• 한국태양에너지학회 논문집
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• 제25권4호
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• pp.29-35
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• 2005

Wind turbines can produce an unpolluted electricity getting energy only from the natural resource. It is one of the most economic power generating system among renewables up to now. Currently, ther are many wind turbines in operation world-wide under various external conditions. A wind turbine is composed of many machine components. So it is likely that the many accidents have been occurred in many wind turbines. In this paper, we reviewed "Wind turbine Accident data" of Caithness Windfarms Information Forum 2005. We classified this data and analyzed. The most of wind turbines in our country are foreign product. It is like that application it is possible with information which is important for wind farm operations and maintenance and for the wind turbine design and manufacturing.

• 한국안전학회지
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• 제35권2호
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• pp.94-99
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• 2020

Bikers can be subjected to injuries from unexpected accidents even if they wear basic helmets. A properly designed airbag can efficiently protect the critical areas of the human body. This study introduces a wearable smart airbag system using machine learning techniques to protect human neck and shoulders. When a bicycle accident happens, a microprocessor analyzes the biker's motion data to recognize if it is a critical accident by comparing with accident classification models. These models are trained by a variety of possible accidents through machine learning techniques, like k-means and SVM methods. When the microprocessor decides it is a critical accident, it issues an actuation signal for the gas inflater to inflate the airbag. A protype of the wearable smart airbag with the machine learning techniques is developed and its performance is tested using a human dummy mounted on a moving cart.

• International Journal of Aeronautical and Space Sciences
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• 제16권3호
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• pp.451-462
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• 2015

Safety is the first priority in civil aviation, and so the International Civil Aviation Organization (ICAO) has introduced and mandated the use of Safety Management Systems (SMS) by airlines, airports, air traffic services, aircraft maintenance organizations, and training organizations. The aircraft manufacturing industry is the last for which ICAO has mandated the implementation of SMS. Since SMS is a somewhat newer approach for most manufacturers in the aviation industry, they hardly believe in the value of implementing SMS. The management of safety risk characteristics that occur during early aircraft development stages and the systematic linkage that the safety risk has to do with an aircraft in service could have a significant influence on the safe operation and life cycle of the aircraft. This paper conducts a case analysis of the McDonnell Douglas MD-11 accident/incident to identify the root causes and safety risk levels, and also verified why aircraft manufacturing industry should begin to adopt SMS in order to prevent aircraft accident.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제12권9호
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• pp.273-282
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• 2023

최근 스마트항만을 구축하기 위해 ICT 기술이 적용된 물류 자동화, 항만 운영 자동화 등 다양한 기술이 개발 중이다. 하지만 항만 안전과 안전사고를 예방하기 위한 기술 개발은 부족한 상황이다. 이에 본 논문에서는 항만 내 컨테이너 적재 공간에서 발생할 수 있는 안전사고를 예방하기 위한 인공지능 기반 컨테이너 적재 안전관리 시스템을 제안한다. 이 시스템은 인공지능 기반 컨테이너 안전사고 위험도 분류 및 저장 기능과 실시간 안전사고 모니터링 기능으로 구성되어 있다. 이 시스템은 실시간으로 현장의 사고 위험도를 모니터링하며 이를 통해 컨테이너 붕괴사고를 예방할 수 있다. 제안된 시스템은 프로토타입으로 개발되어 직접 항만에 적용하여 시스템을 평가하였다.

• 대한안전경영과학회지
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• 제16권3호
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• pp.195-200
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• 2014

Occupational fatal injury rate per 10,000 population of Korea is still higher among the OECD member countries. To prevent fatal injuries, the causes of accidents including human error should be analyzed and then appropriate countermeasures should be established. There was an severe converter furnace accident resulting in five people death by chocking in 2013. Although the accident type of the furnace accident was suffocation, many safety problems were included before reaching the death of suffocation. If the safety problems are reviewed throughly, the alternative measures based on the review would be very useful in preventing similar accidents. In this study, we investigated the converter furnace accident by using human error analysis and accident scenario analysis. As a result, it was found that the accident was caused by some human errors, inappropriate task sequence and lack of control in coordinating work by several subordinating companies. From the review of this case, the followings are suggested: First, systematic human error analysis should be included in the investigation of fatal injury accidents. Second, multi man-machine accident scenario analyis is useful in most of coordinating work. Third, the more provision of information on system state will lessen human errors. Fourth, the coordinating control in safety should be performed in the work conducting by several different companies.

• 해양환경안전학회지
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• 제23권2호
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• pp.168-176
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• 2017

HNS사고는 대규모 화재와 폭발을 수반하며, 다수의 인명사고와 주변지역에 극심한 환경오염을 야기함으로 신속한 의사결정을 통하여 광범위한 확산을 막아야 한다. 본 연구는 국내 HNS사고사례를 해상이라는 특수성이 반영된 표준코드를 바탕으로 고품질, 표준화, 디지털화된 HNS사고 데이터베이스를 구축하여 사고발생 시 신속하고 합리적인 의사결정을 지원하고, 체계적인 통합관리 및 공유가 가능한 HNS사고이력관리시스템(HATS)을 설계하고 구현하였다. 또한 개발된 시스템을 활용하여 23년간 수집된 국내 HNS사고데이터 76건에 대해 각 항목별로 통계분석을 수행하여, 국내에서는 매년 평균 3.3건의 사고가 일어나며, 주요 HNS사고요인은 춘계기간 (41%), 계류장 (51 %), 케미컬운반선 (49 %), 승무원에 의한 과실 (45 %), 자일렌류 (12 %)인 것으로 확인되었다. (괄호안 : 사고분류기준별 해당 사고요인의 퍼센트 비율임)

• 한국안전학회지
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• 제35권4호
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• pp.64-73
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• 2020

As Korean government and safety-related organizations make continuous efforts to reduce the number of industrial accidents, accident rate has steadily declined since 2010, thereby recording 0.48% in 2017. However, the number of fatalities due to industrial accidents was 1,987 in 2017, which means that more efforts should be made to reduce the number of industrial accidents. As an essential activity for enhancing the system safety, accident analysis can be effectively used for reducing the number of industrial accidents. Accident analysis aims to understand the process of an accident scenario and to identify the plausible causes of the accident. Accident analysis offers useful information for developing measures for preventing the recurrence of an accident or its similar accidents. However, it seems that the current practice of accident analysis in Korean manufacturing companies takes a simplistic accident model, which is based on a linear and deterministic cause-effect relation. Considering the actual complexities underlying accidents, this would be problematic; it could be more significant in the case of human error-related accidents. Accordingly, it is necessary to use a more elaborated accident model for addressing the complexity and nature of human-error related accidents more systematically. Regarding this, HFACS(Human Factors Analysis and Classification System) can be a viable accident analysis method. It is based on the Swiss cheese model and offers a range of causal factors of a human error-related accident, some of which can be judged as the plausible causes of an accident. HFACS has been widely used in several work domains(e.g. aviation and rail industry) and can be effectively used in Korean industries. However, as HFACS was originally developed in aviation industry, the taxonomy of causal factors may not be easily applied to accidents in Korean industries, particularly manufacturing companies. In addition, the typical characteristics of Korean industries need to be reflected as well. With this issue in mind, we developed HFACS-K as a method for analyzing accidents happening in Korean industries. This paper reports the process of developing HFACS-K, the structure and contents of HFACS-K, and a case study for demonstrating its usefulness.

• 한국안전학회지
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• 제36권4호
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• pp.80-87
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• 2021

Risk assessment techniques are processes used to evaluate hazardous risk factors in construction sites, facilities, raw materials, machinery, and equipment, and to estimate the size of risk that could lead to injury or disease, and establish countermeasures. The most important thing in assessing risk is calculating the size of the risk. If the size of the risk cannot be calculated objectively and quantitatively, all members who participated in the evaluation would passively engage in establishing and implementing appropriate measures. Therefore, this study focused on predicting accidents that are expected to occur in the future based on past occupational accident statistics, and quantifying the size of the risk in an overview. The technique employed in this study differs from other risk assessment techniques in that the subjective elements of evaluators were excluded as much as possible by utilizing past occupational accident statistics. This study aims to calculate the size of the risk, regardless of evaluators, such as a manager, supervisor, safety manager, or employee. The size of the risk is the combination of the likelihood and severity of an accident. In this study, the likelihood of an accident was evaluated using the theory of Bud Accident Chainability, and the severity of an accident was calculated using the occupational accident statistics over the past five years according to the accident classification by the International Labor Organization.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.

• 대한안전경영과학회지
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• 제12권1호
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• pp.35-42
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• 2010

Due to the industrialization and urbanization, the transport of hazardous materials increases, which rises possibilities in occurring prospective accidents in terms of hazardous material transport as well. This study applied the model developed from the previous research to analyze the scale of damage areas from the accidents related to hazardous material accidents, as well as suggested a method to measure automatically the scale of accident including casualties and environmental damage based on the guideline which suggests the quantities of hazardous materials exposed from an accident and was defined in the study of standardization for hazardous material classification. A buffering analysis technique of Geographic Information System (GIS) was applied for that. To apply the model which evaluates the scale of population and exposure to environment on each link, rail network, zones, rail accident data, rail freight trips, and locations of rivers etc were complied as a database for GIS analysis. In conclusion, a method to measure damage areas by the types of hazardous materials was introduced using a Clip and a Special Join technique for overlay analysis.