Safety Risk Analysis Research Articles

Dynamic Analysis and Temporal Governance of Safety Risks: Evidence from Underground Construction Accident Reports

Due to the complexity and dynamics of underground construction projects, safety risk management has experienced significant challenges restricting the sustainable development of underground space. The research on risk causal chains and risk coupling has yet to reveal the dynamic interactive characteristics of these risk factors and their temporal relationships over time. This study utilized a complex system view for safety risk analysis, using 37 accident investigation reports of underground construction projects. Combined with two novel and emerging analytical methods, temporal qualitative comparative analysis and crisp-set qualitative comparative analysis, this study discusses the temporal relationship of risk factors to the cause of accidents and explores the multi-actor coupling characteristics of management risk. The findings indicate that (1) compared with general construction projects, underground construction should pay more attention to management safety risks because they have an obvious time lag effect expressed in all accident causation paths, namely, preceding management risk, management risk, and machine/material risk cross-concurrently, and management risk initiation and (2) underground construction project management risks have three key main paths, namely, single-actor-dominated management deficiency (supervisors, owners, and subcontractors that cause management risks as a single-core actor) and dual-actor-dominated management deficiency (owner and subcontractor as dual core actors of management risk). Multi-actor-dominated management deficiency (owners, subcontractors, and supervisors are the multiple core actors of management risk). This study thus developed a temporal governance framework of underground construction safety risks based on the synergy of multi-actors and proposed risk governance strategies, such as synergistic multi-actor governance, to consider the temporal relationship of safety risk. This study further reveals the temporal and coupling characteristics of safety risks to enrich the risk casual chain theory and risk coupling theory and establish a systematic risk analysis framework for new guidance for safety and risk management for underground construction projects.

Research on coal mine safety risk evolution and key hidden dangers under the perspective of complex network

In order to find out the main causes of coal mine safety accidents and improve the pertinence of coal mine safety risk management and control, the identification and analysis of coal mine safety risks and hidden dangers are carried out based on the analysis of coal mine accident reports. Combing the complex network theory, a complex network model for the evolution of coal mine safety risks is constructed. The key elements that affect coal mine safety risk accidents are obtained through quantitative research on the characteristic indicators of the complex network model of coal mine safety risks. And the key nodes of coal mine safety risk spread network are obtained through network interference to the overall efficiency. The research results show that the complex network of coal mine safety risks illustrate the characteristics of a small-world network, and the spread of a certain risk is likely to cause coal mine safety accidents. Strengthening the risk management and control of hidden dangers with higher intermediate centrality can isolate the spread of coal mine safety risks and reduce the possibility of coal mine accidents.

Analysis of Occupational Safety and Health Risk in the Private Hospital Laboratory

Analysis of Occupational Safety and Health Risk in the Private Hospital Laboratory

Occupational Health & Safety Risk Analysis with HIRADC Method in Building Construction Project X

Occupational Health & Safety Risk Analysis with HIRADC Method in Building Construction Project X

Analysis and control of occupational safety risks using the HIRARC method in the Machining Workshop

This qualitative study focuses on occupational safety and health in vocational school machining workshops to identify significant risks related to training practices. Workplace accidents are considered a serious threat to workers and equipment, potentially affecting productivity and environmental safety. Observations at several vocational schools, especially at SMK Negeri 1 Batipuh, showed low student awareness and compliance with OHS regulations, increasing the risk of risky behaviour and accidents. To address this, the research used the Hazard Identification, Risk Assessment, and Risk Control (HIRARC) method, which systematically identifies hazards, evaluates risks based on severity and likelihood, and proposes control measures. The research at SMK Negeri 1 Batipuh involved direct observation, interviews, and analysis of SOPs in the workshop, finding significant risk variations in workshop conditions, lathe operations, welding, material handling, hand tool use, and machine protection. The results highlighted the predominance of intermediate risks in all-hazards analyzed, emphasizing the importance of developing more effective risk management strategies. This research aims to reduce accidents and improve student safety during training by addressing existing OHS implementation gaps and implementing appropriate risk controls. In addition to filling a gap in the literature, this study provides practical insights for improving OHS practices in vocational schools.

Quantitative analysis of toxicity risks in the operation of ammonia-fueled tugboats

As efforts to conserve energy and reduce emissions in the global shipping industry intensify, people are constantly looking for new types of energy to replace traditional fuels. Ammonia is considered a novel energy source due to its potential for carbon-neutral shipping when produced from renewable energy sources and is extremely promising for the shipping industry. In this study, the fuel toxicity risk of ammonia-fueled ships under operating conditions was quantified for the first time. The assessment process adopts the traditional quantitative risk assessment (QRA) framework with accident probability calculations based on Bayesian theory, and the process of partial quantification of consequences also guides the delineation of safety zones. The results of the study suggest that ammonia-powered tugboats are at a higher risk of toxic accidents during operation than accidents at sea, but both are within the acceptable limits of current international maritime safety and environmental standards. Finally, safety measures and risk mitigation strategies are proposed based on the study results. This provides important support in safety risk analysis for the design, production and operation of subsequent ammonia fueled vessels and is of great theoretical and practical importance.

A systematic review of the integration between occupational and process safety risk analysis methodologies

Safety considerations in process industries primarily revolve around process and occupational safety. In recent times, there has been a growing emphasis on the development and application of risk estimation frameworks to provide a more holistic evaluation of these critical risk types. While previous studies have offered valuable insights into the concurrent assessment and management of occupational and process hazards, a comprehensive review of frameworks and models incorporating risk estimation dimensions is lacking. Accordingly, this review aims to systematically examine studies that have devised methods to integrate the estimation of both occupational and process risks, with a focus on categorizing applied criteria for risk estimation. A thorough literature review was conducted using reputable databases, including Web of Science and Scopus, resulting in the identification of 16 studies meeting the predetermined inclusion criteria. Subsequently, the selected studies were classified into four categories: (1) New Framework Developments, (2) Existing Framework Adjustments, (3) Hybrid Frameworks, and (4) Management System/Risk Management Integration. Furthermore, employing a relevant risk dimension perspective, the identified studies were categorized based on four primary dimensions: (a) Scenario Probability, (b) Scenario Consequences, and (c) Economical Damage. It is crucial to note that the existing literature on occupational-process hazards and associated risk dimensions lacks reliable and robust studies. Therefore, further research efforts are imperative to effectively evaluate, quantify, and precisely delineate diverse risk dimensions within the integrated domain of occupational-process safety.

Joint safety and security risk analysis in industrial cyber‐physical systems: A survey

Joint safety and security risk analysis in industrial cyber‐physical systems: A survey

Medication Error Prevention Using Healthcare Failure Mode And Effect Analysis At Clinical Pharmacy Installation

Medication error is the second most common patient safety incident worldwide. Medication errors can be defined as unintentional failures in medication services that have the potential to cause harm to patients. Maintaining safe health services is highly dependent on the ability of service providers to proactively conduct patient safety risk analysis, one of which is using the Healthcare Failure Mode and Effect Analysis (HFMEA) method. This study was aimed at obtaining the HFMEA design as an effort to prevent medication errors at Company X Clinical Pharmacy Installation. The research method used is qualitative research with a specific type of Operations Research. Data collected by in-depth interviews, observation, secondary data analysis, and focus group discussion. The results of this study found factors that cause medication errors to occur from organizational factors and staff factors. These results then analyzed for the HFMEA design which obtained 11 risks that required attention and then 14 action plans are made to overcome them. This study successfully developed HFMEA design to prevent medication error in Company X Clinical Pharmacy Installation.

A Safety Risk Analysis of a Steel-Structure Building Using an Improved Controlled Interval and Memory Model

Scholars and engineers have increasingly focused on the safety of steel-structure buildings. An accurate analysis can substantially reduce the collapse probability of these buildings. This paper proposes a novel risk analysis model to assess the safety of steel-structure buildings. The vector entropy method and weight clustering were used to improve the controlled interval and memory (CIM) model. The proposed model has the advantages of a straightforward modeling approach, strong adaptability, and logical relationships. The new strategy improves the reliability and stability of the CIM model results when the maximum membership principle is not applicable. The Jiangxi Exhibition Center in China, which has a steel truss roof, is used as a case study. The results indicate a high safety risk of the project and the need for maintenance and repair. The improved CIM model has higher stability and adaptability for analyzing the safety risks of steel structure than the standard CIM model.

A Method for Evaluating Systematic Risk in Dams with Random Field Theory

The parameters of gravity dams and foundation materials objectively exhibit spatial variability due to environmental and load influences, which significantly affect the safety status of dam structures. Therefore, a safety risk analysis method for a gravity dam–foundation system based on random field theory is proposed in this paper. Spatial variabilities in materials are particularly considered by using the finite element method. Then, composite response surface equations for the performance function (PF) of strength and stability failure are established, and then, the system failure risk is obtained using the Monte Carlo method. The proposed method solves the problem wherein the effect of spatial variability on failure risk cannot be reflected accurately by the performance function of multi-element sliding paths, and the difficulties in solving the failure risk of the series–parallel system due to multiple failure paths and their complex correlations. The application of a gravity dam shows that the developed method overcomes the disadvantages of the traditional method, such as the homogenization of the spatially random characteristics of parameters and the overestimation of failure risk in the system due to large variance estimation.

The Challenges of Blood Sample Delivery via Drones in Urban Environment: A Feasibility Study through Specific Operation Risk Assessment Methodology

In recent years, Unmanned Aircraft System (UAS) usage in the medical sector as an alternative to traditional means of goods transport has grown significantly. Even though the reduced response time achieved with UASs can be lifesaving in critical situations, their usage must comply with technological constraints such as range, speed and capacity, while minimizing potential risks. In this paper, the feasibility of a drone operation dedicated to the transport of blood samples in an urban area is studied through a safety risk analysis. The assessment utilizes the Specific Operation Risk Assessment (SORA) framework, in line with current European regulations, and extends it to define flight trajectories with minimal risk. A case study in the Helsinki urban area is used as a reference, with an exemplary case of commercial drone transportation of blood samples between the Töölö and Malmi Hospitals. By leveraging the drone performance capabilities and minimizing the risk for people on the ground, this approach demonstrates that medical delivery using drones in densely populated urban environments remains challenging. Nonetheless, it argues that the proposed method can enhance risk awareness and support the planning of feasible operations.

Systemic Risk Analysis of Safety, Progress, and Investment in the Construction of a Water Transfer Project and the Importance of Common Cause Failure

Safety, progress, and investment risks are correlated during the construction period of large-scale water transfer projects. However, previous studies have only considered individual risk factors, overlooking the potential systemic risk posed to safety, progress, and investment, as well as any underlying common cause failures. Since traditional risk analysis methods are ill-suited to addressing common cause failure, this paper’s objective was to establish a comprehensive evaluation index framework and to identify the basic events of common cause failure. To do that, we developed a risk analysis method that models common cause failure based on a Bayesian network for assessing that systemic risk. The Henan Section of the Yangtze-to-Huaihe River Water Diversion Project in China was then used as a case study. The results show that a variety of common cause failure events, such as epidemic disease, design alteration, lagged approval process, heavy rain in the flood season, renewal material and failing equipment, construction accidents, and external interference, can significantly impact the safety, progress, and investment systemic risk. Design alteration poses the greatest risk, with renewal material and failing equipment exerting the strongest influence among all common cause failure events. It is also possible to elucidate the predominant causal chains; specifically, the contributing influence of each basic failure event to the systemic risk can be clarified by adjusting their respective initial state. The failure of renewal material and failing equipment was found to significantly increase the safety risk. This study effectively simulated the complex causal relationships and uncertainties of pertinent risk factors, thereby enhancing our understanding of the systemic risk associated with safety, progress, and investment in large-scale water transfer projects.

Coupled analysis and simulation of safety risk in subway tunnel construction by shallow-buried excavation method based on system dynamics

To address the existing shortcomings in the research on the coupling of safety risk factors in subway tunnel construction using the shallow-buried excavation method, this paper conducts a coupled analysis and dynamic simulation of the safety risks associated with this construction method. Firstly, by analyzing the mechanisms and effects of risk coupling in shallow-buried excavation construction of subway tunnels, this study divides the risk system into four risk subsystems (human, material, management, and environment), establishes an evaluation index system for the coupling of safety risks, calculates the comprehensive weight values of the risk indicators using the AHP-entropy weight method, and constructs a risk coupling degree model by combining the inverse cloud model and efficacy function. Subsequently, based on the principles of system dynamics, a causal relationship diagram and a system dynamics simulation model for the coupling of “human-material” risks in construction are established using Vensim PLE software. Finally, the case study of the underground excavation section of Chengdu Metro Line 2 is employed to perform dynamic simulation using the established model. By adjusting the relevant risk coupling coefficients and simulation duration, the impact of the coupling of various risk factors on the safety risk level of the human-material coupling system is observed. The simulation results demonstrate that: 1) Heterogeneous coupling of human and material risks has a particularly significant effect on the system’s safety risks; 2) Violations by personnel and initial support structure defects are key risk coupling factors. The findings of this study provide new insights for decision-makers to assess the safety risk of shallow-buried excavation construction in subway tunnel.

Efficient distributed association management method of data, model, and knowledge for digital twin railway

ABSTRACT Digital twin railway is a pivotal foundation for the intelligent construction and maintenance of railway engineering projects within extensive open spaces. Its essence is the integrated representation and association management of multi-granularity spatiotemporal data, executable analysis models, and professional knowledge. These elements are characterized by the prominent characteristics of multi-source, heterogeneity, and massive volume. However, current decentralized and independent management strategies often neglect the dynamic coupling relationships between them, and numerous multi-path joins and conversion aggregation operations exist across various spatial scale applications. Consequently, this results in challenges such as the inability to dynamically couple data-model-knowledge and conduct global association retrieval, thereby limiting the potential for real-time analysis and intelligent application capabilities. To address these problems, we first constructed a tripartite graph model ( DMK − Graph model ) that explicitly associates temporal, spatial, and interactive relationships. Subsequently, an association management architecture was proposed, accompanied by a global association graph index ( DMK − Graph index ) and a global-local indexing mechanism. Finally, a prototype system for railway data-model-knowledge association management was developed. The effectiveness of the distributed association management method was demonstrated by employing a case study of high-temperature safety risk analysis in railway tunnel engineering with multi-physics field coupling.

Occupational Safety And Health Risk Analysis (K3) Using The HIRADC Method On Cleaning service Workers In The Health Segment

Occupational Safety And Health Risk Analysis (K3) Using The HIRADC Method On Cleaning service Workers In The Health Segment

Safety Risk Analysis of Urban Viaduct Construction Based on Dynamic Weight

The safety risk analysis of urban elevated bridge construction is an important management method to reduce the loss of safety accidents, and it has significant scientific research value and engineering application value. Therefore, this study proposes a novel analysis method to address these challenges. Firstly, this paper constructs a Work Breakdown Structure (WBS)–Risk Breakdown Structure (RBS) matrix for the safety risk of urban elevated bridge construction in order to achieve a comprehensive and complete identification of the indicator system. Then, a combination of static weights and dynamic weights calculation methods is developed. The static weights are obtained using the analytic hierarchy process, while the dynamic weights are obtained based on the relationship between the dynamic scores of construction safety risk indicators in different construction stages and the preset evaluation levels. Finally, a case study of the Longlingshan elevated bridge project in Wuhan, China, is conducted to validate the feasibility of the proposed model and its potential application in projects. The case analysis for the first time reveals that with the progress of construction, the weights of each indicator continuously change, and the secondary indicators related to environmental factors, such as extreme high-temperature weather, undergo the greatest changes. A comparison of different dynamic weight calculation methods is conducted to highlight the advancement of the proposed model. The research findings of this paper will provide new insights and guidance for improving the construction safety of urban elevated bridge projects.

Occupational safety & health risk analysis in formwork in high-rise building projects

The implementation of Occupational Health and Safety Management systems remains a significant concern, particularly in the context of multi-storey building construction projects. Within the realm of these complex endeavors, the management of work-related accidents during formwork operations is of paramount importance. This research employs a rigorous methodology involving questionnaire distribution and interviews, complemented by advanced analytical tools such as the Frequency Adjusted Importance Index (FAII) and Bow Tie Analysis. The study focuses on the Indonesian Development University’s high-rise building project, systematically assessing potential hazards associated with formwork activities. Furthermore, this research evaluates the inherent risk levels and proposes comprehensive control measures to mitigate these hazards effectively. By shedding light on the intricate interplay between safety management and high-rise construction, this study contributes to the enhancement of occupational safety and health practices in the construction industry, ultimately promoting safer and more efficient work environments.

Blockchain technology design based on food safety and halal risk analysis in the beef supply chain with FMEA-FTA

Beef has an important role in the health of the body. Food safety and halal are the main factors for consumers in purchasing beef. However, in reality, several activities in the beef supply chain result in status changes to be unsafe and not halal for consumption. This occurs due to weak food safety and halal supervision in the beef supply chain system. Therefore, this study proposes the use of blockchain technology to strengthen the food safety and halal supervision system in the beef supply chain. The objectives of this study are (1) to identify food safety and halal risk factors, and (2) to develop a blockchain technology design for mitigating food safety and halal risks in the beef supply chain. This research uses the FMEA method to measure risks and FTA for risk analysis. The results showed that 30 risks were identified in the beef supply chain. The highest risk is the absence of a halal certificate on the product. The 30 risks are grouped into 4 risks that are included in extreme priority risk, 11 risks in high priority risk, 4 risks in moderate risk, and 11 risks as acceptable risk. Based on these results, the role of blockchain technology to minimize risk is in the flow of data, and transactions will be easier to track, more transparent, and safer to use as part of the control and supervision system for food safety and halal standards in the beef supply chain. This research has implications for transparency in the supply chain, the accuracy of product track records, prevention of food poisoning, improving halal compliance, risk management and thus increasing consumer confidence.

Aviation Safety Risk Analysis Based on Bayesian Network Modeling

The occurrence of serious flight accidents not only brings huge economic losses to airlines but also poses a great threat to passengers' lives. The occurrence of serious flight accidents will not only bring great economic losses to airlines but also cause great threats to the lives of passengers. Therefore, in this paper, based on the flight records of different flight crews, flight routes, airports, and specific flight conditions, aircraft safety risk analysis is conducted to calculate and evaluate the risk propensity. Firstly, the data are preprocessed, and then the QAR data are clustered to extract the key data items affecting the safe flight of the aircraft; then the data are transformed to the attached data, and a hierarchical clustering model is established based on the K-means clustering algorithm, which classifies the factors affecting the safety quality of the aircraft flight into the three main aspects of environmental factors, crew maneuvering, and aircraft state, and the key parameters are weighted by the Random Forest algorithm. weights of the key parameters. Then, based on the 3 criterion, the outliers exceeding 3 were selected as the dependent variables leading to the occurrence of deviation; based on the three-layer model, a Bayesian neural network model based on the three-layer model, and then determine the Bayesian nodes; finally, calculate the Bayesian node probability, and then provide a reasonable quantitative description of the flight maneuver.