Search Results (144)

Fatal accidents in UK’s manufacturing sector are expected to remain the same or increase in coming years. This paper has tried to combat this issue by adapting and further developing a previously defined Safety Framework for the Paint Sector, to evaluate the safety performance of a metal manufacturing facility. To achieve this, the original Safety Framework was updated to align with the current British safety legislation outlined by the British Standards Institution. The framework was based on a three-level multi-attribute value theory (MAVT). Upon reviewing BSI 45001, the Safety Framework was founded upon the concept of Deming’s Plan, Do, Check, Act (PDCA) which is the foundation for the original framework, therefore, the first-level attributes remained consistent. The 13 attributes of the second level and 36 attributes of the third level were derived from the literature review and updated to relevant legislation. To develop the Safety Framework, the Delphi method was used. This included interviews that were conducted with employees and managers from either a Safety or Engineering background. The second part of the paper involved the improvement of the Safety Framework, based on the interview feedback. The main findings of the study revealed that the final Safety Framework has been deemed relevant for the Metal Manufacturing Sector by Industry Suitably Qualified and Experienced Personnel (SQEP). The majority of Interviewees deemed the Safety Framework to have a clear layout and easy to understand. The interviews and final Safety Framework suggested the importance of a company’s emphasis on employee welfare and health, in order to reduce accidents in the workplace. The originality of this paper lies in its application and validation of a sector-specific safety framework, contributing to the body of knowledge by offering a replicable methodology for adapting safety frameworks to other manufacturing sectors. Full article

Driver drowsiness is a major contributor to road accidents, often resulting from delayed reaction times and impaired cognitive performance. This study introduces EffRes-DrowsyNet, a hybrid deep learning model that integrates the architectural efficiencies of EfficientNetB0 with the deep representational capabilities of ResNet50. The model is designed to detect early signs of driver fatigue through advanced video-based analytics by leveraging both computational scalability and deep feature learning. Extensive experiments were conducted on three benchmark datasets—SUST-DDD, YawDD, and NTHU-DDD—to validate the model’s performance across a range of environmental and demographic variations. EffRes-DrowsyNet achieved 97.71% accuracy, 98.07% precision, and 97.33% recall on the SUST-DDD dataset. On the YawDD dataset, it sustained a high accuracy of 92.73%, while on the NTHU-DDD dataset, it reached 95.14% accuracy, 94.09% precision, and 95.39% recall. These results affirm the model’s superior generalization and classification performance in both controlled and real-world-like settings. The findings underscore the effectiveness of hybrid deep learning models in real-time, safety-critical applications, particularly for automotive driver monitoring systems. Furthermore, EffRes-DrowsyNet’s architecture provides a scalable and adaptable solution that could extend to other attention-critical domains such as industrial machinery operation, aviation, and public safety systems. Full article

This research critically examines the integration of the Seveso III Directive into spatial planning, with a focus on land-use policies in Greece, Cyprus, and Slovakia. It specifically focuses on Article 13, which aims to limit the impact of industrial accidents on human health and the environment through land-use and other relevant policies across four key dimensions: (a) land-use planning, (b) development control, (c) mitigation of existing Major Accident Hazards (MAHs), and (d) consultation procedures. The analysis includes the legal, administrative, and regulatory frameworks of each country, enriched with empirical data and case studies focusing on upper-tier oil and gas refineries. The findings reveal distinct procedural and decision-making approaches among the three countries, closely tied to their respective spatial planning systems and traditions. It also highlights weaknesses and best practices within these diverse planning systems, potentially informing initiatives aimed at establishing a more comprehensive institutional and operational framework for MAH protection. Full article

In response to global concerns about climate change and decarbonization across every sector, pressure has mounted on the maritime industry to reduce its environmental impacts, specifically its greenhouse gas (GHG) emissions, representing around 2.8% of the global total. As such, it prompts new alternative fuels that align with the International Maritime Organization (IMO)’s 2050 net-zero target. In recent years, several alternative fuels, such as hydrogen, ammonia, and methanol, have been proposed. However, alternative fuels face many challenges regarding cost, safety, and efficiency compared to traditional fossil fuels. Currently, methanol is considered one of the most promising alternatives since it is available, easy to store, and can take full advantage of existing infrastructure in situ. Moreover, methanol has a lower carbon intensity than conventional fossil fuels. However, its usage poses related risks of toxicity and flammability; thus, this area still needs in-depth research regarding hazard control. This study implements a systematic five-step methodology. Through a comprehensive literature review, the predominant hazards are delineated. To systematically analyze these risks, this study introduces a novel hazard-based coding system developed to categorize hazards into three classifications: toxicity, flammability, and explosivity. This system is specifically designed to analyze qualitative reports from thirty methanol accident investigations utilizing MAXQDA software. Subsequently, safety barriers related to methanol are identified, followed by a gap analysis to evaluate the effectiveness of existing safety measures. The findings indicate that physical hazards, including flammability and explosivity, represented the majority of identified risks. Furthermore, tank explosions emerged as a prominent sub-hazard, frequently linked to the highest number of reported fatalities. A gap analysis delineates the identified barriers related to Equipment and Personal Protective Equipment (PPE), Human Error Reduction, the Legal Framework, and First Aid, comparing them against the current measures outlined in IMO Circular 1621 and other legislative frameworks. Consequently, the analysis highlights critical gaps in technical guidelines and operational procedures related to methanol use. The study recommends the development of fuel-specific safety protocols, mandatory training for seafarers, and regulatory updates to address the unique hazards of methanol. These measures are necessary to create higher safety standards and make methanol a viable alternative fuel by ensuring its safe integration into the industry. Full article

This study analyzes the risks posed by high-temperature summer conditions to atmospheric storage tanks containing acrylic acid and proposes mitigation measures. Recent increases in heat waves and tropical nights have led to an increase in the temperatures of acrylic acid storage tanks. This temperature increase results in higher vapor pressure and promotes spontaneous polymerization, thereby increasing the risk of explosions in atmospheric storage tanks. Hazard and operability (HAZOP) analysis identified explosions due to pressure buildup as a major risk scenario. To mitigate this risk, a spray-tower system was introduced through a layer of protection analysis (LOPA), which effectively reduced the hazards associated with atmospheric storage tanks. Additionally, the removal of flame-arrester replacement operations not only achieves economic benefits, such as reduced replacement costs and labor time, but also enhances safety by eliminating worker exposure to hazardous chemicals. These findings have significant implications for improving safety at industrial sites and highlight the potential economic benefits of preventing chemical accidents. Full article

Nowadays, electric motors are an integral part of most modern electromechanical systems that are used in industry. It follows that industrial processes are becoming more dependent on their efficiency. If faults in electric motors are not rectified, they can lead to malfunctions and accidents, as well as production downtime. Symmetry of a three-phase system means that the voltage and current in the three phase conductors are equal to each other, with a period of 120°. Asymmetry occurs if one of these conditions or both conditions are violated at the same time. In most cases, asymmetry is caused by loads. Predictive diagnostics is the most effective way to identify motor faults while the motor is in operation and prevent the likelihood of failure. Predictive diagnostics can identify problems that could lead to major failures, thus reducing production downtime and maintenance costs. The paper discusses the control and diagnosis of electric motors using prediction techniques. In particular, the use of neural network models and predictive control to improve accuracy and reliability is investigated. The main objective of this research is to develop a neural network controller based on predictive model predictive control (MPC), which will improve the quality of the control and diagnostics system of electric motors, ensuring their stability and preventing possible malfunctions. Full article

Occupational health and safety (OHS) is a critical component of sustainable work practices, guaranteeing employee well-being in parallel with minimizing business operation threats. The integration of ethics in OHS practices, however, poses a major obstacle, given that most businesses prefer complying with regulations rather than adopting proactive, ethically directed risk avoidance. This study employs a systemic process in assessing business ethics integration in practices of OHS, emphasizing leadership, employee engagement, and precautionary safety. This quantitative survey research sought to gauge the utilization of OHS practices among firms in the construction industry. This study examined critical factors such as employee training, absenteeism patterns, wellness programs, and usage of safety practices. Our study outcomes identify a reduction in accidents in workplaces, lower absenteeism, and improved monitoring of employee well-being when a blend of systemic safety programs and ethically directed strategies is utilized. This study emphasizes the imperative of a proactive, ethically comprehensive strategy in practices of OHS, which calls for improved leadership, constant safety learning, and enhanced wellness programs. The findings contribute to the development of sustainable risk management frameworks, offering practical insights for businesses, policymakers, and industry stakeholders to improve workplace safety culture. Full article

Remotely piloted aircraft are a fast-emerging sector of the aviation industry. Although technical failures have been the largest cause of accident occurrences for Remotely Piloted Aircraft Systems (RPASs), if they are to follow the path of conventionally crewed aviation, Human Factors (HFs) will increasingly contribute to accidents as the technology of RPASs improves. Examining an RPAS accident database from 2008–2019 for HF-caused accidents and coding to the Human Factors Analysis and Classification System (HFACS) taxonomy, an exploration of RPAS HFs is carried out and the predominant HF issues for RPAS pilots identified. The majority of HF accidents were coded to the Unsafe Acts level of the HFCAS. Skill errors, depth perception and environmental issues were the largest contributors to HF RPAS safety occurrences. A comparison with other sectors of aviation is also made where perception issues were found to be a greater contributor to occurrences for RPAS pilots than for other sectors of aviation. Developing appropriate training programs to develop skilled RPAS operators with good depth perception can contribute to a reduction in RPAS accident rates. The importance of reporting RPAS incidents is also discussed. Full article

Chemical plants inherently handle and operate with a wide range of hazardous materials, making them more prone to accidents compared to other industrial sectors. Consequently, safety management in chemical plants tends to be systematically organized based on elements of process safety management (PSM) systems. In June 2023, South Korea’s Ministry of Employment and Labor released the Serious Injury and Fatality (SIF) report, which summarized 4432 major accident cases that occurred over six years (2016–2021), including 1834 cases in manufacturing and related industries and 2574 cases in construction. The report provided an overview of these accidents, their causes, and measures to prevent their recurrence, with a focus on fatalities and severe injuries associated with critical losses across different industries. This study examined 16 accident cases that occurred at PSM-regulated facilities, which are managed on the basis of a systematic safety framework established by regulatory requirements. Among these, particular attention was paid to an explosion accident in the organic catalyst packaging process at a facility with no prior accident history and exhibiting unique accident characteristics. A systemic root cause analysis was conducted using the barrier-based systemic cause analysis technique (BSCAT) and the system theoretic accident model and process (STAMP-CAST) methodologies. The systemic analysis highlighted the critical importance of clearly identifying materials or factors that may inadvertently mix during the process design or mass production phases and evaluating whether such interactions could lead to accidents during the hazard assessment stage. Beyond incorporating the risk mitigation measures identified in the process design and procedural development phases without omissions, it is essential to periodically conduct “worker-centered risk assessments”. These assessments help evaluate the potential for accidents resulting from human errors, such as workers’ non-compliance with established procedures, which is a key aspect of preventing chemical accidents. Although this study did not include an evaluation of the impacts of high pressures or high temperatures on workers near chemical accident sites—hence, no specific recommendations regarding safe working distances are made—the findings are expected to contribute to the development of preventive measures for chemical accidents in smaller-scale plants where workers directly manage and operate processes. Full article

This study determined the environmental condition of the benthos of Milford Haven Waterway, an area that is arguably the most vulnerable in the UK to anthropogenic activities, including the potential effects of a major oil spill in 1996, using historical data on the macrobenthos more than a decade later in 2008, 2010 and 2013. These data show a gradual decline in numerous univariate diversity measures from the outer (marine) to inner (estuarine) stations. Taxonomic distinctness generally falls within the expected range, and most stations have above-average values compared with other monitoring stations around the UK. The W-statistics for Abundance/Biomass Comparison (ABC) plots are usually strongly positive and never negative. There was a sequential change in community composition from the outer to inner stations, which was strongly related to salinity, and, to a lesser extent, sediment granulometry. None of the species regarded as indicators of organic pollution were prominent in the macrobenthic community of Milford Haven Waterway. On this basis, although there are some slight indications of environmental perturbation at particular sites in certain years, it can be concluded that the benthic communities of Milford Haven Waterway are in a healthy state. This study provides a baseline against which the potential effects of any future environmental accidents and/or the increased industrial development can be assessed. Full article

With the rapid advancement of modern industries, pressure vessels and piping have become increasingly integral to sectors such as energy, petrochemicals, and process industries. To grasp the research and application status in the field of pressure vessel and piping safety, 670 publications in the Web of Science core database from 2008 to 2024 were taken as data samples in this paper. The knowledge mapping tools were used to carry out co-occurrence analysis, keyword burst detection, and co-citation analysis. The results show that the research in this field presents a multidisciplinary and cross-disciplinary state, involving multiple disciplines such as Nuclear Science and Technology, Engineering Mechanics, and Energy and Fuels. The “International Journal of Hydrogen Energy”, “International Journal of Pressure Vessels and Piping”, and “Nuclear Engineering and Design” are the primary publication outlets in this domain. The study identifies three major research hotspots: (1) the safety performance of pressure vessels and piping, (2) structural integrity, failure mechanisms, and stress analysis, and (3) numerical simulation and thermal–hydraulic analysis under various operating conditions. The current challenges can be summarized into three aspects: (1) addressing the safety risks brought by new technologies and materials, (2) promoting innovation and the application of detection and monitoring technologies, and (3) strengthening the building capacity for accident prevention and emergency management. Specific to China, the current challenges include the safety and management of aging equipment, the effective detection of circumferential weld cracks, the refinement of risk assessment models, and the advancement of smart technology applications. These findings offer valuable insights for advancing safety practices and guiding future research in this multidisciplinary field. Full article

The construction industry’s poor safety is a global issue, with construction workers’ unsafe behaviors (CWUBs) identified as a major cause of accidents. Based on social cognitive theory (SCT) and using multiple regression analysis, this study categorizes accident experience (AE) into direct and indirect types, examining how each affects CWUBs and the roles of risk perception (RP), safety attitude (SA), and safety competence (SC) in these relationships. Utilizing a structured questionnaire completed by 334 valid respondents and analyzed through structural equation modeling (SEM), the study found that indirect experience (IE) significantly reduced CWUBs, with a standardized path coefficient of −0.364, while direct experience (DE) has a smaller impact, with a standardized path coefficient of −0.154, but a significant p. Furthermore, IE positively influenced RP, SA, and SC, explaining 66.8% of its total effect. This study offers a new framework for understanding how AE influences CWUBs, providing actionable insights for managers to implement effective strategies that reduce CWUBs on construction sites. Full article

The demand for the use of secondary batteries is increasing rapidly worldwide in order to solve global warming and achieve carbon neutrality. Major minerals used to produce cathode materials, which are key raw materials for secondary batteries, are treated as conflict minerals due to their limited reserves, and accordingly, research on the battery recycling industry is urgent for the sustainable secondary battery industry. There is a significant risk of accidents because there is a lack of prior research data on the battery recycling process and various chemicals are used in the entire recycling process. Therefore, for the safety management of related industries, it is necessary to clearly grasp the battery recycling process and to estimate the risk accordingly. In this study, the process was generalized using the information on the battery recycling process suggested in the preceding literature. And to estimate the relative risk of each battery recycling process, the RAC (Risk Assessment Code) matrix described in the US Department of Defense’s “MIL-STD-882E” was used. Severity was derived by using “NFPA 704”, and probability was derived by combining generalized event analysis for each process and the WEEE (Waste Electrical and Electronic Equipment) report. The results confirmed that the process using H₂SO₄ had the highest risk when extracting Li during the leaching process, and that dismantling and heat treatment had the lowest risk. Using the probability factor for each process calculated through the research, it is expected to be used in future battery recycling process research as basic data for quantitative risk assessment of the battery recycling process. Full article

Lake Maurepas, Louisiana, holds ecological, recreational, and economic significance, but recent concerns have arisen over its water quality due to industrial activities. From June to November 2023, we investigated water and sediment quality at nine sites and three depths. Results showed that NH₃-N levels were within safety limits (0.11 ± 0.10 mg/L), while Total Nitrogen (TN, 0.83 ± 0.65 mg/L), Total Phosphorus (TP, 0.32 ± 0.13 mg/L), Chemical Oxygen Demand (COD, 25.94 ± 11.37 mg/L), Arsenic (As, 0.26 ± 0.17 mg/L), and Lead (Pb, 0.23 ± 0.002 mg/L) exceeded acceptable thresholds. Spatial-temporal analysis revealed significant variations across sites, depths, and sampling dates. Major contaminant sources included discharges from the Tickfaw, Amite, and Blind rivers, as well as a vehicle accident on Pass Manchac. Seismic and drilling activities by Air Products and Chemicals had little to no observed impact. Four AI algorithms were also evaluated using different physical parameter inputs to predict December’s chemical pollutant levels, which were missing due to adverse weather. The LSTM model outperformed the others, achieving R² values of 0.852 for COD, 0.869 for TN, 0.842 for As, and 0.921 for TP and Pb. Predictions indicated decreasing pollutant levels in December, which matched salinity and specific conductance measurements, and reverted to those observed in September and October. This pattern is attributed to the settling of contaminants from the Pass Manchac accident and ongoing pollutant sources from September and October. Full article

The increase in energy demand due to industrial development and urbanization has resulted in the development of large-scale energy facilities. Republic of Korea’s petrochemical industrial complexes serve as prime examples of this phenomenon. However, because of complex processes and aging facilities, many of which have been in operation for over a decade, these industrial complexes are prone to process-deviation-related accidents. Chemical accidents in energy facilities involving high-pressure liquids or gases are especially dangerous; therefore, proactive accident prevention is critical. This study is also relevant to corporate environment, social, and governance (ESG) management. Preventing chemical accidents to protect workers from injury is critical for business and preventing damage to surrounding areas from chemical accidents is a key component of ESG safety. In this study, we collected accident data, specifically injury-related incidents, from Republic of Korea’s petrochemical industrial complexes, which are the foundation of the energy industry. We analyzed the causes of accidents in a step-by-step manner. Furthermore, we conducted a risk analysis by categorizing accident data based on the level of risk associated with each analysis result; we identified the main causes of accidents and “high-risk process stages” that posed significant risk. The analysis reveals that the majority of accidents occur during general operations (50%, 167 cases) and process operations (39%, 128 cases). In terms of incident types, fire/explosion incidents accounted for the highest proportion (43%, 144 cases), followed by leakage incidents (24%, 78 cases). Furthermore, we propose a disaster safety artificial intelligence (AI) model to prevent major and fatal accidents during these high-risk process stages. A detailed analysis reveals that human factors such as accumulated worker fatigue, insufficient safety training, and non-compliance with operational procedures can significantly increase the likelihood of accidents in petrochemical facilities. This finding emphasizes the importance of introducing measurement sensors and AI convergence technologies to help humans predict and detect any issues. Therefore, we selected representative accident cases for implementing our disaster safety model. Full article