공통특허분류 분석을 활용한 안전기술융합분야 탐색 : Association Rule Mining(ARM) 접근법

서용윤,Suh, Yongyoon 한국안전학회 2017 한국안전학회지 Vol.32 No.5

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

데이터 분석 기반 미래 신기술의 사회적 위험 예측과 위험성 평가

서용윤 ( Yongyoon Suh ) 한국안전학회 2017 한국안전학회지 Vol.32 No.3

A new technology has provided the nation, industry, society, and people with innovative and useful functions. National economy and society has been improved through this technology innovation. Despite the benefit of technology innovation, however, since technology society was sufficiently mature, the unintended side effect and negative impact of new technology on society and human beings has been highlighted. Thus, it is important to investigate a risk of new technology for the future society. Recently, the risks of the new technology are being suggested through a large amount of social data such as news articles and report contents. These data can be used as effective sources for quantitatively and systematically forecasting social risks of new technology. In this respect, this paper aims to propose a data-driven process for forecasting and assessing social risks of future new technology using the text mining, 4M(Man, Machine, Media, and Management) framework, and analytic hierarchy process (AHP). First, social risk factors are forecasted based on social risk keywords extracted by the text mining of documents containing social risk information of new technology. Second, the social risk keywords are classified into the 4M causes to identify the degree of risk causes. Finally, the AHP is applied to assess impact of social risk factors and 4M causes based on social risk keywords. The proposed approach is helpful for technology engineers, safety managers, and policy makers to consider social risks of new technology and their impact.

4차 산업혁명시대의 산업안전혁신시스템

서용윤(Yongyoon Suh),이상훈(Sanghoon Lee) 한국기술혁신학회 2017 한국기술혁신학회 학술대회 발표논문집 Vol.2017 No.11

산업이 고도화되고 기술발전이 가속화되고 있지만, 생산현장에서의 사고와 재해는 아직까지도 지속적으로 발생하고 있다. 이는 시스템의 대규모화, 복잡화, 다양화 등에 따라 나타나는 불안전한 상태(unsafe condition)와 근로자의 안전불감증, 낮은 학습효과, 안전문화 비활성화 등을 포함하는 불안전한 행동(unsafe behavior)에 기인한다. 최근 4차 산업혁명이 대두되면서, 인간과 기계 시스템 사이의 상호작용이 활발해지고, 데이터 가용성과 알고리즘 우수성이 확보되면서, 산업현장에서도 시스템과 공정안전을 위해 최신 기술을 활용하려는 시도가 시작되고 있다. 궁극적으로는, 품질관리, 고장분석, 작업환경관리, 보건관리 등 생산관리의 다양한 범위에 새로운 산업안전혁신을 가져올 것으로 기대된다. 본 논문에서는 사물인터넷, 드론, 인공지능 등 4차 산업혁명 시대의 하드웨어와 소프트웨어의 결합의 사례를 통해 안전한 생산현장은 물론 신뢰성할 수 있는 공공 및 사회를 위한 지능형 시스템 구축의 필요성을 제시하고자 한다.

개방형 혁신 중심의 산업안전혁신 방안

장우현,서용윤(YONGYOON SUH) 대한산업공학회 2019 대한산업공학회 춘계학술대회논문집 Vol.2019 No.4

국내 제조업 화재감시자 운영의 문제 확인 및 개선방안

김경민,서용윤,이종빈,장성록,Kyung Min Kim,Yongyoon Suh,Jong Bin Lee,Seong Rok Chang 한국안전학회 2023 한국안전학회지 Vol.38 No.6

Sparks cause most fire and explosion accidents in the manufacturing industry during hot work, which ignites surrounding combustible materials. Such incidents lead to high casualties due to suffocation from toxic gases and lack of evacuation. Therefore, the government recently enacted and revised 'The Occupational Safety and Health Act' to prevent fires and explosions at work sites, incorporating legal standards for fire observers, which are important in preventing accidents and the spread of fire during hot work. However, there are notable shortcomings in conducting professional cause analysis of these accidents and in aligning them with advanced foreign legal standards. Additionally, there is a lack of literature review reflecting the manufacturing industry characteristics. Despite the recent enactment and revision of legal standards, gathering sufficient opinions and professional reviews remains insufficient. To address these gaps, interviews were conducted with safety and health workers, analyzing recent fire and explosion causes in domestic manufacturing industries, and reviewing both domestic and international legal standards. Conclusively, proposed improvement measures were centered on the professionalization of fire observer education, enhancing their roles and authority realistically, and improving fire observer placement and operation standards. Consequently, additional 'Occupational Safety and Health Act' standards are necessary for fire observer education and defining the government's role. Second, precise legal standards outlining the role and authority of fire observers are required. Third tailored fire observer arrangements and management standards appropriate for varying work characteristics and company sizes are required. This study emphasizes the importance of supplementing relevant legal standards to prevent fire accidents in the manufacturing industry.

특허분석을 활용한 산업별 안전기술개발 동향 모니터링

최유리,서용윤,Choi, Yuri,Suh, Yongyoon 한국안전학회 2020 한국안전학회지 Vol.35 No.4

Along with the rapid development of industrial technology, the industrial structure has been continuously changed. Accordingly, safety technologies have been gradually developed to be applied into various industrial fields as well, not limited to a specific industry area. As a result, it became important to analyze and predict trends of safety technology development in order to establish technology strategies for industrial safety. In particular, since patents are easily accessible to gather the technology and business information, many studies have highlighted technology forecasting using patent information. Thus, this study proposes the patent analysis of monitoring trends of safety technologies of industry fields, taking into account both static and dynamic aspects through index and text analysis. First, patent documents containing safety-related keywords are collected from the WIPSON database for extracting technology information. Then, the development trends of safety technologies by industry fields are identified and analyzed through the analysis of indicators such as marketability, growth, and activation. The results of various indicator analyses of safety technologies are visualized to compare among industrial safety technologies for businesses and technology developers. Second, textmining algorithm is applied to identify trends of specific technology keywords of major industries extracted from patent index analysis. As a result, it is expected that the safety manager uses the patent analysis of safety technologies to provide safety technology information with safety-related companies and institutes. The extracted safety technologies are applicable to business practice and predict future promising technologies.

개방형 혁신 중심의 산업안전혁신 방안

장우현,서용윤(YONGYOON SUH) 한국경영과학회 2019 한국경영과학회 학술대회논문집 Vol.2019 No.4

국내 산업재해집중수준 확인을 위한 지표분석

이봉근,서용윤,장성록,Lee, Bong Keun,Suh, Yongyoon,Chang, Seong Rok 한국안전학회 2020 한국안전학회지 Vol.35 No.5

For monitoring the status of industrial accidents, many statistical indexes have been developed and applied such as fatal rate, frequency rate, and severity rate. These accident indexes are measured by frequency and loss time according to the accidents in the individual industry level. However, it is less considered to use the index of identifying the industrial concentration of accidents in the holistic view. Thus, this study aims to suggest the accident concentration level among domestic industries through index analysis. The concentration level of industrial accidents is calculated by the accident composition of sub-industries. This concentration level shows whether an industry is comprised of a few sub-industries generating more accidents or an industry consists of sub-industries having the similar number of accidents. To this end, the concentration rate (CR) and concentration index (CI) are proposed to take a look at the industry composition of accidents by embracing the concept of market concentration indexes such as Hirschman-Herfindahl Index. As for the case study, four industries of mining, manufacturing, transportation, and other business (usually service) are analyzed in terms of indexes of accident rate, death(fatality) rate, and CR and CI of accident and death. Finally, we illustrate the positioning map that the accident concentration level is compared with the traditional accident frequency level among industries.

사망사고와 부상사고의 산업재해분류를 위한 기계학습 접근법

강성식,장성록,서용윤,Kang, Sungsik,Chang, Seong Rok,Suh, Yongyoon 한국안전학회 2021 한국안전학회지 Vol.36 No.5

As the prevention of fatal accidents is considered an essential part of social responsibilities, both government and individual have devoted efforts to mitigate the unsafe conditions and behaviors that facilitate accidents. Several studies have analyzed the factors that cause fatal accidents and compared them to those of non-fatal accidents. However, studies on mathematical and systematic analysis techniques for identifying the features of fatal accidents are rare. Recently, various industrial fields have employed machine learning algorithms. This study aimed to apply machine learning algorithms for the classification of fatal and non-fatal accidents based on the features of each accident. These features were obtained by text mining literature on accidents. The classification was performed using four machine learning algorithms, which are widely used in industrial fields, including logistic regression, decision tree, neural network, and support vector machine algorithms. The results revealed that the machine learning algorithms exhibited a high accuracy for the classification of accidents into the two categories. In addition, the importance of comparing similar cases between fatal and non-fatal accidents was discussed. This study presented a method for classifying accidents using machine learning algorithms based on the reports on previous studies on accidents.

컴퓨터 비전 기반 다중객체탐지 기법을 이용한 화재 발생 이벤트 모니터링

박병현,이지섭,하지수,서용윤(Yongyoon Suh) 한국경영과학회 2022 한국경영과학회 학술대회논문집 Vol.2022 No.6