Efficient Safety Management Research Articles

A Study on Safety Management Efficiency for Coastal Accident Prevention

A Study on Safety Management Efficiency for Coastal Accident Prevention

Human factors and maintenance in delivery transportation: drivers' work outside the cab in focus

PurposeTo investigate safety at truck drivers' work outside the cab with a special focus on work environment and equipment maintenance to prevent occupational accidents.Design/methodology/approachTwo statistical databases on Finnish occupational accidents for truck drivers are analysed. Firstly, the national accident statistics database is examined to understand the broad context, and secondly a database on fatal accidents is analysed to better understand the root causes of the accidents and their relationship to human factors in maintenance. Based on the root cause analysis, four accident scenarios are created, and risk management measures are prioritized by occupational safety and health specialists (n = 7).FindingsThe study shows that there are a variety of accidents in truck drivers' work. Most of the accidents occur outside the cab while performing tasks other than driving. Further, in-depth analysis of the fatal accidents increases understanding of the possibilities of different risk management and maintenance actions in preventing such accidents.Research limitations/implicationsDatabases contain different limitations concerning the data.Practical implicationsTruck drivers' work environments are wide in nature. Efficient safety management requires broad participation from different stakeholders. In addition to safe work activities, work environment and equipment maintenance is highlighted as a key component for safe and fluent delivery transportation.Social implicationsRoad transportation forms a backbone of modern society. Accidents affect the efficiency of transportation and cause manifold costs reaching all the way to the societal level.Originality/valueThis study adds an important dimension of delivery transportation to a current scientific discussion on human factors and maintenance.

Applying beacon sensor alarm system for construction worker safety in workplace

The construction site is one of the most dangerous workplaces among all the industries, workers are exposed to various hazards sources. Ubiquitous accidents occur even with detailed regulations and laws. Situation awareness theory revealed that there are three processes when people are dealing with the changing environment: perception of environmental situation, comprehension of what people are dealing with and decision-making. The likelihood of risky behaviours increases a lot when any of these processes go wrong. In this paper, the author proposed an alarm system to help workers get a better perception of construction site and improve the efficiency and quality of safety management. In this system, a beacon sensor will be deployed on the hazard source and it will keep send Bluetooth package to receiver equipment. Workers will carry the receiver, a BLE sensor, to calculate the distance between people and the hazard point. If the distance is less than the setting number, the sensor will trigger the alarm to broadcast siren and send the unsafety behaviour event to manager backend to archive the entire process.

Analysis and Forecast of Mining Accidents in Pakistan

In the mining sector, the barrier to obtain an efficient safety management system is the unavailability of future information regarding the accidents. This paper aims to use the auto-regressive integrated moving average (ARIMA) model, for the first time, to evaluate the underlying causes that affect the safety management system corresponding to the number of accidents and fatalities in the surface and underground mining in Pakistan. The original application of the ARIMA model provides that how the number of accidents and fatalities is influenced by the implementation of various approaches to promote an effective safety management system. The ARIMA model requires the data series of the predicted elements with a random pattern over time and produce an equation. After the model identification, it may forecast the future pattern of the events based on its existing and future values. In this research work, the accident data for the period of 2006-2019-is collected from Inspectorate of Mines and Minerals (Pakistan), Mine Workers Federation, and newspapers in order to evaluate the long-term forecast. The results obtained reveal that ARIMA (2, 1, 0) is a suitable model for both the mining accidents and the workers’ fatalities. The number of accidents and fatalities are forecasted from 2020 to 2025. The results obtained suggest that the policy-makers should take a systematic consideration by evaluating the possible risks associated with an increased number of accidents and fatalities, and develop a safe and effective working platform.

Identifying hazardous road sections using a fuzzy expert system

To identify hazardous sections of newly built mountainous highways, decision-makers require assistance to determine the sections that may pose risks to road users, thereby enhancing the level of road safety management and capital utilisation efficiency. In this research, traffic accident economic losses were used as evaluation indices to characterise 30 horizontally curved sections of roadways. These highway sections were divided into five levels based on their evaluated level of risk. With the effects of multiple factors and the characteristics of uncertainty, mathematical statistics and fuzzy expert systems (FESs) were used to determine the factors contributing to hazardous sections of mountainous highways. The membership functions and fuzzy rule base were decided according to accident data and expert experience and a method for identifying hazardous sections based on the expert systems was established. The risk values of another 35 horizontally curved sections were obtained by this method and good results were achieved using the method to identify hazardous sections. The results showed that hazardous section classification is greatly affected by the horizontal radius, grade and declination angle of the horizontal curve. The results obtained from the FESs agreed overall with actual accident data.

Recognition of High-Risk Scenarios in Building Construction Based on Image Semantics

The action analysis and semantic interpretation of images have recently attracted increased attention in the field of computer vision. However, it is difficult for an intelligent monitoring method based on computer vision to understand complex scenarios and describe hazardous events from a surveillance video. To identify risks in a construction process and prevent construction accidents, an automatic identification method combining object detection and ontology is proposed. First, a faster region-convolutional neural network is used to extract low-level semantic information from scene elements and element spatial relationship attributes from images exported from a surveillance video. Second, an ontology semantic network is established within the scope of a construction scene, and logical language of the ontology is used to transform the low-level semantic information of images into high-level semantics of event descriptions. Third, construction risk rules are translated into ontology rules, and high-risk situations that may arise at the construction site are identified by a Pellet inference engine. Finally, a foundation pit excavation scene is taken as an example, and test results are used to verify the feasibility and effectiveness of the proposed method. The proposed method can be used to improve the efficiency of construction safety management.

Safety management efficiency of China’s coal enterprises and its influencing factors—Based on the DEA-Tobit two-stage model

In order to accurately analyze the safety management efficiency of China’s coal enterprises, based on the panel data of 14 coal listed enterprises in 2012–2018, this paper analyzes the overall technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of safety management of sample enterprises by the Data Envelopment Analysis (DEA) model, and builds Tobit model of random panel effect to evaluate the impact of business management and safety investment on safety management efficiency. The results show that: in 2012–2018, the average values of TE, PTE and SE of sample enterprises are respectively 0.674, 0.777 and 0.864; all have great room for improvement. The development of PTE and SE in most sample enterprises is unbalanced; TE of sample enterprises does not significantly improve, and shows a trend of rising-decreasing-rising; safety investment, enterprise scale and labor productivity are significantly positively related to safety management technical efficiency, while safety training person time and employees quality are negatively correlated. This paper identified the positive and negative effects of various influencing factors on the safety management efficiency of coal enterprises, and analyzed the main reasons that hinder the improvement of safety efficiency, and puts forward corresponding countermeasures and suggestions, which are helpful for coal enterprises to effectively improve their safety management efficiency and economic efficiency.

Constraints of coal mining safety management efficiency.

Investigation of the safety management efficiency in a coal mine aims to improve its safety management level thus ensuring coal mining safety. However, the safety management efficiency is affected by many factors especially for those coal mines operated underground. Furthermore, the constraint factors that are difficult to be identified and eliminated may impede safety management efficiency. This work aims to explore the constraints affecting safety management efficiency through a mathematical model accompanied by some effective measures guided by the theory of constraint (TOC). An index system for coal mining safety management efficiency (CMSME) is first established. Then a mathematical model roughly identifying the constraint factors is constructed. The principle of the proposed model is a comparison with the changes of the ratio of integrated CMSME and the ratio of each impact factor over a certain period. Thus, a constraint factor may be one whose ratio changes at a slower rate than that of the integrated CMSME. Following this, some measures are adopted to identify one, or more, real constraints. Finally, the constraints may be broken by internal, or external, means. A case study from Quandian coal mine verified the proposed method: the constraints affecting CMSME could be identified and broken through during the production. This research currently is applied to coal mining activities in a few coal mines, and it will be widely used in the future. This paper provides a novel method investigating the constraints affecting CMSME and breaking through them. The case study shows that breaking through constraints during the production is beneficial to CMSME. Furthermore, a coal mine with a high CMSME index may still, at some time, have one, or more, bottleneck constraints.

Predicting Hidden Danger Quantity in Coal Mines Based on Gray Neural Network

The hidden danger is the direct cause of coal mine accidents, and the number of hidden dangers in a certain area not only reflects the current safety situation, but also determines the development trend of safety production in this area to a large extent. By analyzing the formation and development law of the hidden dangers and hidden danger accident-induced mechanism in coal mines, it is concluded that there are some objective laws in the process of occurrence, development, weakening, and even stabilization of hidden dangers in a certain area. The development of the number of hidden dangers for a coal mine generally presents the law of similar normal distribution curve, with a certain degree of partial symmetry. Many years of hidden danger elimination in coal mines will accumulate large-scale hidden danger data. In this paper, by using the average value of hidden danger quantity in consecutive months to weaken the oscillation of hidden danger quantity sequence, and combining with gray model (1,1) and the neural network of extreme learning machine, and employing big data of hidden dangers available, a hidden danger quantity prediction model based on the gray neural network was established, and the experimental analysis and verification carried out. The results show that the model can achieve good prediction effect on the number of hidden dangers in a coal mine, which not only reflects the complex gray system behavior of hidden dangers of a coal mine, but also can predict dynamically. The safety management efficiency and emergency capacity of the coal mine enterprise will be greatly improved.

Management and economic efficiency criteria in the organization of safe rail transportation

Ensuring safety in rail transportation is achieved by creating a certain management structure of the company, which contributes to the improvement of economic sustainability and organization of safe traffic. The analysis of indicators to assess the state of traffic safety in JSC “Uzbekistan Temir Yullari” (the object of the study) allowed the authors to formulate the purpose of the study, which is to develop algorithms for carrying out measures to ensure traffic safety on the basis of economic criteria of management efficiency. Following stages of planning as the analysis of indicators of safety and identification of problems, analysis of causes of the identified problems, development of ideas objectives, setting measurable goals, checking the achievement of objectives, developing options for action achieve the goals. For each stage on the basis of methods of correlation, regression and factor analysis algorithms of their carrying out are developed. The concept of measures is developed to improve the economic efficiency of traffic safety management, depending on the method of management. With the functional approach, the main direction of the plan is to strengthen control, and with the process approach-the regulation of technological processes and training of production personnel. The authors believe that the implementation of the proposed recommendations for decision - making on traffic safety is a comprehensive preventive measure to ensure a guaranteed level of safety, which will improve the overall economic efficiency of traffic safety management in the railway company.

Ensuring the Economic Sustainability of the Railway National Company in a Globalizing World Economy

The railway industry of the Republic of Uzbekistan is currently an emerging market for transport services that integrates into the global economy, primarily in the Asian space. This is explained by the fact that the Republic of Uzbekistan occupies a strategic geographical position in Central Asia and is the center of the region’s geopolitical development, the main transit corridors connecting the North and South, East and West of the continent pass through the territory of the Republic of Uzbekistan [1]. When organizing both freight and passenger rail traffic, the issues of ensuring their safety should be considered taking into account the parameters of economic sustainability, which is still not given due attention. Based on the analysis of the indicators and the assessment of traffic safety in JSC “Uzbekistan Temir Yollari”, the authors identified such planning steps as analyzing traffic safety indicators and identifying problems, analyzing the causes of the problems identified, forming the idea of a goal, checking the achievement of a goal, development of options for activities to achieve goals. For each stage, based on the methods of correlation, regression and factor analysis, algorithms for their implementation have been developed. A concept of measures has been developed with the aim of increasing the economic efficiency of traffic safety management depending on the method of control. The authors believe that the implementation of the proposed recommendations for decision-making on road safety is a comprehensive preventive measure to ensure a guaranteed level of economic security in the developing market of Uzbekistan.

VR Panoramic Technology in Urban Rail Transit Vehicle Engineering Simulation System

Rail transit is a kind of rail transit based on fixed lines, which is carried out through special vehicles, passengers, and goods. However, urban rail transit construction activities are mostly underground activities, the construction environment and construction technology are complex, and the potential disaster risks are different. At present, the traditional 3D simulation technology is lack of interactive experience, but with the development of VR technology, 3D panorama technology, as a branch of VR technology, is rapidly popularized with its interactive and immersive characteristics. VR reality technology is applied in aerospace, real estate, education, entertainment, games, and other fields. Therefore, authors propose the application of VR panoramic technology based on the Unity3D engine and HTC Vive interactive equipment in the urban rail transit vehicle engineering simulation system. Furthermore, the content construction scheme and the overall development process of the simulation system are given. The function of VR technology in the simulation system and the main technology of real-time interaction for vehicle maintenance are discussed. The methods of literature analysis, expert interviews, on-site data acquisition, and questionnaire surveys are applied. By determining the intensity of protection measures, improving the construction quality of urban rail transit, preventing and controlling risks, and making the best plan and measures from a systematic point of view. From the final results of this study, user can gradually change the traditional ideas and methods of urban rail transit disaster prevention and mitigation and implement VR technology in the urban rail transit vehicle engineering simulation system, which plays a very important role in improving the safety management efficiency of urban rail transit construction.

Research on Informatization of Hidden Danger Investigation and Management in Modern Cigarette Factory

As an important part of the development strategy of cigarette enterprises, safety production management is an important guarantee to realize the operation target of cigarette factory and improve the economic benefit of enterprises, among which, hidden danger investigation and management are the most important means and methods. Especially when the industry is striving to achieve “Implementing the New Concept of Development, Go Up to a New Level of Cigarettes”, hidden danger investigation is not tolerated in the slightest carelessness. This paper expounds the improvement of enterprise safety management efficiency and the role of security hidden danger analysis and decision-making by realizing informatization of hidden danger investigation and management in cigarette enterprises. This paper also discusses the infrastructure of system construction, the principles and promotion strategy to be noted in the process of implementation.

Safety performance and technology heterogeneity in China’s provincial construction industry

The technology heterogeneity in the construction industry causes difficulties for an unbiased evaluation of safety performance. The non-parametric and two-hierarchy frontier data envelopment analysis (DEA) model was constructed according to the inputs and outputs of China’s provincial construction industry in 2017. Safety performance and its potential as well as undesirable output potential were analyzed from the aspect of technology gap and management efficiency. The results showed that the average safety performance in China's provincial construction industry was calculated to be 0.715, which was caused by technology gap and management efficiency. Northwest China has good performance in technology gap ratio and Central China performs well in management efficiency. Meanwhile, the strategies to improve safety performance in China's provincial construction industry were developed. In addition, potential of the safety technology gap and safety management efficiency took up 70.18% and 29.82% in terms of the undesirable output control. East, Central, South and Southwest China are the main areas needing to strengthen accident prevention practice. The findings can be used to help scholars understand the condition of safety performance in China's provincial construction industry, and provide guidelines to evaluate the performance in construction safety considering production technology heterogeneity.

Dynamic Analysis of Construction Safety Risk and Visual Tracking of Key Factors based on Behavior-based Safety and Building Information Modeling

Construction has long been seen as a high-risk industry. Many studies conduct risk management by controlling construction risk indicators, but few studies associate risk indicators with time and space to propose long-term risk management methods. Therefore, this study proposes a dynamic analysis and visual tracking method based on behavior-based safety (BBS). This study establishes a BBS observation checklist and records workers’ unsafe behavior. The risk level of unsafe behavior is then determined by grey clustering model. When a high risk occurs, an improved grey correlation model is used to track key indicators that affect risk. In order to achieve visual risk management, this study develops semantic logic to predefine the relationship between components and space. In schedule simulation of BIM, the key indicators of BBS are transformed into an executable visual inspection between work items, components, and space through ARC. This method makes it easier for construction managers to combine time and space to manage safety risk and to adopt appropriate strategies in a timely manner to improve the efficiency of safety management.

Research and Development of BIM Operation and Maintenance System in Nuclear Power Plant

The BIM (Building Information Modeling) operation and maintenance management system of the nuclear power plant has been developed to cope with the security risks in the operation and maintenance process of nuclear power plant, the difficulty in querying the operation and maintenance status, the low work efficiency and the difficulty in statistical analysis of various large-scale operation and maintenance data. Practice has shown that the BIM operation and maintenance management system enhances the safety of the plant; on the other hand, the convenience of the results information query improves the professionalization, refinement and systematization of the nuclear power plant safety and operation management; in that way, the safety management efficiency of nuclear power plants will be comprehensively improved.

Correlative Analysis of Occupational Health Management in Construction Companies to Related Factors Based on Fuzzy Clustering and Grey Theory

In recent years, China’s construction industry has developed rapidly and become a pillar industry of the national economy, with a large number of construction practitioners. Occupational health management in construction industry is becoming more and more important.By means of risk identification and factor correlation, this paper studies various factors affecting occupational health management in construction enterprises, and ranks the importance of these factors. This is conducive to the construction enterprises to clarify the important and secondary factors affecting occupational health management, know which aspects can effectively improve the level of occupational safety management, so as to take targeted measures to make up for the shortcomings, improve the efficiency of occupational safety management, and ensure the occupational health and safety of construction personnel.

An Analysis of Priority for Safety Management of Taekwondo Gym

The results of analysis of a superordinate concept and priority for safety management of taekwondo Gym are as follows. First, the superordinate concept for taekwondo Gym appeared as facility safety, safety training, vehicle safety and training safety, and in order of importance, appeared as safety training, facility safety, vehicle safety and training safety. Second, in the order of priority of safety training, Regular training for trainees, ranked highest, followed by provision of safety training for vehicle operation. Third, in order of facility safety, safe cushion attachment ranked highest, followed by tidiness and order of entrance and painting facility. Fourth, in the order of priority of vehicle safety, safety guidance for getting into and out of vehicles ranked highest, followed by proper service interval between vehicles. Fifth, in the order of priority of vehicle safety, wearing guards(head gear, body protection devices)during training ranked highest, followed by wearing guards(forearm protector, leg protector, feet top protector) during training. Based on these results, an efficient safety management of taekwondo Gym should be required in case of safety accidents without knowing where to happen and how to happen.

A Bayesian networks approach to build human-machine-ergonomic risk assessment model for construction workers

Effective safety management should pay much attention to harmony of human-machine ergonomic system. Bayesian Networks is a valuable tool to provide a robust probabilistic method of reasoning with uncertainty and is more suitable to represent complex dependencies among components and to include uncertainty in modeling. This paper build a BN risk model in order to analyze the extent to identify potential risk factors of human-machine-Ergonomic system, which can give reference to improve efficiency of safety management.

Assessment of gas and dust explosion in coal mines by means of fuzzy fault tree analysis

During the past decade, coal dust and gas explosions have been the most two serious types of disasters in China, threatening the lives of miners and causing significant losses in terms of national property. In this paper, an evaluation model of coal dust and gas explosions was constructed based on a fuzzy fault tree by taking the Xingli Coal Mine as a research site to identify the risk factors of coal dust and gas explosions. Furthermore, the hazards associated with such explosions were evaluated for this particular coal mine. After completing an on-site investigation, the fuzzy probabilities of basic events were obtained through expert scoring, and these expert opinions were then aggregated as trapezoidal fuzzy numbers to calculate the degrees of importance of all basic events. Finally, these degrees of importance were sorted. According to the resulting order, the basic events with higher probabilities were determined to identify key hazards in the daily safety management of this particular coal mine. Moreover, effective measures for preventing gas and coal dust explosions were derived. The fuzzy fault tree analysis method is of high significance in the analysis of accidental coal mine explosions and provides theoretical guidance for improving the efficiency of coal mine safety management in a scientific and feasible manner.