• 제목/요약/키워드: mining equipment

검색결과 92건 처리시간 0.036초

텍스트 마이닝을 통한 건설기계분야 국내 정부 R&D 연구동향 분석 (Text-Mining Analysis of Korea Government R&D Trends in Construction Machinery Domains)

  • 윤봄;배준수
    • 산업경영시스템학회지
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    • 제46권spc호
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    • pp.1-8
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    • 2023
  • To investigate the national science and technology policy direction in the field of construction machinery, an analysis was conducted on projects selected as national research and development (R&D) initiatives by the government. Assuming that the project titles contain key keywords, text mining was employed to substantiate this assumption. Project information data spanning nine years from 2014 to 2022 was collected through the National Science & Technology Information Service (NTIS). To observe changes over time, the years were divided into three-year sections. To analyze research trends efficiently, keywords were categorized into groups: 'equipment,' 'smart,' and 'eco-friendly.' Based on the collected data, keyword frequency analysis, N-gram analysis, and topic modeling were performed. The research findings indicate that domestic government R&D in the construction machinery field primarily focuses on smart-related research and development. Specifically, investments in monitoring systems and autonomous operation technologies are increasing. This study holds significance in analyzing objective research trends through the utilization of big data analysis techniques and is expected to contribute to future research and development planning, strategic formulation, and project management.

An Interactive Planning and Scheduling Framework for Optimising Pits-to-Crushers Operations

  • Liu, Shi Qiang;Kozan, Erhan
    • Industrial Engineering and Management Systems
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    • 제11권1호
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    • pp.94-102
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    • 2012
  • In this paper, an interactive planning and scheduling framework are proposed for optimising operations from pits to crushers in ore mining industry. Series of theoretical and practical operations research techniques are investigated to improve the overall efficiency of mining systems due to the facts that mining managers need to tackle optimisation problems within different horizons and with different levels of detail. Under this framework, mine design planning, mine production sequencing and mine transportation scheduling models are integrated and interacted within a whole optimisation system. The proposed integrated framework could be used by mining industry for reducing equipment costs, improving the production efficiency and maximising the net present value.

A Study on the Fault Process and Equipment Analysis of Plastic Ball Grid Array Manufacturing Using Data-Mining Techniques

  • Sim, Hyun Sik
    • Journal of Information Processing Systems
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    • 제16권6호
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    • pp.1271-1280
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    • 2020
  • The yield and quality of a micromanufacturing process are important management factors. In real-world situations, it is difficult to achieve a high yield from a manufacturing process because the products are produced through multiple nanoscale manufacturing processes. Therefore, it is necessary to identify the processes and equipment that lead to low yields. This paper proposes an analytical method to identify the processes and equipment that cause a defect in the plastic ball grid array (PBGA) during the manufacturing process using logistic regression and stepwise variable selection. The proposed method was tested with the lot trace records of a real work site. The records included the sequence of equipment that the lot had passed through and the number of faults of each type in the lot. We demonstrated that the test results reflect the real situation in a PBGA manufacturing process, and the major equipment parameters were then controlled to confirm the improvement in yield; the yield improved by approximately 20%.

절취사면의 암질평가사례 (Case Study of Rock Mass Classifications in Slopes)

  • 신희순;한공창;선우춘;송원경;신중호;박찬
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2000년도 봄 학술발표회 논문집
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    • pp.109-116
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    • 2000
  • Rippability refers to the ease of excavation by construction equipment. Since it is related to rock quality in terms of hardness and fracture density, which may be measured by seismic refraction surveys, correlations have been made between rippability and seismic P wave velocities. The 1-channel signal enhancement seismograph(Bison, Model 1570C) was used to measure travel time of the seismic wave through the ground, from the source to the receiver. The seismic velocity measurement was conducted with 153 lines at 5 rock slopes of Chungbuk Youngdong area. Schmidt rebound hardness test were conducted with 161 points on rock masses and the point load test also on 284 rock samples. The uniaxial compressive strength and seismic wave velocity of 60 rock specimens were measured in laboratory. These data were used to evaluate the rock quality of 5 rock slopes.

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텍스트 마이닝을 통한 건설 생산성 분야의 연구동향 분석 - KSCE 저널을 중심으로 - (Analysis on Research Trend of Productivity Using Text Mining - Focusing on KSCE Journal -)

  • 구본길;허영기
    • 한국건설관리학회논문집
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    • 제21권2호
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    • pp.15-21
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    • 2020
  • 국토교통부가 2017년 12월에 발표한 제6차 건설기술진흥기본계획에 따르면, 건설기술혁신 등을 통해 2022년까지 건설 노동생산성을 40% 향상하는 것을 주요 목표로 하고 있다. 또한, 건설업계 및 학계에서는 건설 생산성 향상을 위해 지속적으로 다양한 연구 및 개발을 해오고 있다. 본 연구에서는 과거 15년간 대한토목학회 영문논문집에 발표된 생산성(Productivity) 관련 논문을 대상으로 어 프라이오리(A Priori) 알고리즘을 활용하여 키워드(Keyword) 간의 상관관계를 분석하였다. 분석 결과, 생산성 연구 키워드는 '작업(Work)' 및 '노무 인력(Labor)' 단어와 연관성이 매우 높은 것으로 나타났으며 생산성 영향요소, 생산성 모델과 시뮬레이션, 그리고 작업 시간에 따른 생산성 등이 키워드로 주로 연구되고 있음이 밝혀졌다. 또한, 건설기계(Machine) 혹은 장비(Equipment)와의 상관성은 낮은 것으로 분석되었다. 본 연구는 텍스트 마이닝(Text Mining)을 활용하여 국내 토목 분야에서 이루어진 생산성 관련 연구들의 개략적인 상관성과 경향을 분석하였으며, 특정 분야에서 이루어지고 있는 연구 동향 분석의 새로운 방안을 제시하였다.

구리원석광산에서의 Elemental Carbon (EC) 노출에 관한 사례연구 (A Case Study of Exposure to Elemental Carbon (EC) in an Underground Copper Ore Mine)

  • 이수길;김정희;김성수
    • 한국환경과학회지
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    • 제26권9호
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    • pp.1013-1021
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    • 2017
  • Exposure to Diesel Particulate Matter (DPM) potentially causes adverse health effects (e.g. respiratory symptoms, lung cancer). Due to a lack of data on Elemental Carbon (EC) exposure levels in underground copper ore mining (unlike other underground mining industries such as non-metallic and coal mining), this case study aims to provide individual miners' EC exposure levels, and information on their work practices including use of personal protective equipment. EC measurement was carried out during different work activities (i.e. drilling, driving a loader, plant fitting, plant operation, driving a Specialized Mining Vehicle (SMV)) as per NIOSH Method 5040. The copper miners were working 10 h/day and 5 days/week. This study found that the most significant exposures to EC were reported from driving a loader (range $0.02-0.42mg/m^3$). Even though there were control systems (i.e. water tanks and DPM filters) on the diesel vehicles, around 49.5% of the results were over the adjusted recommendable exposure limit ($0.078mg/m^3$). This was probably due to: (1) driver's frequently getting in and out of the diesel vehicles and opening the windows of the diesel vehicles, and (2) inappropriate maintenance of the diesel vehicles and the DPM control systems. The use of the P2 type respirator provided was less than 19.2%. However, there was no significant difference between the day shift results and the night shift results. In order to prevent or minimize exposure to EC in the copper ore mine, it is recommended that the miners are educated in the need to wear the appropriate respirator provided during their work shifts, and to maintain the diesel engine and emission control systems on a regular basis. Consideration should be given to a specific examination of the diesel vehicles' air-conditioning filters and the air ventilation system to control excessive airborne contaminants in the underground copper mine.

Analysis of acoustic emission signals during fatigue testing of a M36 bolt using the Hilbert-Huang spectrum

  • Leaman, Felix;Herz, Aljoscha;Brinnel, Victoria;Baltes, Ralph;Clausen, Elisabeth
    • Structural Monitoring and Maintenance
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    • 제7권1호
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    • pp.13-25
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    • 2020
  • One of the most important aspects in structural health monitoring is the detection of fatigue damage. Structural components such as heavy-duty bolts work under high dynamic loads, and thus are prone to accumulate fatigue damage and cracks may originate. Those heavy-duty bolts are used, for example, in wind power generation and mining equipment. Therefore, the investigation of new and more effective monitoring technologies attracts a great interest. In this study the acoustic emission (AE) technology was employed to detect incipient damage during fatigue testing of a M36 bolt. Initial results showed that the AE signals have a high level of background noise due to how the load is applied by the fatigue testing machine. Thus, an advanced signal processing method in the time-frequency domain, the Hilbert-Huang Spectrum (HHS), was applied to reveal AE components buried in background noise in form of high-frequency peaks that can be associated with damage progression. Accordingly, the main contribution of the present study is providing insights regarding the detection of incipient damage during fatigue testing using AE signals and providing recommendations for further research.

스마트제조시스템의 설비인자 분석 (Analysis of Equipment Factor for Smart Manufacturing System)

  • 안재준;심현식
    • 반도체디스플레이기술학회지
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    • 제21권4호
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    • pp.168-173
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    • 2022
  • As the function of a product is advanced and the process is refined, the yield in the fine manufacturing process becomes an important variable that determines the cost and quality of the product. Since a fine manufacturing process generally produces a product through many steps, it is difficult to find which process or equipment has a defect, and thus it is practically difficult to ensure a high yield. This paper presents the system architecture of how to build a smart manufacturing system to analyze the big data of the manufacturing plant, and the equipment factor analysis methodology to increase the yield of products in the smart manufacturing system. In order to improve the yield of the product, it is necessary to analyze the defect factor that causes the low yield among the numerous factors of the equipment, and find and manage the equipment factor that affects the defect factor. This study analyzed the key factors of abnormal equipment that affect the yield of products in the manufacturing process using the data mining technique. Eventually, a methodology for finding key factors of abnormal equipment that directly affect the yield of products in smart manufacturing systems is presented. The methodology presented in this study was applied to the actual manufacturing plant to confirm the effect of key factors of important facilities on yield.

탐해2호의 240채널 해양탄성파 탐사자료취득 (240 channel Marine Seismic Data Acquisition by Tamhae II)

  • 박근필;이호영;구남형;김경오;강무희;장성형;김영건
    • 지구물리와물리탐사
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    • 제2권2호
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    • pp.77-85
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    • 1999
  • 국내 대륙붕에서의 석유발견 가능성 제고를 위하여 탐해2호가 건조되었으며, 이를 이용하여 국내최초로 240 채널 2차원 해양 탄성파 탐사가 동해에서 이루어졌다. 탐해2호에는 2차원 및 3차원 탄성파 탐사를 위한 음원 및 수신장비, 기록장비 그리고 항측장비 등이 갖추어져 있고, 간단한 선상자료처리 시스템도 포함되어 있다. 음원은 4개의 소배열로 구성되어 있으며 각 소배열은 6개의 에어건으로 구성된다. 전체 음원 용량은 4578 $in^3$이다. 수신장비는 2조의 스트리머로 구성되며 각 조는 240 채널로 길이가 3 km이다. 탐사선 도입 후 처음 시도된 현장탐사에서 성공적인 2차원 탄성파 탐사 자료를 취득하였다. 전산처리를 통하여 자료취득 상태를 점검한 결과 양질의 탄성파 자료가 취득되었음을 확인할 수 있었다. 양질의 자료를 취득하기 위해서는 전체적인 탐사설계, 탐사장비 운용, 현장탐사시 탐사선의 항해, 체계적인 품질관리 등의 기술이 고루 갖추어져야 한다.

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