Industrial Safety Management Research Articles

The energy sector of the economy of the Arctic zone of the Russian Federation from the perspective of national security: legal aspects

Russia’s Arctic zone plays a key role in the development of energy resources on the world stage. At the same time, the development of the energy sector of the economy is associated with solving the tasks of the national security of the Russian Federation. The effective solution of these tasks is possible due to the more active use of the tools offered by the “green” economy and alternative energy, which requires a significant modification of legal regulation. However, at the moment, a complete replacement of the raw hydrocarbon sector in the world, according to researchers, seems impossible. Today, the main engine of the development of the Russian Arctic is precisely the raw energy sector, and the global economy is based mainly on energy, which is produced from mineral resources. The development of energy in the Arctic zone depends on the level of industrial safety. Industrial safety can be understood as the state of protection of personal interests (vital and property), as well as public interests (society and the state) due to the system of industrial safety management provided for by legislation. The industrial safety management system and the Institute of Civil Liability Insurance for owners of hazardous facilities is a comprehensive mechanism for preventing accidents and neutralizing their negative consequences at hazardous facilities, which is especially important for the Arctic zone of the Russian Federation. The main problems of the implementation of this mechanism and the ways to solve them are outlined.

CONDUCTING AN INDUSTRIAL SAFETY AUDIT AT OIL AND GAS FACILITIES

In modern conditions, it has become necessary to partially shift responsibilities for supervision and control of industrial safety without deterioration of quality from the state to business. Large-scale oil and gas companies have a great demand for an independent assessment of industrial safety at hazardous production facilities, due to a significant increase in financial costs for eliminating the consequences of accidents at hazardous production facilities of I and II hazard classes. The state is interested in controlling a new type of activity and expanding the regulatory framework for industrial safety. President of the Russian Federation Vladimir V. Putin signed Federal Law No. 637-FZ dated December 25, 2023, which amends the Federal Law «On Industrial Safety of Hazardous Production Facilities» and some other legislative acts. One of the key innovations is the introduction of the Institute for Audit of Industrial Safety Management Systems. This article analyzes the best existing practices of conducting industrial safety audits in large-scale oil and gas companies of the Russian Federation. Particular emphasis was placed on identifying the advantages and positive aspects of implementing such activities in organizations like Rosneft, Gazprom and Lukoil. The issues of assessing the compliance of hazardous production facilities in the oil and gas complex with the requirements of legislation in the field of industrial safety by conducting an industrial safety audit were raised. The purpose of the work is to develop a step-by-step algorithm for conducting an industrial safety audit for oil and gas facilities. The industrial safety audit algorithm includes four steps: preparation for the audit, documentary analysis, full-scale audit, and registration of the results. The result of an industrial safety audit is an audit report drawn up at the final meeting of auditors and customers, based on documentary and in-kind inspections. This document is necessary for the management of the enterprise and the supervisory authorities of the Russian Federation. Industrial safety audit provides a number of significant advantages that help organizations to identify deviations from mandatory requirements established in the field of industrial safety. This makes it possible to detect violations in a timely manner and promptly take the necessary corrective measures to eliminate the identified problems. As a result, effective audit contributes to improving the overall safety level at enterprises, preventing possible risks and reducing the possibility of emergencies.

Relationship network of safety management elements in the construction industry under the perspective of resilience

PurposeConstruction safety resilience is gradually gaining attention in the field of engineering construction as a new management concept and way to improve safety performance. However, how to cope with the dilemma of the unclear relationship of construction safety resilience elements at the practice level and promote the harmonization of construction safety goals and resilience enhancement paths has become an urgent challenge for safe construction.Design/methodology/approachThis study analyzes the components of construction safety resilience elements. A relationship network model of construction safety resilience elements is developed by using the social network analysis method. The location and influence of each element in the network and the interrelationships among the elements are explored in depth.FindingsThe findings reveal a robust interconnection among the elements of safety resilience in the construction industry. Key components such as safety behavior, risk prevention and control mechanisms, disaster prevention and mitigation technologies as well as information technology, are positioned at the core of the network. Notably, safety behavior exerts the most significant influence over the other elements, serving as the linchpin of safety management in the construction industry. Moreover, the interplay among safety resilience elements in the construction sector can alter the structure of the relationship network.Originality/valueThis study adopts the social network approach to solve the problem that it is difficult to quantitatively analyze the elements of construction safety resilience and their interrelationships and to clarify the interactions among the core elements, which can help to further assist the construction project manager to continuously optimize safety resilience and improve construction safety.

Numerical simulation and risk assessment of toluene tank leakage in petrochemical industries, China.

Large-capacity toluene storage tank leakage accidents can lead to severe casualties and environmental damage. In this study, numerical simulation of the toluene leakage accidents is performed using PHAST and ALOHA softwares across 16 scenarios. The present research focuses on the dispersion of toluene lethal and toxicity clouds, as well as the associated risks from vapor cloud explosions and pool fires resulting from the large-capacity toluene storage tank leakage. Meanwhile, the effects of influential factors such as leakage height, wind speed, ambient temperature, and atmospheric stability on toluene leakage accidents are also discussed, and then the worst-case scenario of the toluene leakage accident is obtained. The effects of wind speed, ambient temperature, leakage height, and atmospheric stability on outcomes such as toxic clouds, vapor dispersion, explosions, and pool fires are also analyzed. The result reveals that toxic cloud dispersion increases with ambient temperature, while the impact of vapor cloud explosions and pool fires decreases with the increase of leak heights. Wind speed significantly affects pool fire spread. The influential factors related to maximizing hazard range including low leak heights, low wind speeds, high temperatures, and stable conditions are obtained. Risk analysis indicates that vapor cloud explosions significantly impact outdoor potential loss of life (PLLoutdoor) compared with other incidents. Scenario 4 within a directional range from 33.8 to 56.3° shows the highest incident frequencies, highlighting its importance for risk monitoring. These findings are crucial for enhancing emergency response strategies and safety protocols in industrial safety management.

Investigation of Unsafe Construction Site Conditions Using Deep Learning Algorithms Using Unmanned Aerial Vehicles.

The rapid adoption of Unmanned Aerial Vehicles (UAVs) in the construction industry has revolutionized safety, surveying, quality monitoring, and maintenance assessment. UAVs are increasingly used to prevent accidents caused by falls from heights or being struck by falling objects by ensuring workers comply with safety protocols. This study focuses on leveraging UAV technology to enhance labor safety by monitoring the use of personal protective equipment, particularly helmets, among construction workers. The developed UAV system utilizes the tensorflow technique and an alert system to detect and identify workers not wearing helmets. Employing the high-precision, high-speed, and widely applicable Faster R-CNN method, the UAV can accurately detect construction workers with and without helmets in real-time across various site conditions. This proactive approach ensures immediate feedback and intervention, significantly reducing the risk of injuries and fatalities. Additionally, the implementation of UAVs minimizes the workload of site supervisors by automating safety inspections and monitoring, allowing for more efficient and continuous oversight. The experimental results indicate that the UAV system's high precision, recall, and processing capabilities make it a reliable and cost-effective solution for improving construction site safety. The precision, mAP, and FPS of the developed system with the R-CNN are 93.1%, 58.45%, and 27 FPS. This study demonstrates the potential of UAV technology to enhance safety compliance, protect workers, and improve the overall quality of safety management in the construction industry.

Enhancing Safety Management in the Ghanaian Construction Industry: Evaluating the Role of UAV Implementation and Construction Managers Understanding

The integration of unmanned aerial vehicles (UAVs) and other rising technologies has become paramount in construction safety monitoring and management. The study aimed to gain insight into the use of drones in construction safety practices and management in the Ghanaian construction industry. Through a literature review, five key domains (aerial surveillance and real-time monitoring, data analysis and risk assessment, emergency response and search-and-rescue operations, information management and visualisation, and safety training and education) were identified as the areas where UAVs or drones could enhance safety practices and management. The study included construction professionals who had a minimum of ten (10) years of experience in project management across different positions. A convenience sampling technique was used for the selection of participants from construction companies within the city of Accra. A structured questionnaire was designed and distributed to these professionals. The collected data was analysed using descriptive statistics and correlation analysis. The correlation analysis highlights the association among the variables used. The study underscores the pivotal role of UAVs in transforming safety practices and management. The diverse applications and potential benefits of UAV technology provide insights for policymakers, educators, and industry stakeholders to optimise safety management strategies and enhance efficiency on construction sites. In addition, the findings emphasise the importance of education and training initiatives to bridge the knowledge gap among construction professionals, thereby promoting a more sustainable and secure construction environment in Ghana.

An analysis of the relationship between project management and safety management in the Norwegian construction industry

The significance of general project management performance for safety performance in construction projects is studied in a sample of Norwegian construction projects. The data used are from a benchmarking tool for performance assessment and incident data from construction projects across the industry. Statistical analysis through independent-sample Mann–Whitney U-tests is performed to test for and identify significant relationships between project management, safety management and safety performance. The analysis confirms that good overall management of a construction project positively impacts safety management. The results advocate for applying safety management as an integral aspect of all management activities in a project rather than as a disconnected sub-system. The work is novel by empirically demonstrating the impact of project management aspects on safety management in construction projects.

A Hierarchical Matrix Factorization-Based Method for Intelligent Industrial Fault Diagnosis.

Data-driven fault diagnosis, identifying abnormality causes using collected industrial data, is one of the challenging tasks for intelligent industry safety management. It is worth noting that practical industrial data are usually related to a mixture of several physical attributes, such as the operating environment, product quality and working conditions. However, the traditional models may not be sufficient to leverage the coherent information for diagnostic performance enhancement, due to their shallow architecture. This paper presents a hierarchical matrix factorization (HMF) that relies on a succession of matrix factoring to find an efficient representation of industrial data for fault diagnosis. Specifically, HMF consecutively decomposes data into several hierarchies. The intermediate hierarchies play the role of analysis operators which automatically learn implicit characteristics of industrial data; the final hierarchy outputs high-level and discriminative features. Furthermore, HMF is also extended in a nonlinear manner by introducing activation functions, referred as NHMF, to deal with nonlinearities in practical industrial processes. The applications of HMF and NHMF to fault diagnosis are evaluated by the multiple-phase flow process. The experimental results show that our models achieve competitive performance against the considered shallow and deep models, consuming less computing time than deep models.

Dynamic risk assessment of natural gas transmission pipelines with LSTM networks and historical failure data

In the realm of energy infrastructure, ensuring the security of gas transmission pipelines is critical. This research introduces an advanced dynamic risk assessment framework that leverages the predictive capabilities of LSTM networks, presenting an improvement over conventional failure prediction models. Unlike traditional approaches that rely on averaging historical failure records, this framework dynamically processes historical pipeline failure incidents into sequential time series analysis, facilitating and improving the accuracy of the current failure rate. The model refines the failure rate estimation for individual pipelines by incorporating unique characteristics and modification factors, resulting in a highly precise failure likelihood estimation. Additionally, this study introduces a quantifiable linkage between mortality risk and the fatality probit value across various accident scenarios, enhancing consequence evaluation. A sensitivity analysis is then performed to assess the impact of various input parameters on the model's performance. The practical application of the model on a U.S. pipeline confirms its effectiveness. This proposed methodology substantially enhances the understanding of incident causation in gas pipeline systems, paving the way for superior safety management strategies. It is instrumental in enhancing pipeline safety, refining infrastructure planning, and optimizing safety resource allocation. The methodology offers benefits for pipeline operators, industry professionals, and regulatory agencies, contributing to improved operational safety and resource management in the pipeline industry.

Innovation using dynamic balanced scorecard design as an industrial safety management system in a company in the mining metallurgical sector

Over the years, industrial safety management in Peru's metallurgical mining sector has become a business problem with no acceptable solution. Annual statistics reveal an average of 60–70 fatal accidents in companies in this sector. This paper proposes using the Systemic Methodology to Develop and Maintain a Dynamic Balanced Scorecard MSDBSC-EM) to be used in the industrial safety management of the safety department of a Peruvian company in the metallurgical mining sector. This methodology was created at the Instituto Andino de Sistemas - IAS of Peru and combines the criteria of the Balanced Scorecard with the modeling of System Dynamics and contributions of the Soft System Methodology. This proposal demonstrates that dynamic simulation facilitates organizational learning and allows the designing of action plans in the present to manage the future. Also, modeling and computer tools facilitate the development and implementation of prototypes, which can be used to analyze required scenarios through pleasant and easy-to-use environments. In this sense, a dynamic model of key performance indicators of objectives, goals and initiatives was developed and four scenarios (A, B, C and D) were analyzed, from which it can be observed that the degree of commitment and leadership with the Industrial safety affects the increase in the level of preventive culture, which in turn favors the prevention of risks and the achievement of tangible objectives in industrial safety, evident in the drastic decrease in the occurrence of accidents and occupational diseases, and this is achieved to the extent that the personnel have the necessary competencies, which in turn is obtained through constant comprehensive training and the appropriate selection of personnel. On the other hand, the operating budget of the security department is a limiting factor in achieving these criteria. Another important aspect is the degree of existing communication, which affects the increase in the level of preventive culture.

A bibliometric analysis of quality and food safety management in the food development industry

Quality and food safety management (QFSM) presents significant concerns for developing countries worldwide. Researchers have not yet reached a consensus on the most complicated QFSM practices in the food industry. Our study aims to fill the research gap by visualising and analysing 537 articles on QFSM using Biblioshiny. Relevant publications from Dimensions, Scopus, and the Web of Science databases expose the current research status from 1982 to January 2024, without bias. We classified publications about Food Safety Management (FSM) and Food Quality Management (FQM) into four stages: the appearance stage (1982–1995), the stage towards increase (1996–2005), a rapid rise phase (2006–2014), and stable, rapid growth between 2015 and 2024. The review of QFSM recorded 5714 paper references and 1677 authors from 57 countries or regions. The most popular keywords are food quality, food industry, quality, and food safety management. China became the first in the group with 84 publications, while Belgium had the highest citations, with 738 total citations and 49.20 average article citations. The most productive institution is “Abu Dhabi Food Control Authority, Abu Dhabi, United Arab Emirates,” while Food Control is the most locally cited source. This study is the first to analyse QFSM resilience using biblioshiny. It is necessary to continue studying the strength of the food industry supply chain related to QFSM. The report identifies critical areas for improvement and future research to assist governments and businesses in developing adaptable food supply networks.

Improving the industrial safety management system at enterprises with chemically hazardous sites

This study focuses on developing an industrial and occupational safety management system for enterprises that contain chemically hazardous sites. The methodology, based on an expert approach, enabled the authors to design the structure of the risk management system at such enterprises. It also facilitated the identification of clusters and their descriptors, along with their roles in evaluating the state of the safety management system. The proposed methodology features a flexible and universal structure, making it applicable for assessing industrial and occupational safety across different enterprises, taking into account the specific technological aspects of production processes. In this case study, the authors examined the accident rates, injury hazards, and health risks associated with chemically hazardous sites in enterprises located in the Republic of Kazakhstan. The findings of this study provide a methodological approach that industrial enterprises can use to evaluate the effectiveness of their safety management systems. This allows for the development of measures aimed at preventing chemical accidents and reducing their impacts.

Safety management in the construction industry: Bibliometric analysis

Despite the continuous improvement of safety standards in the construction industry, this sphere remains one of the most hazardous sectors, and safety management is becoming a crucial determinant of effective operation at construction sites. The aim of this study is to identify the essential contextual, evolutionary-chronological, and geographical-industrial scientific landscape of the development of safety management in the construction industry through comprehensive bibliometric analysis. More than 15,000 articles indexed by Scopus from around the world from 2000 to 2023 were analyzed using the VOSviewer tool, filtered by keywords such as “construction,” “safety,” and “management.” The research revealed the intensification of publishing activity since 2012 (with peak growth in 2012, 2020, and 2022). The leading scientists are from China, the United States, and the United Kingdom (e.g., Chinese scientists make up 26.1% of all scholars). The majority of papers are in the field of engineering. Priority areas of research include safety climate, safety behavior, and building information modeling. The closest connections of construction safety management are with the study of professional risks, safety techniques, and quality control. The evolution of research focuses on “human health and safety-risks-digital security systems.” In general, the findings of this study provide a foundation for future research aimed at enhancing safety management in the construction field, potentially increasing worker protection and technical operational efficiency.

Computer Vision for Safety Management in the Steel Industry

Computer Vision for Safety Management in the Steel Industry

Innovations in safety management for construction sites: the role of deep learning and computer vision techniques

Purpose The purpose of this study is to investigate the potential of using computer vision and deep learning (DL) techniques for improving safety on construction sites. It provides an overview of the current state of research in the field of construction site safety (CSS) management using these technologies. Specifically, the study focuses on identifying hazards and monitoring the usage of personal protective equipment (PPE) on construction sites. The findings highlight the potential of computer vision and DL to enhance safety management in the construction industry. Design/methodology/approach The study involves a scientometric analysis of the current direction for using computer vision and DL for CSS management. The analysis reviews relevant studies, their methods, results and limitations, providing insights into the state of research in this area. Findings The study finds that computer vision and DL techniques can be effective for enhancing safety management in the construction industry. The potential of these technologies is specifically highlighted for identifying hazards and monitoring PPE usage on construction sites. The findings suggest that the use of these technologies can significantly reduce accidents and injuries on construction sites. Originality/value This study provides valuable insights into the potential of computer vision and DL techniques for improving safety management in the construction industry. The findings can help construction companies adopt innovative technologies to reduce the number of accidents and injuries on construction sites. The study also identifies areas for future research in this field, highlighting the need for further investigation into the use of these technologies for CSS management.

A mapping review of challenges in existing technology-based occupational safety training in the tourism and hospitality industry: Research potential in commercial kitchens

Introduction: An effective response to a safe and healthy work environment relies on advanced preparedness such as occupational safety training. The main objectives of this study are to describe and classify the most critical challenges and identify knowledge gaps in the literature that could inform future research. Methods: A systematic mapping review gathers information from six search engines; Francis and Taylor, Scopus, Science Direct, Emerald Insight, and SpringerLink, which yielded journal publications between 1948 and 2022. The data were analyzed using meta-analysis from 135,310 article search results, whereby 20 articles met the inclusion criteria. The studies varied in terms of aim, study design, and reporting detail. Results: The results showed that Canada and the United States are countries that study safety training in the tourism or hospitality industry, mainly in food management and food safety. The results also show that studies on occupational safety training in commercial kitchens are not common in the existing literature. The findings revealed that the highest number of articles involving safety training focused on food safety and food management in the tourism industry but less on kitchen workers' safety. Conclusions: This mapping review demonstrates hospitality workers' struggles, especially commercial kitchen workers. This review presents the types of technologies used for occupational safety training and provides an overview of different strategies that address the challenges. Among the most significant obstacles in occupational safety and health training are a lack of knowledge, high financial costs for implementation, and outdated policies from authorities.

Helmet Detection Based on Context Enhancement Pyramid Under Surveillance Images

Helmet detection is of great significance for realizing the automated management of industrial safety. To address the problem that existing object detection methods have insufficient ability to detect helmet small objects under surveillance images, this paper proposes a helmet detection based on context enhancement pyramid under surveillance images to realize the automatic detection task of helmet objects. The method helps the network improve position localization for small-scale helmet objects by adding a high-resolution detection layer to YOLOv5. Also, the proposed context enhancement pyramid reduces the semantic differences between different scale features and generates rich contextual features to enhance the network’s discriminative learning ability for helmet small object features. In addition, the proposed multi-scale attention module improves thefeature fusion effect in the pyramid network to further capture multi-scale features and expand the receptive field to enhance the network’s detection precision of helmet objects under surveillance images. The experimental analysis shows that the proposed method has good detection effect compared to existing object detection methods on the Safety Helmet Wearing Dataset (SHWD) as well as the customized dataset.

О проведении аудита системы управления промышленной безопасностью на примере ООО «Газпром трансгаз Томск»

The results of the audit of the industrial safety management system of Gazprom transgaz Tomsk, LLC, with the participation of the independent expert organization Scientific and Technical Center for Industrial Safety Problems Research, JSC, are provided. Notably, the audit of the industrial safety management system has been combined with the “classic” industrial safety audit. Brief information on Gazprom transgaz Tomsk, LLC, is provided, with the main focus on typical hazardous production facilities selected for the audit. The audit planning process, including the distribution of executives among the facilities to visit, in accordance with their geographic location, is described. The principles of establishment of criteria for the audit are listed. The parallel coordination of the jobs within the audit by the manager of the group of auditors and the representatives of the audit client is mentioned. A description of the stages of audit where the main attention has been paid to the industrial safety management system audit is provided. Notably, depending on the specifics of a visited department, the audit’s focuses change as well. The obtained results have been analyzed. The problem of currently missing requirements for the implementation, functioning, and evaluation of the efficiency of industrial safety management systems has been mentioned. The conclusion on the possibility and advisability of the industrial safety management system auditing combined with the control over the extent of compliance with the industrial safety requirements for hazardous production facilities as proof of the system's efficient functioning has been made. It is stated that such an experience can be used to develop regulatory and legal acts adopting the changes introduced in the Federal Law of July 21, 1997, № 116-FZ «On industrial safety of hazardous production facilities».

유통산업의 ESG경영을 위한 임파워링리더십, 안전문화, 안전행동, 조직신뢰관계 연구

ESG management, which considers non-financial elements of companies, is the current emphasis of corporate management. To sustain development in the shifting business landscape, the distribution industry is exploring digital transformation(DX) initiatives like AI and robotics. However, to ensure environmental, social, and governance(ESG) safety, industry-specific precautions must be taken. This study focused on the ESG safety management in the distribution industry. It aimed to identify the mechanisms of empowering leadership, safety culture, safety behavior, and organizational trust. The study also empirically confirmed that safety culture acts as a mediator between empowering leadership and safety behavior. Additionally, it found that organizational trust plays a moderating role between safety culture and safety behavior. In order to achieve this objective, a survey was performed online with a sample size of 400 workers in the distribution industry. Out of the 400 replies, 384 were considered reliable for analysis after eliminating 16 dishonest responses. The data was then analyzed using SPSS 25.0 Process Macro and AMOS 22.0 to check the link between the main variables and test the hypotheses. The study revealed that empowering leadership had a large and beneficial impact on safety behavior and safety culture. Furthermore, research has demonstrated that the implementation of empowered leadership has a positive impact on safety culture, hence strengthening and initiating safety-related actions among individuals. Furthermore, it was discovered that organizational trust acts as a moderating mediator between empowering leadership and safety behavior, specifically through safety culture. The study confirmed that as the level of organizational trust increases, the positive impact of empowering leadership on safety behavior is enhanced through the mediating role of safety culture. The given findings provide theoretical and practical recommendations for implementing ESG safety compliance response systems and safety processes in the distribution industry.

Fuzzy Logic-Based Decision-Making Method for Ultra-Large Ship Berthing Using Pilotage Data

As seafarers are involved in Maritime Autonomous Surface Ships (MASS), except for those in the fourth level of autonomy, the decision making of autonomous berthing should be carried out and be understood by human beings. This paper proposes a fuzzy logic-based human-like decision-making method for ultra-large ship berthing, which considers locations, ship particulars and the natural environment, and these factors are treated as the input variables. The IF–THEN rules are then established after the fuzzification of the input variables and are used for fuzzy inference to derive the decision of ship handling. It can be implemented in the decision-making system for safe navigation or be included in the process of autonomous berthing. The pilotage data are collected with nautical instruments and a distance measurement system during the berthing process, which are used to validate the proposed model and calculate the speed and turn errors. The overall and individual error of the decision-making model is in a reasonable and small range, which indicates that the model has good accuracy. The results of this research offer theoretical and practical insights into the development of a human-like decision-making method for autonomous navigation in port waters and maritime safety management in the shipping industry. The model can be further applied to develop a more widely applicable decision-making system for autonomous navigation in confined waters.