• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.spc
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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.

• Industrial Engineering and Management Systems
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• v.11 no.1
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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.

• Journal of Information Processing Systems
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• v.16 no.6
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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%.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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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.

• Korean Journal of Construction Engineering and Management
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• v.21 no.2
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• pp.15-21
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• 2020

The relationship between keywords, found in all productivity related papers published in the KSCE journal for last 15 years, were analyzed in order to reveal a research trend in the area using text mining and A-Priori algorithm. As the results, it is found that the word of 'productivity' is most closely related to the words of 'work' and 'labor'. Futhermore, the word is somewhat related to those of 'factor', 'model', simulation', and 'work time'. It is also revealed that, on the other hand, the words of 'machine' and 'equipment' have little relationships with the keyword. This research will be a great help for academia to understand a research trend in the area of construction productivity.

• Journal of Environmental Science International
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• v.26 no.9
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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.

• Structural Monitoring and Maintenance
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• v.7 no.1
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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.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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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.

• Geophysics and Geophysical Exploration
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• v.2 no.2
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• pp.77-85
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• 1999

The 3-D seismic research vessel, Tamhae II, was built to raise up the probability of the hydrocarbon discovery in the Korean continental shelf and the first test survey was completed in the East Sea. During the survey, the 240 channel 2-D marine seismic data were acquired by the Korean flag vessel for the first time. Tamhae II has been equipped with source, receiver, recording equipment, and navigation equipment as well as an onboard processing system. The source is composed of four subarrays and each subarray has six airguns. Total airgun volume is 4578 $in^3$. The receiver consists of two sets of 3 km long 240 channel streamer. In the first survey, the successful acquisition of 2-D seismic data was accomplished. From the result of the data processing, we confirmed that the high quality seismic data were acquired. For the high quality data acquisition, technology of survey design and planning, operation of vessel and equipments and systematic quality control should be developed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.851-852
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• 2010