• Tunnel and Underground Space
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• v.32 no.3
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• pp.194-202
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• 2022

An increased number of cases have occurred in applying ICT technology in the resource development field due to factors such as safety, eco-friendliness, and low cost since the 2000s. In Korea, the 2nd mining master plan specified the significance of converging the full cycle of mining and ICT, while the 3rd mining master plan highlighted ICT and smart mining such as supporting the supply of an ICT mining device and introducing demonstrational smart mining. This study introduces the application of an ICT device and safety system operation in the Jangseong underground mine of Korea Cement Co., Ltd. Currently, Jangseong mine combines two different kinds of 3D equipment including the handheld 3D scanner and multi-station that provides both the measurement and 3D scanning to perform a 3D measurement of the mine. Taken from the 3D measurement of the mine, it is now possible to identify any hazardous areas and abnormalities in different directions and analyze the safety of the crown pillar between two stopes in different level. Besides, the real-time location tracking and communications system have established highly efficient rescue and evacuation plans to effectively deal with any accidents in the mine.

• Geomechanics and Engineering
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• v.9 no.4
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2185-2191
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• 2007

The traditional sensor network is composed of the cable and the sensor of high price, when collecting a sensing data, there is a weak point which is not pliability. WSN uses the equipment of low price, it will be able to collect the data which is diverse from various node. In this paper we composed coal mining topology which used IEEE802.15.4 MAC in Korea Coal Corporation site. We proposed models for the mobility support of the work manager from the coal mining, we selected the optimum model through simulation experiments. When applying the WSN in the Korea Coal Corporation and other mines, this result can be used as a basis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.292-299
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• 2021

A form of data mining software, based on manufacturing-based IIoT environment with the development of IT technologies are increasingly growing. However, it is difficult to evaluate the software quality in the same form as general software due to the characteristics of the software of a manufacturing company that has a large amount of data that needs to be carried out with big data and data mining. In addition, in a manufacturing-based environment where heterogeneous equipment and software are mixed, it is difficult to perform quality judgment on software used by applying existing quality characteristics. Therefore, in this paper, the characteristics of the manufacturing base are investigated, and a software quality evaluation model suitable for it is developed and evaluated.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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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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• v.13 no.2
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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.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1119-1126
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• 2002

In this paper, we propose two predictive spatial data mining based on spatial statistics and apply for predicting the forest fire hazardous area. These are conditional probability and likelihood ratio methods. In these approaches, the prediction models and estimation procedures are depending un the basic quantitative relationships of spatial data sets relevant forest fire with respect to selected the past forest fire ignition areas. To make forest fire hazardous area prediction map using the two proposed methods and evaluate the performance of prediction power, we applied a FHR (Forest Fire Hazard Rate) and a PRC (Prediction Rate Curve) respectively. In comparison of the prediction power of the two proposed prediction model, the likelihood ratio method is mort powerful than conditional probability method. The proposed model for prediction of forest fire hazardous area would be helpful to increase the efficiency of forest fire management such as prevention of forest fire occurrence and effective placement of forest fire monitoring equipment and manpower.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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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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• v.38 no.4
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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.

• The Journal of Information Systems
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• v.26 no.2
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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.