• 대한인간공학회지
• /
• 제36권5호
• /
• pp.411-420
• /
• 2017

Objective: The purpose of this study is to analyze the accident characteristics according to the gender of the injured workers in building cleaning and to reflect them in the Industrial Accident Prevention Policy. Background: An analysis of industrial accidents is an essential process for establishing systematic industrial accident prevention measures. In order to establish industrial accident prevention measures for workers effectively, it is necessary to analyze accident characteristics by job type for workers who do the same work. Method: In this study, we analyzed the accident characteristics of 1,645 janitors who were approved of work-related injuries in 2015. We also analyzed the characteristics according to gender by dividing them into worker-related factors and accident-related factors. Results: The accidents caused to the janitors showed different characteristics according to gender, age, work experience, agency of accident, and distribution of original cause materials. In other words, 70.2% occurred to workers over 60 years old and 56.2% occurred to unskilled workers with less than a year of work experience. In the case of accident pattern, 79.1% occurred in tripping (slip) hazards, and 68.2% of accidents occurred on the floor (including the ground) and the stairs, indicating that the accident occurred most frequently during cleaning work on the floor or stairs. Conclusion and Application: The results of the study on the accident characteristics of the janitors can be used as basic data for systematic preventive measures against accidents occurring to the elderly female workers in the service industry.

• 대한안전경영과학회지
• /
• 제5권3호
• /
• pp.1-10
• /
• 2003

Accident analyses are used to identify common factors contributing to occupational accidents and to give recommendations for accident prevention. In this study we developed a human error analysis system that can be used easily at the industries. This accident analysis system can be used to develop accident prevention programs to reduce human initiated accidents.

• 산업공학
• /
• 제15권2호
• /
• pp.114-125
• /
• 2002

The objective of this paper is to describe a systematic accident scenario analysis method(SASA) adept at creating accident scenarios for the design of safer products. This approach was inspired by the Quality Function Deployment(QFD) method, which is conventionally used in quality management. In this study, the QFD provides a formal and systematic scheme to devise accident scenarios while maintaining objectivity. SASA consists of three key stages to be broken down into a series of consecutive steps:(1) developing an accident analysis tableau,(2) devising the accident scenarios using the accident analysis tableau,(3) performing a feasibility test, a clustering process and a patterning process, and finally(4) performing quantitative evaluation of each accident scenario. The SASA was applied to a case study of child safety seats. The accident analysis tableau devised 2828(maximum) accident scenarios from all possible relationships between the hazard factors and situation characteristics. Among them, 270 scenarios were devised through the feasibility test and the clustering process. The patterning process reduced them to 29 patterns representative of all accident scenarios. Based on an intensive analysis of the accident patterns, design guidelines for a safer child safety seat were recommended. The implications of the study on the child safety seat case were then discussed.

• 한국안전학회지
• /
• 제33권6호
• /
• pp.77-84
• /
• 2018

Report documents of industrial and occupational accidents have continuously been accumulated in private and public institutes. Amongst others, information on narrative-texts of accidents such as accident processes and risk factors contained in disaster report documents is gaining the useful value for accident analysis. Despite this increasingly potential value of analysis of text information, scientific and algorithmic text analytics for safety management has not been carried out yet. Thus, this study aims to develop data processing and visualization techniques that provide a systematic and structural view of text information contained in a disaster report document so that safety managers can effectively analyze accident risk factors. To this end, the risk factor map using text mining and self-organizing map is developed. Text mining is firstly used to extract risk keywords from disaster report documents and then, the Self-Organizing Map (SOM) algorithm is conducted to visualize the risk factor map based on the similarity of disaster report documents. As a result, it is expected that fruitful text information buried in a myriad of disaster report documents is analyzed, providing risk factors to safety managers.

• 한국안전학회지
• /
• 제36권1호
• /
• pp.56-63
• /
• 2021

The narrative texts of industrial accident reports help to identify accident risk factors. They relate the accident triggers to the sequence of events and the outcomes of an accident. Particularly, a set of related keywords in the context of the narrative can represent how the accident proceeded. Previous studies on text analytics for structuring accident reports have been limited to extracting individual keywords without context. We proposed a context-based analysis using a Natural Language Processing (NLP) algorithm to remedy this shortcoming. This study aims to apply Word2Vec of the NLP algorithm to extract adjacent keywords, known as word embedding, conducted by the neural network algorithm based on supervised learning. During processing, Word2Vec is conducted by adjacent keywords in narrative texts as inputs to achieve its supervised learning; keyword weights emerge as the vectors representing the degree of neighboring among keywords. Similar keyword weights mean that the keywords are closely arranged within sentences in the narrative text. Consequently, a set of keywords that have similar weights presents similar accidents. We extracted ten accident processes containing related keywords and used them to understand the risk factors determining how an accident proceeds. This information helps identify how a checklist for an accident report should be structured.

• 한국안전학회지
• /
• 제35권4호
• /
• pp.64-73
• /
• 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.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2005년도 춘계학술대회 논문집
• /
• pp.151-156
• /
• 2005

The objective of this study is to devise an accident scenario analysis method adept at creating accident scenarios at the Preliminary Hazard Analysis(PHA) step of a hazard analysis for railway system. This approach was inspired by the Quality Function Deployment(QFD) method, which is conventionally used in quality management and was used at the systematic accident scenario analysis(SASA) for the design of safer products. In this study, the QFD provides a formal and systematic schema to devise accident scenarios while maintaining objective. The accident scenario analysis method first identifies the hazard factors that cause railway accidents and explains the situation characteristics surrounding the accident. This method includes a feasibility test, a clustering process and a pattering process for a clearer understanding of the accident situation. Since this method enables an accident scenario analysis method to be performed systematically as well as objectively, this method is useful in building better accident prevention strategies. Therefore, this study can serve to reduce railway accident and be an effective tool for a hazard analysis.

• 한국항공운항학회지
• /
• 제25권4호
• /
• pp.195-203
• /
• 2017

Around 70% of domestic aircraft accidents in helicopter aircraft. The causal factors of the helicopter accidents are identified as human factors. People have focused mostly on unsafe acts to prevent the accident. The accidents should be analysed on human factors to reduce accident. The unsafe acts can be managed effectively if the latent failures were identified through the HFACS. This paper is to introduce about the latent failure classified by the HFACS and provide the analysis regarding the latent failure of the helicopters by the aviation safety advisors through the interviews.

• Journal of the Korean Data and Information Science Society
• /
• 제26권3호
• /
• pp.661-668
• /
• 2015

교통사고는 인구의 증가와 그에 따른 자동차의 증가로 인하여 매년 증가하고 있다. 그러한 교통사고의 원인은 운전자의 부주의뿐만 아니라 도로상의 기상상황에 의해 영향을 받는다. 특히, 강수량, 시계, 습도, 흐림 정도, 기온 등에 의해 많은 교통사고들이 영향을 받는다. 따라서 본 연구는 다양한 기상 요인의 영향 정도에 따른 교통사고 발생 유무의 분석을 목적으로 하였다. 부산 해운대구의 센텀남대로 및 해운대로의 2013년도 교통사고 발생 자료와 지역별 상세 기상 관측 자료인 AWS 기상자료(시간당 강수량, 강수유무, 기온, 풍속), 시간대, 요일을 활용하여 로지스틱 회귀모형 및 의사결정나무모형을 이용하여 분석하였다. 그 결과 기상 요인 중 강수유무와 기온이 교통사고 발생에 영향을 미치는 요인으로 나타났다. 이러한 결과는 도로위의 기상상태에 따른 교통사고의 발생을 예측하는데 유용하게 사용할 수 있을 것이다.

• 한국건설관리학회논문집
• /
• 제11권3호
• /
• pp.97-104
• /
• 2010

최근 고속도로 건설공사는 대형화, 복잡화, 첨단화로 인한 작업환경 및 작업의 종류도 다양화 되고 있다. 공사 장비 또한 대형화와 고소작업의 증가에 따라 안전사고가 증가하고 있어 건설재해를 감소시키려는 노력이 요구된다. 그러나 구체적이고 과학적 방법을 사용한 기술적 안전관리 대처 수단이 미비하다. 사고 예방을 위해서 안전사고 유형 및 사고요인 등을 통계적인 방법으로 분석하여 각 변수들에 대한 안전관리에 적용할 수 있는 방안이 구체적으로 필요하다. 따라서 본 연구에서는 고속도로 건설공사의 12년간 안전사고에 대한 조사를 실시하여 사고발생요인들에 따라 사고유형 및 환산재해자수에 대한 특성을 분석하기 위한 목적으로 실증분석을 하였다. 연구결과 첫째, 사고요인별 사고유형과의 유의미한 차이를 검정한 결과 사고 발생 원인 및 사고발생 높이가 유의한 차이가 나타났다. 둘째, 기간별요인 중에 사고발생시간이 환산재해자수와의 유의한 차이가 나타났다. 작업여건별 요인 중에는 사고발생원인, 사고발생높이, 사고발생유형이 환산재해자수와의 유의한 차이가 나타났다. 이러한 요인들과 변수들의 특징을 분석하여 제시한 결과는 향후 안전관리 대책 수립에 중요한 의미가 있다.