• Title/Summary/Keyword: Accident classification system

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A Study on the Standard and Information System for Urban Transit Maintenance (도시철도 유지보수체계 표준화 및 정보화에 대한 연구)

  • Ahn, Tae-Ki;Shin, Jeong-Ryol;Park, Kee-Jun
    • Journal of the Korean Society for Railway
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    • v.9 no.5 s.36
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    • pp.539-543
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    • 2006
  • We need to make the standards of maintenance information for urban transit to reduce the cost to maintain the information and to share the information with maintenance workers. It is enable to do systematic maintenance for urban transit by using the information system based on the standardized information. In this paper we propose the major items to standardize and the methods to lay out the standard schemes to enable structured maintenance. We present the 4 items, bill of material, material classification, accident/fault classification, electronic document, to standardize. And we propose how to implement the information system for urban transit based on the standardized information. We describe the implemented information system in two parts; a rolling-stock and an infrastructure part. And also we describe the result of survey to evaluate the system installed at Seoul Metro and Seoul Metropolitan Rapid Transit.

A Suggestion of the Direction of Construction Disaster Document Management through Text Data Classification Model based on Deep Learning (딥러닝 기반 분류 모델의 성능 분석을 통한 건설 재해사례 텍스트 데이터의 효율적 관리방향 제안)

  • Kim, Hayoung;Jang, YeEun;Kang, HyunBin;Son, JeongWook;Yi, June-Seong
    • Korean Journal of Construction Engineering and Management
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    • v.22 no.5
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    • pp.73-85
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    • 2021
  • This study proposes an efficient management direction for Korean construction accident cases through a deep learning-based text data classification model. A deep learning model was developed, which categorizes five categories of construction accidents: fall, electric shock, flying object, collapse, and narrowness, which are representative accident types of KOSHA. After initial model tests, the classification accuracy of fall disasters was relatively high, while other types were classified as fall disasters. Through these results, it was analyzed that 1) specific accident-causing behavior, 2) similar sentence structure, and 3) complex accidents corresponding to multiple types affect the results. Two accuracy improvement experiments were then conducted: 1) reclassification, 2) elimination. As a result, the classification performance improved with 185.7% when eliminating complex accidents. Through this, the multicollinearity of complex accidents, including the contents of multiple accident types, was resolved. In conclusion, this study suggests the necessity to independently manage complex accidents while preparing a system to describe the situation of future accidents in detail.

A Classification of the Wind Turbine Accident (풍력발전기에서 발생하는 사고의 원인에 대한 분류)

  • Yang, In-Sun;Kim, Seok-Woo;Kyong, Nam-Ho
    • Journal of the Korean Solar Energy Society
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    • v.25 no.4
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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.

A Study on a Wearable Smart Airbag Using Machine Learning Algorithm (머신러닝 알고리즘을 사용한 웨어러블 스마트 에어백에 관한 연구)

  • Kim, Hyun Sik;Baek, Won Cheol;Baek, Woon Kyung
    • Journal of the Korean Society of Safety
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    • v.35 no.2
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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.

Roles of Safety Management System (SMS) in Aircraft Development

  • Lee, Won Kwan;Kim, Seung Jo
    • International Journal of Aeronautical and Space Sciences
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    • v.16 no.3
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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.

Research on Artificial Intelligence Based Shipping Container Loading Safety Management System (인공지능 기반 컨테이너 적재 안전관리 시스템 연구)

  • Kim Sang Woo;Oh Se Yeong;Seo Yong Uk;Yeon Jeong Hum;Cho Hee Jeong;Youn Joosang
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.9
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    • pp.273-282
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    • 2023
  • Recently, various technologies such as logistics automation and port operations automation with ICT technology are being developed to build smart ports. However, there is a lack of technology development for port safety and safety accident prevention. This paper proposes an AI-based shipping container loading safety management system for the prevention of safety accidents at container loading fields in ports. The system consists of an AI-based shipping container safety accident risk classification and storage function and a real-time safety accident monitoring function. The system monitors the accident risk at the site in real-time and can prevent container collapse accidents. The proposed system is developed as a prototype, and the system is ecaluated by direct application in a port.

A Case Study on the Human Error Analysis for the Prevention of Converter Furnace Accidents (전로사고 예방을 위한 인적오류 분석)

  • Shin, Woonchul;Kwon, Jun Hyuk;Park, Jae Hee
    • Journal of the Korea Safety Management & Science
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    • v.16 no.3
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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.

Design and Implementation of an HNS Accident Tracking System for Rapid Decision Making (신속한 의사결정을 위한 HNS 사고이력관리시스템 설계 및 구현)

  • Jang, Ha-Lyong;Ha, Min-Jae;Jang, Ha-Seek;Yun, Jong-Hwui;Lee, Eun-Bang;Lee, Moon-jin
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.2
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    • pp.168-176
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    • 2017
  • HNS accidents involve large-scale fires and explosions, causing numerous human casualties and extreme environmental pollution in the surrounding area. The widespread diffusion of effects should be prevented through rapid decision making. In this study, a high-quality, standardized, and digitized HNS accident databases has been generated based on the HNS standard code proposed. Furthermore, the HNS Accident Tracking System (HATS) was applied and implemented to allow for systematic integration management and sharing. In addition, statistical analysis was performed on 76 cases of domestic HNS accident data collected over 23 years using HATS. In Korea, an average of 3.3 HNS accidents occurred each year and major HNS accident factors were Springs (41 %), Aprons (51 %), Chemical Carriers (49 %), Crew's Fault (45 %) and Xylenes (12 %). (The number in parentheses is the percentage of HNS accident factors for each HNS accident classification)

HFACS-K: A Method for Analyzing Human Error-Related Accidents in Manufacturing Systems: Development and Case Study (제조업의 인적오류 관련 사고분석을 위한 HFACS-K의 개발 및 사례연구)

  • Lim, Jae Geun;Choi, Joung Dock;Kang, Tae Won;Kim, Byung Chul;Ham, Dong-Han
    • Journal of the Korean Society of Safety
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    • v.35 no.4
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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.

A Case Study on the Estimation of the Risk based on Statistics (산업재해통계기반 Risk 산정에 관한 연구)

  • Woo, Jong-Gwon;Lee, Mi-Jeong;Seol, Mun-Su;Baek, Jong-Bae
    • Journal of the Korean Society of Safety
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    • v.36 no.4
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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.