• 터널과지하공간
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• 제32권3호
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• pp.194-202
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• 2022

2000년대 이후 자원개발 분야에서는 안전성, 친환경 및 저비용 등의 이유로 ICT 기술을 적용한 사례들이 증가되고 있다. 국내에서도 제 2차 광업기본계획에서 광업 전주기와 ICT 융합에 대한 중요성을 명시하고, 제 3차 광업기본계획에서는 국내에 ICT 광산장비 보급 지원 및 스마트마이닝 시범 도입 등 ICT와 스마트 마이닝에 대해 강조하고 있다. 본 연구는 (주)고려시멘트 장성 광업소에서의 ICT 장비의 활용과 안전시스템 운용에 대해 설명하였다. 장성 광업소에서는 측량과 3D 스캐닝이 가능한 멀티스테이션과 핸드형 3D 스캐닝 등 두 종류의 3D 장비를 혼용하여 갱도의 3D 측량을 실시하고 있다. 3D 측량을 통해서 각 편별 위험 개소 및 특이사항을 파악하고, 편과 편 사이의 크라운 필라에 대한 안정성을 분석하였다. 또한, 실시간 위치추적 및 통신시스템을 구축하여 갱내 사고에 대한 구조방안 및 대피계획을 수립하고 있다.

• Geomechanics and Engineering
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• 제9권4호
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• pp.483-498
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• 2015

This article describes a new in-situ load test called the Hydraulic Cylinder Test (HCT) and its application to determine the geotechnical properties of soil-rock mixtures. The main advantages of the test are its easy implementation, speed of execution and low-cost. This article provides a detailed description of the equipment and the test procedure, and examines a case study of its application to determine the geotechnical properties of an earth-filled dam for a tailings pond. The containment dams of the ponds are made from blocks of gypsum and marl, obtained from the excavation of the ponds, mixed in a matrix of sands and clays. The size of the rocks varies between 1 and 30 cm. The HCT is particularly useful for determining the geotechnical properties of this type of soil-rock mixture. Nine HCTs were carried out to determine its strength (c, ${\phi}$) and deformation (B, G) properties. The results obtained were validated using the Bim strength criterion, recently proposed, and some pressure meter tests carried out beforehand. The properties obtained are used to analyze the stability of the dam using computer simulations and a modification to its design is proposed.

• 한국정보통신학회논문지
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• 제11권11호
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• pp.2185-2191
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• 2007

전통적인 센서 네트워크는 고가의 센서와 케이블로 연결되어 있어, 센싱 데이터를 수집할 때 유연성이 떨어지는 단점을 가지고 있다. WSN은 저가의 장비를 사용하고, 임무를 여러 노드에서 나누어서 수행하기 때문에 다각도에서 세밀한 데이터를 수집할 수 있다. 본 논문에서는 대한석탄공사의 작업현장에서 IEEE802.15.4 MAC을 이용하여, 채탄 작업환경을 그대로 적용한 채탄토폴로지를 구성하였다. 채탄 작업시에 작업 관리자의 이동성 지원을 위한 모델들을 제안하였고, 시뮬레이션을 수행하여 최적의 모델을 선정하였다. 본 논문의 결과는 대한석탄공사와 다른 광업소에서 WSN을 적용할 때 중요 자료로 사용할 수 있을 것이다.

• 한국정보전자통신기술학회논문지
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• 제14권4호
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• pp.292-299
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• 2021

IT기술의 발달로 제조 기반의 IIoT환경을 기반으로 한 데이터 마이닝 형태의 소프트웨어들이 점차 늘어나고 있다. 그러나 빅데이터 및 데이터마이닝을 진행해야 하는 대량의 데이터를 가지는 제조 기업의 소프트웨어 특성상 일반 소프트웨어와 동일한 형태로 소프트웨어 품질을 평가하기 힘든 실정이다. 또한 이기종간의 장비 및 소프트웨어가 혼재된 제조 기반의 환경에서 특히 기존의 품질 특성을 적용하여 사용되는 소프트웨어에 대한 품질 판단을 진행하기 어렵다. 본 논문에서는 제조 기반의 특성을 조사하고 이에 맞는 소프트웨어 품질 평가 모델을 개발하여 평가를 실시하고자 한다.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• Safety and Health at Work
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• 제13권2호
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• pp.163-169
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• 2022

Background: It is estimated that about 13 million artisanal and small-scale miners carry out their activities under harsh, precarious, unfriendly, and risky conditions. Yet, our understanding of the extent to which these workers use personal protective equipment (PPE) and navigate through the various risks and hazards they face is still limited. This article has two main objectives. First, it explores the extent of usage of PPE among artisanal and small-scale miners for the prevention of hazards and risks. Second, it examines the coping strategies used by these miners as a response to experiences of occupational injuries and risks Methods: A cross-sectional survey of small-scale miners was conducted in six communities across three districts in Ghana, West Africa. The mixed methods approach was adopted. A total of 148 small-scale miners participated in the study. Six focus group discussions (FGDs) were held across the six communities. The data were analysed using descriptive statistics. Chi-square tests were used to analyse the relationship between some socio-demographic characteristics (sex, age, and educational background) and the usage of PPE. Open-ended questions and responses from FGDs were analysed based on the content and verbatim quotations from miners. Results: Findings suggest that 78% of the miners interviewed do not use the appropriate PPE citing reasons such as cost, and their personal discomfort associated with use of PPE. There was no significant relationship between socio-demographic characteristics (i.e., sex, age, education and major mining activity) and the usage of PPE. The study further revealed four main coping strategies used by miners to handle the risks. These are rest, taking unprescribed medication and hard drugs, registration with health insurance scheme and savings and investments. Conclusion: This study shows that very few artisanal miners use PPE despite the significant hazards and risks to which they are exposed. The study recommends to the government to put in place measures to ensure that miners adhere to health and safety regulations before undertaking mining activities. This means that health and safety plans and use of PPE should be linked to the license acquisition process for miners.

• 정보처리학회논문지D
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• 제9D권6호
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• pp.1119-1126
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• 2002

이 논문에서는 공간적 통계기법에 근거한 예측적 공간 데이터 마이닝 방법을 제안하고, 산불위험지역을 예측하는데 적용하였다. 제안된 방법은 조건부 확률과 우도비를 이용한 방법으로 과거 산불발생지역에 대해 산불과 관련된 공간데이터 집합들 사이의 정량적 관계에 의존적인 예측 모델이다. 두 가지 방법을 이용하여 산불위험지역 예측도를 만들고, 각 모델의 예측력을 평가하기 위해 산불위험율(FHR : Forest Fire Hazard Rate)과 예측률곡선(PRC : Prediction Rate Curve)을 이용하였다. 제안된 두 가지 예측모델의 예측력 비교분석 결과, 우도비 방법이 조건부 확률 방법보다 더 우수한 것으로 나타났다. 이 논문에서 제안된 산불위험지역 예측모델을 이용하여 작성된 산불위험지역 예측도는 산불예방과 산불감시장비 및 인력의 효율적인, 배치 등 산불관리의 효율성을 높이는데 많은 도움을 줄 것으로 기대된다.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.211-218
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• 2023

Due to the implementation of COVID-19 distancing, interest and users in 'home training' are rapidly increasing. Therefore, the purpose of this study is to identify the perception of 'home training' through big data analysis on social media channels and provide basic data to related business sector. Social media channels collected big data from various news and social content provided on Naver and Google sites. Data for three years from March 22, 2020 were collected based on the time when COVID-19 distancing was implemented in Korea. The collected data included 4,000 Naver blogs, 2,673 news, 4,000 cafes, 3,989 knowledge IN, and 953 Google channel news. These data analyzed TF and TF-IDF through text mining, and through this, semantic network analysis was conducted on 70 keywords, big data analysis programs such as Textom and Ucinet were used for social big data analysis, and NetDraw was used for visualization. As a result of text mining analysis, 'home training' was found the most frequently in relation to TF with 4,045 times. The next order is 'exercise', 'Homt', 'house', 'apparatus', 'recommendation', and 'diet'. Regarding TF-IDF, the main keywords are 'exercise', 'apparatus', 'home', 'house', 'diet', 'recommendation', and 'mat'. Based on these results, 70 keywords with high frequency were extracted, and then semantic indicators and centrality analysis were conducted. Finally, through CONCOR analysis, it was clustered into 'purchase cluster', 'equipment cluster', 'diet cluster', and 'execute method cluster'. For the results of these four clusters, basic data on the 'home training' business sector were presented based on consumers' main perception of 'home training' and analysis of the meaning network.

• ETRI Journal
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• 제38권4호
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• pp.787-797
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• 2016

Mining, construction, and other special vehicles for heavy use are designed to work under high-performance and off-road working conditions. The driving and executive mechanisms of the support structures and superstructures of these vehicles frequently operate under high loads. Such high loads place the equipment under constant risk of an accident and can jeopardize the dynamic stability of the machinery. An experimental investigation was conducted on a refuse collection vehicle. The aim of this research was to determine the working conditions of a real vehicle: the kinematics of the waste container, that is, a hydraulic rotate drum for waste collection; the dynamics of the load manipulator (superstructure); the vibrations of the vehicle mass; and the strain (stress) of the elements responsible for the supporting structure. For an examination of the force (weight) on the rear axle of a heavy vehicle, caused by its own weight and additional load, a universal measurement system is proposed. As a result of this investigation, we propose an alternative system for continuous vehicle weighing during waste collection while in motion, that is, an on-board weighing system, and provide suggestions for measuring equipment designs.

• 한국정보시스템학회지:정보시스템연구
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• 제26권2호
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• pp.105-121
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• 2017

Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.