these sites since they combine personnel, machinery, and construction equipment. The purpose of this paper is to determine, analyze, and compare the risks present at road building sites, and how they affect the health and safety of the workers. The study also examines workplace stress and psychosocial risk factors, which may have long-term effects on workers’ physical and mental health. To meet the goals of the research, risk evaluations for a specific construction project were carried out using the Analytic Hierarchy Process (AHP). Using the risk categories and risk factor hierarchy, the AHP compares data pairings. The skills, experience, judgments, and value system of the decision-makers were taken into account while deciding the amount of importance to give each criterion. The final risk rankings were established after calculating the overall priority numerically and running the necessary judgment consistency tests. The most significant risks to the health and safety of workers at road construction sites were identified by the study’s findings. The study additionally showed that psychosocial risk factors were important contributors to workplace stress and may have a negative impact on employees’ health and wellbeing. The results of the present study have important implications for risk management practices in the construction industry. Project managers can implement effective mitigation measures to reduce the likelihood and severity of accidents and injuries by identifying and evaluating the most critical risks associated with road construction sites. The findings also highlight the importance of addressing psychosocial risk factors and workplace stress in improving workers’ health and safety outcomes. Overall, this study underscores the need for a comprehensive approach to risk management that considers the diverse and complex factors contributing to construction site hazards.
... In this working and living environment, the analysis of risk events gives us the distribution of risks and likelihood values for specific activities. Different methods are applied, including IR profile calculation, the average IR for the activity, the Fatal Accident Rate (FAR), Individual Risk Per Annum (IRPA) and some others described in [34]. ...
In recent years, the maritime trade of crude oil has suffered notable perturbations caused by the unbalanced relationship between supply and demand. The COVID-19 pandemic caused a drop in oil consumption in 2019, followed by a reduction in production in 2020. The seaborne transport of oil accounts for approximately 50-60% of all crude oil in world production. The crude oil market is a crucial regulator of the global economy and instabilities in this market have noticeable effects on collective risks. The immediate risks that the society see are the changes in the cost of living, which are followed by political uncertainties. Less visible are the risks that these uncertainties have on shipping companies and the level of management stability they have to maintain in order to keep seagoing safe. This paper presents an update on the overall state of risk management for the crude oil tanker fleet, evidenced by EMSA and other international marine organisations. The previous paper, entitled Safety Assessment of Crude Oil Tankers, which applied the methodology of the Formal Safety Assessment (FSA), was published in 2018 and covered the historical data related to the fleet size, accident reports, amount of oil spilled on sea and the economic value of the crude oil transport business. The particular focus of this paper is on the evolution of the risk acceptance criteria over the years and the difference in the predictions from 2018 to the present day. The effects of the pandemic on crude oil shipping are discussed through the changes in the risks. Three of them are analysed: PLL (potential loss of lives), PLC (potential loss of containment) and PLP (potential loss of property). The representation of the risk applies the F-N curves among the risk acceptance criteria lines observed for different tanker sizes. Among the three risks, the paper exposes the vulnerability of the loss of containment risk, where the strong economic impact of the oil trade outweighs the environmental concerns. In relation to the PLC, the paper proposes the approach of relating the oil spill acceptability with the spill quantity and ship revenue instead of to the cost of cleaning or the cost of environment recovery.
... Similarly, several studies have investigated in detail risk analyses of marine accidents CONTACT Fatih Burak Izci fizci@marun.edu.tr [10,11]. A programmable logic controller (PLC)-based communication system has been proposed and is expected to reduce accidents in the shipyard by providing an uninterrupted communication environment and safer working conditions [12]. ...
... There are several approaches: Societal Value of Statistical Life (SVSL), Societal Willingness to Pay (SWTP), Implied Cost of Averting a Fatality (ICAF), Societal Life Saving Cost (SLSC), compensation to be paid for death by accident… [29][30][31][32] . A systematic review is given in [33]. ...
Risk is involved in the whole lifecycle of a structure: design, construction, utilization, and demolition. There is a close connection between reliability and risk. Contemporary building codes introduce consideration of reliability in structural design. Here, the concept of risk takes into account the level of consequences of a failure. Structural engineers, who are used to deterministic calculation procedures, are often unfamiliar with the uncertainties associated with risk analysis. An overview of the basic principles of risk management in civil engineering is presented in this paper.
... In this working and living environment, the analysis of risk events gives us the distribution of risks and likelihood values for specific activities. Different methods are applied, including IR profile calculation, the average IR for the activity, the Fatal Accident Rate (FAR), Individual Risk Per Annum (IRPA) and some others described in [34]. ...
In recent years, the maritime trade of crude oil has suffered notable perturbations caused by the unbalanced relationship between supply and demand. The COVID-19 pandemic caused a drop in oil consumption in 2019, followed by a reduction in production in 2020. The seaborne transport of oil accounts for approximately 50–60% of all crude oil in world production. The crude oil market is a crucial regulator of the global economy and instabilities in this market have noticeable effects on collective risks. The immediate risks that society sees are the changes in the cost of living, which are followed by political uncertainties. Less visible are the risks that these uncertainties have on shipping companies and the level of management stability they have to maintain in order to keep seagoing safe. This paper presents an update on the overall state of risk management for the crude oil tanker fleet, evidenced by EMSA and other international marine organisations. The previous paper, entitled Safety Assessment of Crude Oil Tankers, which applied the methodology of the Formal Safety Assessment (FSA), was published in 2018 and covered the historical data related to the fleet size, accident reports, amount of oil spilt on the sea and the economic value of the crude oil transport business. The particular focus of this paper is on the evolution of the risk acceptance criteria over the years and the difference in the predictions from 2018 to the present day. The effects of the pandemic on crude oil shipping are discussed through the changes in the risks. Three of them are analysed: PLL (potential loss of lives), PLC (potential loss of containment) and PLP (potential loss of property). The representation of the risk applies the F-N curves among the risk acceptance criteria observed for different tanker sizes. Among the three risks, the paper exposes the vulnerability of the loss of containment risk, where the strong economic impact of the oil trade outweighs the environmental concerns. In relation to the PLC, the paper proposes the approach of relating the oil spill acceptability with the spill quantity and ship revenue instead of to the cost of cleaning or the cost of environmental recovery.
... Similarly, several studies have investigated in detail risk analyses of marine accidents CONTACT Fatih Burak Izci fizci@marun.edu.tr [10,11]. A programmable logic controller (PLC)-based communication system has been proposed and is expected to reduce accidents in the shipyard by providing an uninterrupted communication environment and safer working conditions [12]. ...
This study reports the new data for 1028 non-fatal occupational accidents dated between January 2010 to April 2015 by applying the Analytical Hierarchy Process (AHP) technique. A comprehensive survey was conducted at four shipyards in Tuzla, Istanbul and Yalova region in Turkey and a workplace questionnaire appropriate for the AHP technique was carried out. The obtained results indicated that inadequate safety equipment and protective clothing, unsuitable usage of machines and tools, and disobeying Occupational Health and Safety (OHS) procedures were the most common risk factor of the happened accidents. Hence the preventive measures could be identified by analyzing non-fatal accident data. After the identification of the descriptive measures, the priority order of these measures was asked of the occupational safety professionals in the shipbuilding industry, and we used the AHP method to evaluate the results.
... Most of these methods are both standardized and described in the studies [11,12]. Most often distinguished qualitative, quantitative, and hybrid methods [13]. One of the positively proven in practice is the Fine and Kinney method [14], the main idea of which is to assess the individual risks of an individual worker, defined as the likelihood of injury or illness because of an existing hazard. ...
... In this step, the residual risk that is still acceptable or tolerable is defined. This residual risk is determined by the following factors, among others [37,38]: ...
Artificial intelligence can be used to realise new types of protective devices and assistance systems, so their importance for occupational safety and health is continuously increasing. However, established risk mitigation measures in software development are only partially suitable for applications in AI systems, which only create new sources of risk. Risk management for systems that for systems using AI must therefore be adapted to the new problems. This work objects to contribute hereto by identifying relevant sources of risk for AI systems. For this purpose, the differences between AI systems, especially those based on modern machine learning methods, and classical software were analysed, and the current research fields of trustworthy AI were evaluated. On this basis, a taxonomy could be created that provides an overview of various AI-specific sources of risk. These new sources of risk should be taken into account in the overall risk assessment of a system based on AI technologies, examined for their criticality and managed accordingly at an early stage to prevent a later system failure.
