Kim, Hyunsoo;Lee, Yong-Soo;Oh, Inhwan;Ahn, Hongseob
Journal of the Korea Institute of Construction Safety
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v.2
no.1
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pp.9-15
/
2019
Despite the efforts for enhancing the safety record, construction industry has been suffered from higher fatalities than other industries. The poor record of safety in construction industry means that there is a clear need for an effective countermeasure. As mentioned in previous studies, it is important to identify the type of activities or risks that are likely to cause accidents and to develop appropriate safety measures. Considering the large number of accident cases on the temporary installations including work platforms and work passages, the temporary installations should be managed first. To support it, this study aims to analyze falling accident cases on construction working platforms and passages which can lead to develop proper safety measures. Through the analysis of 1663 accident cases in the perspective of cost, progress, activity, and type of workers, this study identifies how the recent accidents occur and what is the cause of the accident occurrence. The identified causes of accident occurrence will help us to improve current construction safety.
Khan, Numan;Kim, Youjin;Lee, Doyeop;Tran, Si Van-Tien;Park, Chansik
International conference on construction engineering and project management
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2020.12a
/
pp.87-95
/
2020
Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.
Yoo-Won Lee;Kyung-Jin Ryu;Su-Hyung Kim;Hyungju Kim;Kwi Yeon Koo;Chaegil Lee;Seonghun Kim
Fisheries and Aquatic Sciences
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v.27
no.1
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pp.7-16
/
2024
Fishing is considered one of the most dangerous industries alongside mining that needs further efforts to improve safety. In this study, we have investigated safety management of the gillnet fishing industry in South Korea through identifying safety level and classifying common accident types from the statements of accident com-pensation insurance payments for the last 5 years (2016-2020). There were in total 3,895 accidents and 159 fatalities with an average accident frequency of 5.34 × 10-2 per year per fisher and an average fatality of 2.18 × 10-3 fishers per year. We have also identified that 62.4% of the accidents occurred during Fishing (FS), and the most common and the most severe accident type is Slips and Trips (ST) and Other (OT) marine accidents such as collision and capsizing, respectively. The hand was most frequently injured. Finally, the risk assessment indicated that most of the accident types of gillnet fishing in South Korea have unacceptable levels of risks, and it is urgent to implement improved safety measures to reduce accidents during gillnet fishing operation. The findings of this study are expected to provide valuable data to create a safer working environment for fishers working on gillnet fishing vessels.
According to the statistics, occupational fatal injuries by the fork lifts were about 30 per year in whole industrial. Fork lifts are widely used in various parts of industries to improve the efficiency of the work. In this study, the current regulations to be adequate in industrial site have to be renew in order to prevent the fatal injuries by the fork lifts. Fatal injury analysis were conducted with several accident cases by the fork lifts. For each accident, the causes of the injuries were examined and proper safety measures were proposed. In this study, the fork lift showed a high fatality rate in industrial accidents and no detailed cause analysis of fatal accidents was conducted in terms of unsafe acts or conditions. First, fork lifts were the highest of the machines caused the accidents. In order to prevent fatal injuries by the fork lifts, the tarket was manufacturing industry. Second, the order of the cause of cognitive engineering agenda in the manufacture industrial was visibility, responsibility and affordance, and revision of acts was proposed. Third, there was not a lots of different points of human error between occurrence types and business sizes. Forth, number of fatalities by the attacker was more than by the inducer.
Objective: This study aims to investigate the effects of organizational support, risk perception and job satisfaction on safety consciousness in confined space works. Background: Confined space works are rated as hazardous works with high injury frequency and fatalities. But there were few researches for the occupational injury of the confined space workers. Method: Questionnaire survey targeting 236 workers working in confined spaces were carried out to construct the structural equation model on safety consciousness. The participants were all male workers, and they install and maintain or clean facilities mainly in the confined spaces. Results: A structural equation model for safety consciousness was proposed, and validated based on perceived organizational support, risk perception and job satisfaction factors. Perceived 'organizational support' contributed significantly to 'worker's safety consciousness' both directly and indirectly. Also, perceived 'worker's safety consciousness' was also affected by perceived 'job satisfaction' and 'risk perception'. In terms of magnitude of relationships, the direct effect of perceived 'job satisfaction' on 'worker's safety consciousness' was the greatest among the interrelationships among latent factors. Conclusion: Workers' safety consciousness can function as a leading indicator for safety and hazard prevention of workers. Application: The results can be used in developing safety prevention programs for confined space workers.
Since cranes are a kind of complex human-machine systems, it is almost impossible to completely secure safety with current technologies. Therefore, managerial interventions to prevent human errors are needed for safely operating a crane. The Occupational Safety and Health law states that cabin-type crane operators should have crane drivers' licence and crane-related operators (e.g., pendent-type crane operators, slinging workers) should take a special safety training. However, statistics on industrial accidents showed that fatalities due to crane accidents (185 accidents occurred during 2013~2017) were the highest among hazardous machinery and equipment. To effectively control the crane-related accidents, voices of crane workers need to be analyzed to investigate the current status. This study surveyed perceived causes of crane accidents and status of special safety training for crane workers of 387. The survey revealed that 24.3% of the respondents experienced crane accidents and 31.4% eye-witnessed crane accidents. 79% of the respondents pointed human errors such as improper crane operation and improper slinging as the first cause. Lastly, only 16.7% of the respondents took a professional special safety training; but the rest took lecture-based or incomplete education. The findings of the present study can be applied to improve crane-related policies and special safety training systems.
Tran, Si Van-Tien;Lee, Doyeop;Pham, Trang Kieu;Khan, Numan;Park, Chansik
International conference on construction engineering and project management
/
2020.12a
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pp.96-102
/
2020
The construction industry remains serious accidents, injuries, and fatalities due to it's unique, dynamic, and temporary nature. On workplace sites, Safety pre-task planning is one of the efforts to minimize injuries and help construction personnel to identify potential hazards. However, the working conditions are complicated. Many activities, including tasks or job steps, are executing at the same time and place. It may lead to an increase in the risks from simultaneous tasks. This paper contributes to addressing this issue by introducing a safety risk interaction analyzing framework. To accomplish this objective, accident reports of the Occupational Safety and Health Administration (OSHA) are investigated. The pairs of task incompatibility, which have time-space conflicts and lead to incidents, are found. Ontology technology is applied to build the risk database, in which the information is acquired, structuralized. The proposed system is expected to improve pre-task planning efficiency and relieve the burdens encountered by safety managers. A user scenario is also discussed to demonstrate how the ontology supports pre-task planning in practice.
Robot related injuries in industrial accidents statistics during 2008~2010 have accounted for a total of 109 cases equivalent to 30~40 cases for each of those years. The number of injured compared to the dissemination of industrial robots(51,302 units/2004) can be regarded as quite low. However, the fatal injuries sustained by 7 (6.4%) out of 109 cases paints the stark reality of robot-related accident fatalities. It is a sad probability that as the automation process expands its use of industrial robots which have increased significantly in demand, the incidence of workplace accidents will also increase. Therefore, the incidence of accidents throughout the period of 2008~2010 has been analysed to prevent the injuries due to the increased use of industrial robots. In the analysis, the injuries occurred during the industrial robot operation accounted for 45.9% of the entire accidents. Thus, we examined the present status of the industrial robot operation to analyze the root cause of accidents occurred in our studied time period. We looked at a total of 469 workplaces. 456 workplaces responded in the year 2009 and survey studies were implemented at 13 of the 29 workplaces where work injuries were sustained in the year 2010. Even where protective measures and interlock devices were in place, our studies indicated that workers could access the robot area to perform the tasks in 188 sites(40.1%). Also, the 143 sites(30.5%) had control measures and equipment located in the safety fence. In addition, the robots found at 164 sites(35.0%) could be restarted without additional restarting operation. These three causes accounted for most of the workplace injuries during the industrial robot operations. Futhermore, we confirmed the fact that the protective measures of the current safety regulations were not strictly enforced. Based upon our studies and the investigation of the present status of the industrial robot operation, higher standards in training and supervision of workers in the robot operation must quickly be met in order to prevent these industrial injuries.
Journal of the Korean Society of Industry Convergence
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v.22
no.6
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pp.665-671
/
2019
The estimated on-site accident rate in Forestry is relatively high. According to statistics of the accident, in the recent 5 years, from 2014 to 2018, forestry accidents have resulted in 98% of injuries and 87% of fatalities. Especially, there are significant geographical constraints to access to the scene in case of an accident. Even though the capacity of first aid capacity is notably emphasized its importance to minimize the scale of damages, the relevant employees have been educated only basic first aid, which is not considered circumstances or geographic limitations, by Occupation Safety and Health Acts. Therefore, the purpose of this study is to derive a direction for a forest emergency service system to increase forestry workers' survival and prevent secondary injury through securing 'Golden Time.' This study conducts analyzing relevant laws and regulations in domestic and international settings as well as looking at several concerned accident cases. The outcome of analysis presents an issue regarding the implementation of onsite first aid in forestry and existing risk factors depending on the working process. Finally, we suggest two ways to improve the forest emergency service that are 1) an appropriate curriculum and kit for forest first aid; and 2) a system for emergency transfer through sharing information between National Fire Agency (NFA) and emergency medical service center, and emergency and rescue mission using helicopter from NFA and Korea Forest Service.
Journal of the Korea Institute of Building Construction
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v.21
no.2
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pp.165-174
/
2021
The construction industry causes the most accidents and fatalities among all industries. Although many efforts have been made to reduce safety accidents in construction, the study on the lost workdays that return to work place is insufficient. Therefore, this study proposes a model that classifies the lost workdays lost into moderate and severity, and derives the importance of variable and analyzes important factors through the trained random forest model. We analyze the learning process of the random forest which is a black box model, and extracted important variables that impact on the severity of the lost workdays through the extracted feature importance. The factors existing inside were analyzed through the extracted variables. The purpose of this study is to analyze the accident case data at the construction site through a random forest model and to review variables that have a high impact on the lost workdays. In the future, this sutdy can apply to improve construction safety management and reduce the accident of industrial accidents.
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