• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.143-146
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• 2005

Many data mining techniques have been proved useful in revealing important patterns from large data sets. Especially, data mining techniques play an important role in a customer data analysis in a financial industry and an electronic commerce. Also, there are many data mining related research papers in a semiconductor industry and an automotive industry. In addition, data mining techniques are applied to the bioinformatics area. To satisfy customers' various requirements, each industry should develop new processes with more accurate production criteria. Also, they spend more money to guarantee their products' quality. In this manner, we apply data mining techniques to the production-related data such as a test data, a field claim data, and POP (point of production) data in the automotive parts industry. Data collection and transformation techniques should be applied to enhance the analysis results. Also, we classify various types of manufacturing processes and proposed an analysis scheme according to the type of manufacturing process. As a result, we could find inter- or intra-process relationships and critical features to monitor the current status of the each process. Finally, it helps an industry to raise their profit and reduce their failure cost.

• Atmosphere
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• v.21 no.2
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• pp.173-183
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• 2011

Production of reanalysis data is important since it contributes to develop all fields of atmospheric sciences and to profit national economy. The developed countries such as USA, EU, and Japan have manufactured the global reanalysis data since the 1990s, but their data present a lack of detailed regional climates. For those who need to analyze the regional climate in/around Korea, a high-resolution reanalysis data should essentially be made. This study reviewed the existing reanalysis data and the applications, and the available observations for the data production. We also investigated the opinions and needs of the potential data users in Korea. We suggest the specifications of the data to have the domain of 55-5N, 80-150E (which includes Mongolia and most Southeast Asian countries), the spatial resolution of 10-20 km, and the period of most recent 30 years. With the specifications and climate models operated in KMA, this study argues that production of the reanalysis data with functional climate information is feasible in both technical and economic aspects. Finally, for successful data production, the framework of the future reanalysis data project was suggested.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.9
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• pp.1063-1070
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• 2011

The manufacturing execution system (MES) for product production handles different production processes according to the product characteristics and different types of data according to the process being considered. For efficiently providing the data pertaining to production equipment to production systems such as the MES, data collection through the equipment interface is required for obtaining the production data pertaining to field equipment. In this paper, a method is proposed for collecting the production data through the equipment interface in order to collect the various types of production-equipment data from the field. The proposed method is applied to a real manufacturing system to verify its efficiency. A more powerful MES can be constructed with a data acquisition system that acquires the status data at the shop-floor level.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.118-122
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• 2005

Data mining is the process of autonomously extracting useful information or knowledge from large data stores or sets. For analyzing data of manufacturing processes obtained from database using data mining, source data should be collected form production process and transformed to appropriate form. To extract those data from database, a computer program should be made for each database. This paper presents a program to extract easily data form database in industry. The advantage of this program is that user can extract data from all types of database and database table and interface with Teamcenter Manufacturing.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.485-489
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• 2018

For the construction of smart factory that are part of the Fourth Industrial Revolution, data from the production environments and production machines should be collected, analyzed, and feedback should be given to predict when failures take place or parts should be replaced. For this purpose, a system that monitors the production environments and the status of the production machines are required. In this paper, the monitoring system for mobile devices and PC is implemented by collecting environmental data from production sites and sensor data of production machine using LoRa, a low-power wireless communication technology. On the mobile devices, production environments and vibration data can be displayed in real time. In PC monitoring program, sensor data can be displayed graphically to check standard deviation and data variation. The implemented system is used to collect data such as temperature, humidity, and atmospheric pressure of the production environment, and vibration data of production machines.

• IE interfaces
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• v.15 no.1
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• pp.26-39
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• 2002

Two key data areas of the integrated production database in computer-integrated manufacturing (CIM) systems are the product structure in the forms of bills of material(BOM) and the process structure in the forms of routings. The great majority of existing information systems regard the BOM and routing as two separate data entities, possibly with some degree of cross-referencing. This paper proposes new information structure called the bills of material and routings(BMR) that logically integrates the BOM and routings for the CIM systems in ship production. The characteristics of ship production are described as: 1) make-to-order production type, 2) combined manufacturing principles (workshop production and construction site production), 3) significant overlapping of design, planning and manufacturing, 4) very long order throughput time, 5) complex product structure and production process. The proposed BMR systematically manages ail parts and operations data needed ship production considering characteristics of ship production. Also, the BMR situated on the integrated production database more efficiently supports interface between engineering and production functions, and integrates a wide variety of functions within production such as production planning, process planning, operation scheduling, material planning, costing etc., and simplifies information flow between sub-systems in CIM systems.

• Nuclear Engineering and Technology
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• v.37 no.1
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• pp.11-24
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• 2005

A very important feature in the development of nuclear technology has been and will continue to be the flow of information from nuclear data production to the various applications fields in nuclear technology. Both, nuclear data and this communications flow are defined in this paper. Nuclear data result from specific technical activities including their production, evaluation, processing, verification, validation and applications. These activities are described, focusing on nuclear reactor calculations. Mathematical definitions of different types of nuclear data are introduced, and international forums involved in nuclear data activities are listed. Electronic links to various sources of information available on the web are specified, whenever possible.

• Journal of the Korean Institute of Gas
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• v.20 no.3
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• pp.1-11
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• 2016

Production data from hydraulically fractured well in coalbed methane (CBM) reservoirs was analyzed using decl ine curve analysis (DCA), flow regime analysis, and flowing material balance to forecast the production performance and to determine estimated ultimate recovery (EUR) and timing for applying the DCA. To generate synthetic production data, reservoir models were built based on the CBM propertie of the Appalachian Basin, USA. Production data analysis shows that the transient flow (TF) occurs for 6~16 years and then the boundary dominated flow (BDF) was reached. In the TF period, it is impossible to forecast the production performance due to the significant errors between predicted data and synthetic data. The prediction can be conducted using the production data of more than a year after reached BDF with EUR error of approximately 5%.

• Journal of the Korean Institute of Gas
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• v.20 no.1
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• pp.13-22
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• 2016

This paper presents development of an appropriate procedure and flow chart to analyze shale gas production data obtained from a multi-fractured horizontal well according to flow characteristics in order to calculate an estimated ultimate recovery. Also, the technical considerations were proposed when a rate transient analysis was performed with field production data occurred to only $1^{st}$ transient flow. If production data show the $1^{st}$ transient flow from log-log and square root time plot analysis, production forecasting must be performed by applying different method as before and after of the end of $1^{st}$ linear flow. It is estimated by an area of stimulated reservoir volume which can be calculated from analysis results of micro-seismic data. If there are no bottomhole pressure data or micro-seismic data, an empirical decline curve method can be used to forecast production performance. If production period is relatively short, an accuracy of production data analysis could be improved by analyzing except the early production data, if it is necessary, after evaluating appropriation with near well data. Also, because over- or under-estimation for stimulated reservoir volume could take place according to analysis method or analyzer's own mind, it is necessary to recalculate it with fracture modeling, reservoir simulation and rate transient analysis, if it is necessary, after adequacy evaluation for fracture stage, injection volume of fracture fluid and productivity of producers.

• Journal of Microbiology and Biotechnology
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• v.18 no.6
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• pp.1130-1135
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• 2008

The effect of pH on anaerobic hydrogen production was investigated under various pH conditions ranging from pH 3 to 10. When the modified Gompertz equation was applied to the statistical analysis of the experimental data, the hydrogen production potential and specific hydrogen production rate at pH 5 were 1,182 ml and 112.5 ml/g biomass-h, respectively. In this experiment, the maximum theoretical hydrogen conversion ratio was 22.56%. The Haldane equation model was used to find the optimum pH for hydrogen production and the maximum specific hydrogen production rate. The optimum pH predicted by this model is 5.5 and the maximum specific hydrogen production rate is 119.6 ml/g VSS-h. These data fit well with the experimented data($r^2=0.98$).