Traditional Hazard Research Articles

Comparing Optical and Custom IoT Inertial Motion Capture Systems for Manual Material Handling Risk Assessment Using the NIOSH Lifting Index

Assessing musculoskeletal disorders (MSDs) in the workplace is vital for improving worker health and safety, reducing costs, and increasing productivity. Traditional hazard identification methods are often inefficient, particularly in detecting complex risks, which may compromise risk management. This study introduces a semi-automatic platform using two motion capture systems—an optical system (OptiTrack®) and a Bluetooth Low Energy (BLE)-based system with inertial measurement units (IMUs), developed at the Biomedical Engineering Laboratory, Universidad de Concepción, Chile. These systems, tested on 20 participants (10 women and 10 men, aged 30 ± 9 years without MSDs), facilitate risk assessments via the digitized NIOSH Index method. Analysis of ergonomically significant variables (H, V, A, D) and calculation of the RWL and LI showed both systems aligned with expected ergonomic standards, although significant differences were observed in vertical displacement (V), horizontal displacement (H), and trunk rotation (A), indicating areas for improvement, especially for the BLE system. The BLE Inertial MoCap system recorded mean heights of 33.87 cm (SD = 4.46) and vertical displacements of 13.17 cm (SD = 4.75), while OptiTrack® recorded mean heights of 30.12 cm (SD = 2.91) and vertical displacements of 15.67 cm (SD = 2.63). Despite the greater variability observed in BLE system measurements, both systems accurately captured vertical vertical absolute displacement (D), with means of 32.05 cm (SD = 7.36) for BLE and 31.80 cm (SD = 3.25) for OptiTrack®. Performance analysis showed high precision for both systems, with BLE and OptiTrack® achieving precision rates of 98.5%. Sensitivity, however, was lower for BLE (97.5%) compared to OptiTrack® (98.7%). The BLE system’s F1 score was 97.9%, while OptiTrack® scored 98.6%, indicating both systems can reliably assess ergonomic risk. These findings demonstrate the potential of using BLE-based IMUs for workplace ergonomics, though further improvements in measurement accuracy are needed. The user-friendly BLE-based system and semi-automatic platform significantly enhance risk assessment efficiency across various workplace environments.

Screening of Highly Hazardous Pollutants in Groundwater of Beijing

Groundwater contaminants pose a great threat to water safety and human health. Therefore, in this study, the traditional hazard assessment method was improved and a comprehensive system covering hazard assessment, screening, and characterization by combining the toxicological priority index (Tox Pi) framework; absorption, distribution, metabolism, and excretory (ADME) analysis; and bipartite network analysis was constructed. Then, the system was applied to hazard assessment and toxic pollutants screening from the 234 hydrophobic organic contaminants (HOCs) identified in the groundwater of Beijing. First, the top 20 pollutants with hazard potential were screened out using the Tox Pi method. Subsequently, 17 high-priority HOCs were further identified based on the ADME property analysis. Then, the molecular targets of these 17 high-priority HOCs were characterized through systematic bipartite network analysis. Finally, ten HOCs with high hazard were screened through correlation and weighted average analysis, and it was revealed that their toxic effects were mainly concentrated in the endocrine-disrupting effect, carcinogenic effect, and genetic toxicity. This study provides technical support for the prevention of regional groundwater contaminants.

Developing CBTC system safety requirement hierarchy through STPA methodology

Safety-critical systems, such as the railway signal system, are subject to potentially high costs from failures, including loss of life and property damage. The use of new technology, including communication-based train control (CBTC) systems with software and computers, has changed the types of accidents that occur. Software-related issues and dysfunctional interactions between system components controlled by the software are increasingly the cause of incidents. Developing a “safe” safety-critical system requires accurate and complete safety requirements, which are the foundation of system development. Traditional hazard analysis techniques are insufficient for identifying the causes of accidents in modern railway signaling systems. Systems-Theoretic Process Analysis (STPA) is a powerful new hazard analysis method designed to address these limitations. Building upon this foundation, a hierarchical approach to safety requirement development has been further developed. This approach combines STPA analysis with a hierarchical modeling approach to establish traceability links from safety requirements to specific architectures, refine and allocate system-level safety requirements to relevant subsystems, and abstract safety requirements at higher hierarchical levels to enable easy changes to lower-level implementations. This paper employs the aforementioned methodology within the context of the CBTC system, thereby enhancing risk management and hazard analysis, enabling early insights, and facilitating the generation of safety requirements of CBTC System.

An integrated system theoretic process analysis with multilevel flow modeling for the identification of cyber‐physical hazards in a process industry

AbstractThe deep integration of information technology and process industry production systems makes system failure increasingly multi‐source and multi‐scale. In contrast to conventional hazard methods, system theoretic process analysis (STPA) can analyze the hazards in system control processes from the perspective of interactions among the system components. Theoretically, this method offers advantages that are better suited for modern production systems. However, as of now, the integration between STPA and process industrial production systems is still lacking. To address this issue, this study improved the original STPA method. First, we propose the “5 flows” concept for the process industrial cyber‐physical systems. The systems are described using multilevel flow modeling (MFM). This leads to the development of the MSTPA method, which is specifically designed to analyze the cyber‐physical hazards in process industrial production systems. Subsequently, the cyber‐physical hazards of a fluidized‐bed catalytic cracking unit are analyzed in detail using the MSTPA method as an example. The results show that MSTPA can identify cyber‐physical hazards in multiple dimensions. It is proved that, compared with the original STPA and traditional hazard methods, the MSTPA method can better identify cyber‐physical hazards in process industrial production systems.

A Better Understanding of Safety of Engineered Systems

Given the continued increase in scale and complexity of engineered systems, serious safety and risk management issues arise. There have been several catastrophic accidents, which are typically preceded by a number of seemingly unrelated occurrences that add up and cascade across subsystems. In the light of changing software and user interactions in engineered systems, traditional hazard analysis and risk assessment methodologies offer both benefits and drawbacks. Engineers working in contemporary businesses must be able to comprehend the features and characteristics that come from the interactions of components and subsystems as well as the risk assessment tools/approaches.Therefore, the goal of this paper is to increase awareness of the considerations for engineered systems and the risk assessment tools available for safety engineered systems. Specifically, this work focuses on the emergent properties of engineered systems, the various project phases, the available tools, their strengths and limitations and the codes/standards. A case study of the design and construction of a flash gas compression system is presented

Сучасні тренди розвитку загальноєвропейського ринку аграрного страхування: можливості та перспективи для України

Under martial law on the territory of Ukraine, insurance of agricultural products becomes particular relevance, since the danger of losing future crops is scaled not only due to the traditional hazards (agronomic, natural and climatic, financial and economic, etc.), but also due to the presence of wartime risks. The scientific novelty of the presented article lies in the substantiation of the expediency of further development of agrarian insurance in Ukraine, taking into account the global experience and European experience in particular. The article identifies the key problems that impede the functioning of the agrarian insurance market in Ukraine. Based on the results of the study, a comparative analysis of the existing models of functioning of agrarian insurance markets in the countries of the European Union is carried out, their advantages and disadvantages are substantiated. The importance of insurance for a sustainable development of agribusiness and ensuring the country’s food security is emphasized. Summarizing the current trends in the pan-European agrarian insurance market, the authors of the article emphasize the expediency of diversification of insurance protection of agricultural producers by expanding the range of insurance services (microinsurance, index and classic insurance). On the basis of a generalization, an analysis of the key parameters of the development of the agrarian insurance market in Ukraine for 2019–2022 is carried out, the authors’ proposals aimed at forming a model of public-private partnership are formulated, the expediency of strengthening social responsibility and increasing the stability of communication links between stakeholders of the agrarian insurance market, as well as ensuring comprehensive digitalization of the insurance process, is substantiated. The implementation of these measures is considered in the context of adaptation of the national agrarian insurance market to the pan-European insurance space.

The Cost of Imperfect Knowledge: How Epistemic Uncertainties Influence Flood Hazard Assessments

AbstractClassical approaches to flood hazard are obtained by the concatenation of a recurrence model for the events (i.e., an extreme river discharge) and an inundation model that propagates the discharge into a flood extent. The classical approach, however, uses “best‐fit” models that do not include uncertainty from incomplete knowledge or limited data availability. The inclusion of these, so called epistemic uncertainties, can significantly impact flood hazard estimates and the corresponding decision‐making process. We propose a simulation approach to robustly account for uncertainty in model's parameters, while developing a useful probabilistic output of flood hazard for further risk assessments via the Bayesian predictive posterior distribution of water depths. A Peaks‐Over‐Threshold Bayesian analysis is performed for future events simulation, and a pseudo‐likelihood probabilistic approach for the calibration of the inundation model is used to compute uncertain water depths. The annual probability averaged over all possible models’ parameters is used to develop hazard maps that account for epistemic uncertainties. Results are compared to traditional hazard maps, showing that not including epistemic uncertainties can underestimate the hazard and lead to non‐conservative designs, and that this trend increases with return period. Results also show that the influence of the uncertainty in the future occurrence of discharge events is predominant over the inundation simulator uncertainties for the case study.

A hazard analysis of heavy CNC machine tools based on fusion fault correlation

AbstractThis paper presents an analysis of the fault correlation between CNC machine tool subsystems using decision laboratory analysis and the House of Reliability (HoR) methodology. Initially, the maintenance information of the machine tool and other hazard indicators is comprehensively analyzed based on the cognitive best worst method (CBWM) to assign weights of hazard indicators. The HoR method is then employed to perform fault correlation fusion, which results in comprehensive hazard analysis results of the machine tool subsystems considering the fault correlation. Finally, the results obtained from the fusion fault correlation and the traditional hazard analysis are compared. The results indicate that the proposed method can highlight the relatively important subsystems and the most vulnerable parts of the machine tools. Overall, the hazard analysis results of this paper contribute to the safe and reliable operational and maintenance optimization of CNC machine tools.

Hazard Analysis of an Autonomous Container Handling System – a Comparison of STPA and HAZOP Methods

Increasing automation is a major trend in container terminals. In automated container handling systems, safety has been previously ensured by segregating the automated machinery from other traffic and workers moving on foot. Currently, further increases in flexibility are sought by developing autonomous systems that are capable of mixed-traffic operations without the need for separate operating areas. This increases the complexity of the systems and introduces new safety hazards. In addition to traditional hazard analysis methods, new approaches are needed to address the emergent risks related to autonomous operations. This paper studies the applicability of the STPA (system-theoretic process analysis) method in hazard analysis of an autonomous machine system. To support the evaluation, we define evaluation categories for comparison of the analysis methods. We also compare STPA with an established method, HAZOP (hazard and operability study). To perform the comparison, both STPA and HAZOP are applied to an autonomous container handling system concept. The study suggests that both STPA and HAZOP are well suited to support the development of autonomous machinery. However, we also highlight some notable differences in the methods, mostly related to the different underlying accident models that they utilise. HAZOP is an established method with tools and standards available. STPA, on the other hand, provides a well-defined syntax to ensure the analysis quality and a system modelling approach that supports the system development.

Practical Experience From Risks of Decommissioning of Petrochemical Facilities

Abstract Decommissioning is expensive and can be a complex operation involving a series of distinct phases, including cessation of operation, site preparation, decontamination, dismantling (demolition) and disposal. Each decommissioning phase has associated risks, which need to be identified, controlled, and minimized as far as reasonably practicable. A risk-based approach has been recognized, both for ensuring safety and reducing the total decommissioning period with cost savings. A traditional hazard and operability (HAZOP) study can be conveniently extended to decommissioning HAZOP, which is a guideword-based collective multidisciplinary study identifying types of risks associated with decommissioning and allocates actions to the contractor and specialists departments for implementation. A decommissioning HAZOP enables to address the hazards and risks of decommissioning activities holistically, addresses all major contingencies, and results in safe decommissioning within budget. The presented decommissioning HAZOP study itself was completed ahead of time, without accidents. While there are other methods, decommissioning HAZOP and risk assessment was recognized as one of the effective methods for achieving the safety and project cost objectives.

An Integrated Model for the Geohazard Accident Duration on a Regional Mountain Road Network Using Text Data

A mountainous road network with special geological and meteorological characteristics is extremely vulnerable to nonrecurring accidents, such as traffic crashes and geohazard breakdowns. Geohazard accidents significantly impact the operation of the road network. Timely and accurate prediction of how long geohazard accidents will last is of significant importance to regional traffic safety management and control schemes. However, none of the existing studies focus on the topic of predicting geohazard accident duration on regional large-scale road networks. To fill this gap, this paper proposes an approach integrated with the Kaplan–Meier (K-M) model and random survival forest (RSF) model for geohazard accident duration prediction based on text data collected from mountainous road networks in Yunnan, China. The results indicate that geohazard accidents in road networks have a strong aggregation in tectonically active, steep mountainous, and fragmented areas. Especially the time of the rainy season, and the morning peak, brings high incident occurrences. In addition, accident type, secondary accidents, impounded vehicles or personnel, morning rush hour, closed roads, and accident management level significantly affect the duration of road geohazards. The RSF model was 0.756 and 0.867 in terms of the C-index and the average area under the curve, respectively, outperforming the traditional hazard model (Cox proportional hazards regression) and other survival machine learning models (survival support vector machine). Without censored data, the mean absolute error and mean squared error of the RSF model were 11.32 and 346.99, respectively, which were higher than the machine learning models (random forest and extreme gradient boosting model).

Restricted mean survival time regression model with time-dependent covariates.

In clinical or epidemiological follow‐up studies, methods based on time scale indicators such as the restricted mean survival time (RMST) have been developed to some extent. Compared with traditional hazard rate indicator system methods, the RMST is easier to interpret and does not require the proportional hazard assumption. To date, regression models based on the RMST are indirect or direct models of the RMST and baseline covariates. However, time‐dependent covariates are becoming increasingly common in follow‐up studies. Based on the inverse probability of censoring weighting (IPCW) method, we developed a regression model of the RMST and time‐dependent covariates. Through Monte Carlo simulation, we verified the estimation performance of the regression parameters of the proposed model. Compared with the time‐dependent Cox model and the fixed (baseline) covariate RMST model, the time‐dependent RMST model has a better prediction ability. Finally, an example of heart transplantation was used to verify the above conclusions.

A systems-theoretic hazard analysis for safety-critical medical gas pipeline and oxygen supply systems

Medical gas systems are safety-critical systems due to their association with critical care situations. In particular, the oxygen gas supply system contains many complications represented in the interactions between human and equipment while operating the system and managing emergencies. Therefore, it contains many hazards that require high safety standards to maintain the integrity of the system. The traditional hazard analysis methods suffer from weaknesses as their linear reasoning assumption cannot adequately describe the actual behavior of modern socio-technical systems that are characterized by tight couplings and complex interactions among technical, human and organizational aspects. Alternatively, Systems Theoretical Process Analysis (STPA) is a new hazard analysis approach that accounts for the causal relationships between system components and their unsafe interactions, allowing the integration of both occupational and process safety. STPA is widely used in the automotive, aviation, and aerospace industries whereas there are a few applications of STPA in healthcare domain. This paper proposes the use of STPA methodology in analyzing the hazards related to the medical gas pipeline and oxygen supply systems in a low-medium income country. Specifically, the analysis considers the emergencies that stem from the total or partial failure of oxygen supply and the hazards related to temporary restoration of the medical oxygen system. The results indicate that STPA contributes to identifying the hazards resulting from the interference between the human, machines, and equipment, and studying the unsafe effect of the system elements on each other. This research suggests control measures to prevent the unsafe interaction of the system components and improve the response time to oxygen failure incidents, which greatly reduces the potential consequences.

Debris‐Flood Hazard Assessments in Steep Streams

AbstractDebris floods most commonly occur in steep mountain channels and on their alluvial fans but can also occur on small gravel bed rivers with watershed areas up to several hundred square kilometers. This became obvious during July 2021 and November 2021 debris floods in northwestern Germany and southwestern British Columbia, Canada. We subdivide debris floods into three categories: those triggered by a supra‐critical bed shear stress ratio, form by dilution from debris flows, and resulting from outbreak floods. This trichotomy challenges traditional hazard assessments; debris floods classify as a fluvial process, yet their destructive mechanics are difficult to characterize. Key hazards interact spatially and temporally in debris floods: inundation, scour, sediment transport and deposition and bank erosion. We describe approaches to quantify hazards by systematically accounting for these processes and introduce a novel approach for hazard quantification and mapping in which flow velocity, depth, and presumed fluid density are combined with the annual event frequency for all event scenarios. The derivative “composite hazard maps” are equally valid for debris floods and debris flows. Isolines of bank erosion based on a probabilistic analysis of a physically based model are added to capture the potential of debris floods to abruptly widen their channels. Substantial challenges remain, specifically in the reliable prediction of sediment transport and progressive bank erosion. Our intention is to homogenize debris‐flood hazard assessments and especially mapping methodologies. This could allow for systematic integration with landuse policies assuring consistency among approaches executed by practitioners acting in this field.

Process Hazard Analysis Based on Modeling and Simulation Tools

Chemical and oil processes are intrinsically sources of potential hazards. Although traditional qualitative hazard identification methods are simple, systematic, and flexible, such methodologies present limitations related to the inherent subjectivity, dependence on the team’s level of experience, and widespread time consumption of the members involved. In this context, the present work aims to develop a systematic way to use computational modeling and simulation tools for hazard identification. After extensive literature review, the present work proposes a methodology based on the association of the main points of previous works, with new contributions regarding the preparation for the simulations and the characterization of the minimum set of process variables that can enable appropriate interpretation of the results. The propene polymerization process (LIPP-SHAC process) was used as a case study to illustrate the proposed procedure. The paper explores how the model can be adapted for safety analyses and simulations for different hazard scenarios. The results obtained with different models are discussed and compared to those obtained with a traditional hazard identification approach to discuss how computational process modeling and simulation tools can sum to heuristic analysis. In conclusion, the use of simulations complementing the human-based approach can indeed enhance the understanding of mechanisms of hazardous scenarios, lessen conservative decision-making, and avoid overlooking device failures that can pose a severe hazard to the process.

Avoiding a crisis at Christmas: a systematic review of adverse health effects or ‘Chrishaps’ caused by traditional hazard sources and COVID‐19

ObjectiveTo complement the 2020 ANZJPH editorial “How COVID‐safe Santa can save Christmas”. In addition to a concise update regarding SARS‐CoV‐2/COVID‐19, we aimed to explore some risks of Christmas in terms of adverse health effects, which we call ‘Chrishaps’. Our overall study question was “which hazards have been scientifically associated with old Christmas essentials such as decoration, gifts, menus, and Santa himself, as well as new challenges associated with COVID‐19?” MethodWe searched the PubMed, Web of Science, and Open Grey databases systematically and Google unsystematically. ResultsThirty‐six pertinent articles – most of them case reports or retrospective analyses – documented Chrishaps. ConclusionOverall results suggested that Chrishaps come in different shapes and guises. Implications for public healthChrishaps pose a potential minor public health threat that should be borne in mind every festive season. Assessing and discussing specific public health implications of Chrishaps requires systematic risk research to be conducted.

In-situ biological effects, bioaccumulation, and multi-media distribution of organic contaminants in a shallow lake

Anthropogenic activity-impacted aquatic environment contains a complex mixture of contaminants, and ecological risk assessment solely based on chemical analysis is insufficient and biological assessment is required. However, traditional assessment heavily relies on laboratory bioassays, which may cause uncertainty due to inevitable laboratory-related artifact. A self-designed in-situ bioassay system was successfully applied to simultaneously evaluate water and sediment toxicity by co-exposure of two native species, Chinese rare minnows (Gobiocypris rarus) and Asian clams (Corbicula fluminea) in Tai Lake Basin, China. In-situ exposure caused pronouncedly lethal and sublethal effects (i.e., metabolic and oxidative stress, neurotoxicity, reproductive toxicity) on both fish and clams. Meanwhile, multi-media distribution of organic contaminants in water-sediment-biota system was analyzed. Besides hydrophobicity, metabolism was recognized as an influential factor on phase distribution of contaminants in water-fish and sediment-clam systems. Traditional hazard quotient (HQ) method based on environmental concentrations of 98 contaminants showed bias in risk assessment. Instead, a weight of evidence method by integrating three lines of evidence, including in-situ survival, enhanced integrated biomarker response values and environmental concentrations, successfully differentiate high- and moderate-risk sites in the shallow lakes. The present study incorporated in-situ bioassays into risk assessment using a weight of evidence approach, which reduced uncertainty in decision-making.

Comparison of the HAZOP, FMEA, FRAM, and STPA Methods for the Hazard Analysis of Automatic Emergency Brake Systems

Abstract As autonomous vehicle (AV) intelligence for controllability continues to develop, involving increasingly complex and interconnected systems, the maturity level of AV technology increasingly depends on the systems reliability level, also considering the interactions among them. Hazard analysis is typically used to identify potential system risks and avoid loss of AV system functionality. Conventional hazard analysis methods are commonly used for traditional standalone systems. New hazard analysis methods have been developed that may be more suitable for AV system-of-systems complexity. However, a comprehensive comparison of hazard analysis methods for AV systems is lacking. In this study, the traditional hazard analysis methods, hazard and operability (HAZOP) and failure mode and effects analysis (FMEA), as well as the most recent methods, like functional resonance analysis method (FRAM) and system-theoretic process analysis (STPA), are considered for implementation in the automatic emergency braking system. This system is designed to avoid collisions by utilizing the surrounding sensors to detect objects on the road, warning drivers with alerts about any collision risk, and actuating automatic partial/full braking through calculated adaptive braking deceleration. The objective of this work is to evaluate the methods with the unified theory of acceptance and use of technology (UTAUT) approach, in terms of their applicability to AV technologies. The advantages of HAZOP, FMEA, FRAM, and STPA, as well as the possibility of combining them to achieve systematic risk identification in practice, are discussed.

Improved Systemic Hazard Analysis Integrating With Systems Engineering Approach for Vehicle Autonomous Emergency Braking System

Abstract Safety analysis is a significant step for safety-critical system development. Compared with traditional vehicles, the system interactions for autonomous vehicles are more abundant and complex. Traditional hazard analysis methods, such as failure mode and effects analysis (FMEA) and fault tree analysis (FTA) which are based on the component failure and reliability theory, cannot identify the system hazards related to system interactions. An emerging hazard analysis method based on systems theory, systems theory process analysis (STPA) mainly focuses on identifying the control system hazards caused by system interactions. In this study, STPA method is used to identify the potential hazards and casual factors for autonomous emergency braking systems by concentrating on system interactions. To improve the consistency between system design and safety analysis, the workflow combining model-based systems engineering (MBSE) and STPA is proposed. The systems modeling language (SysML) is used to describe control structure and system interaction relationships. According to the identified casual factors, certain constraints and requirements can be derived, which can provide the guidance for system development with respect to system design. Furthermore, the quantitative analysis of certain unsafe control action is conducted by simulation, which shows effectiveness and feasibility of the proposed method in safety analysis and system design.

A New Semi-Quantitative Process Safety Assessment Method and Its Application for Fluorochemical Industry

Traditional hazard and operability analysis (HAZOP) is one of the most widely applied methods for process safety management in process enterprises. Due to its principles based on the conservative and qualitative judgment, it often leads to too conservative risk identification results for the fluorine chemical industry usually with high-risk processes to keep the continuity of production. Most of improved quantitative and semi-quantitative methods are based on the layer of protection analysis (LOPA) to resolve the over-conservative problem of traditional HAZOP with the database of LOPA. However, the improved model, taking LOPA as the main line and HAZOP only as the provider of scenarios and influencing factors, is limited to the fact that LOPA can only analyze complete and independent protection layers (IPLs). Therefore, in order to realize the quantitative or semi-quantitative analysis of disaster causes and consequences, a new semi-quantitative HAZOP method takes HAZOP as the main line to integrate LOPA, F&EI (fire and explosion index) for quantitatively calculating the reduction factors, probability on failure demand (PFD) of general protection layers (GPLs) and PFD of IPLs. With the case comparison of fluorine chemical industry, it is proved that this new method can effectively improve the problem that traditional HAZOP are too conservative in complex scenarios.