Journal of Health and Safety at Work

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Introduction: Microperforated panels (MPPs), often considered as potential replacements for fiber absorbers, have a significant limitation in their absorption bandwidth, particularly around the natural frequency. This study aims to address this challenge by focusing on the optimization and modeling of sound absorption in a manufactured MPP.
Material and Methods: The study employed Response Surface Methodology (RSM) with a Central Composite Design (CCD) approach using Design Expert software to determine the average normal absorption coefficient within the frequency range of 125 to 2500 Hz. Numerical simulations using the Finite Element Method (FEM) were conducted to validate the RSM findings. An MPP absorber was then designed, manufactured, and evaluated for its normal absorption coefficient using an impedance tube. Additionally, a theoretical Equivalent Circuit Model (ECM) was utilized to predict the normal absorption coefficient for the manufactured MPP.
Results: The optimization process revealed that setting the hole diameter to 0.3 mm, the percentage of perforation to 2.5%, and the air cavity depth behind the panel to 25 mm resulted in maximum absorption within the specified frequency range. Under these optimized conditions, the average absorption coefficient closely aligned with the predictions generated by RSM across numerical, theoretical, and laboratory assessments, demonstrating a 13.8% improvement compared to non-optimized MPPs.
Conclusion: This study demonstrates the effectiveness of using RSM to optimize the parameters affecting MPP performance. The substantial correlation between the FEM numerical model, ECM theory model, and impedance tube results positions these models as both cost-effective and reliable alternatives to conventional laboratory methods. The consistency of these models with the experimental outcomes validates their potential for practical applications.

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Introduction: The safety harness is a critical device for preventing falls from height, particularly in the construction industry. This study aimed to identify the factors contributing to the non-use of safety harnesses during work at height and to evaluate the comfort, satisfaction, and usability of these harnesses among construction workers in Tehran using a custom-designed tool.
Material and Methods: A semi-structured interview was conducted with construction workers to identify the factors influencing the non-use of safety harnesses. The collected data were analyzed using MAXQDA 10 software. Based on the results, which revealed dissatisfaction with the current safety harnesses, the levels of comfort, satisfaction, and usability were assessed using the Safety Harness Usability and Comfort Assessment Tool (SHUCAT) questionnaire.
Results: The reasons for not using safety harnesses were categorized into four main groups: management factors, worker attitudes, comfort, and harness design. These were further subdivided into 27 subgroups. The average satisfaction and comfort scores for safety harnesses were 26.8 ± 6.25, indicating that workers generally felt uncomfortable and dissatisfied with their harnesses. The average usability score was 38.70 ± 5.60, reflecting poor usability of the harnesses.
Conclusion: Improving the safety harness design could enhance workers’ comfort and satisfaction, increasing their willingness to use the equipment. Incorporating feedback from users and experts into the design process can help address the identified shortcomings and result in better product development.

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Introduction: Identifying and modeling the root causes of accidents can play an important role in preventing them. The purpose of this study is to identify and model the causes of gas pipeline excavation and piping operation accidents using the Bayesian network (BN) and fuzzy DEMATEL.
Material and Methods: In this study, industrial accidents during gas pipeline excavation and piping operations were analyzed using the Bowtie method. The fuzzy DEMATEL method was employed to determine relationships between accident root causes, and the fuzzy AHP method was used to compare pairs of causes and determine their weight. Finally, Bowtie and DEMATEL outputs were mapped in Bayesian networks to determine the important risk factors for accidents.
Results: The most important risk factors for trench collapse accidents were as follows: risk management (16% impact weight), competency assessment (14.2% impact weight), supervision (13.8% impact weight), work permit system (13.7% impact weight), compliance with requirements and guidelines (13.4% impact weight), training (11.4% impact weight), HSE system (9.5% impact weight), and contractor management (8% impact weight).
Conclusion: Based on the results, it was demonstrated that risk management and competency assessment, having the highest weight percentages, play the most significant roles in the occurrence of trench collapse accidents. The findings of this study can inform the prioritization of corrective measures to prevent trench collapse accidents in gas pipeline excavation and piping operations.

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Introduction: Barriers play a critical role in mitigating risks and preventing catastrophic incidents in process industries. Human and Organizational Factors (HOFs) significantly influence the performance of safety barriers. This systematic review investigates existing frameworks and methods for assessing the impact of HOFs on safety barrier performance.
Material and Methods: A systematic search was conducted across the Scopus and Web of Science databases, following the PRISMA guidelines. The search aimed to identify studies presenting methodologies for evaluating the influence of HOFs on safety barrier performance in process industries. Data were subsequently extracted from the 16 included studies.
Results: The 16 studies included in this research presented various methods and frameworks examining the impact of HOFs on different types of safety barriers, including technical, operational, and human barriers, across industries such as oil and gas, chemical, and steel. Barrier and Operational Risk Analysis (BORA) emerged as the predominant framework among the studies. Research on operational and human barriers, which depend on human actions and procedures, frequently identified factors such as competence, training, communication, and supervision as key influencers of performance. In contrast, studies on technical barriers highlighted the importance of assessing factors such as maintenance management and procedural compliance.
Conclusion: This research highlights the critical role of HOFs in safety barrier performance within process industries. By systematically reviewing existing methodologies, the study identified their strengths and weaknesses. Findings underscore the need to account for uncertainties in expert judgments and the interplay between HOFs in evaluation models. The integration of fuzzy logic and Bayesian networks is proposed to enhance evaluation processes. Future research should prioritize the development of unified frameworks that address the limitations of current approaches while expanding their applicability across diverse industries.