• 연구논문집
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• s.27
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• pp.167-174
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• 1997

Point of Production/Manufacturing Execution Systems are an essential component of operations in today's competitive business environments, which require greater production efficiency and effectiveness. POP/MES focuses on the valuing-adding processes, helping to reduce manufacturing cycle time, improve product quality, reduce WIP, reduce or eliminate paperwork between shifts, reduce lead time and empowering plant operations staff. In this paper, we implement POP/MES to manage real-time plant floor data which is gathered by I/O server into database management system. I/O server is a software allows data exchange between factory real-time database and several hardware devices such as PLC, DCS, robot and sensor through ethernet TCP/IP protocol.

• Phonetics and Speech Sciences
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• v.7 no.2
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• pp.119-129
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• 2015

This paper investigates the status of the merger between the mid front unrounded vowels ㅔ[e] and ㅐ[${\varepsilon}$] in contemporary Korean. Our analysis is based on a balanced corpus of production and perception data from young subjects from three dialectal areas (Seoul, Daegu and Gwangju). Except for expected gender differences, the production data display no difference in the realization of these vowels, in any of the dialects. The perception data, while mostly in line with the production results, show that Seoul females tend to better discriminate the two vowels in terms of perceived height: vowels with a lower F1 are more likely to be categorized as ㅔ by this group. We then investigate the possible causes of this merger: based on an empirical study of transcribed spoken Korean, we show that the pair of vowels ㅔ/ㅐ has a very low functional load. We argue that this factor, together with the phonetic similarity of the two vowels, may have been responsible for the observed merger.

• Korean Management Science Review
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• v.24 no.1
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• pp.91-111
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• 2007

In this paper an effective two-phase approach adopting modified p-median mathematical model is proposed for grouping machines and parts in cellular manufacturing(CM). Unlike the conventional methods allowing machines and parts to be improperly assigned to cells and families, the proposed approach seeks to find the proper block diagonal solution where all the machines and parts are properly assigned to their most associated cells and families in term of the actual machine processing and part moves. Phase 1 uses the modified p-median formulation adopting new inter-machine similarity coefficient based on the non-binary production data-based part-machine incidence matrix(PMIM) that reflects both the operation sequences and production volumes for the parts to find machine cells. Phase 2 apollos iterative reassignment procedure to minimize inter-cell part moves and maximize within-cell machine utilization by reassigning improperly assigned machines and parts to their most associated cells and families. Computational experience with the data sets available on literature shows the proposed approach yields good-quality proper block diagonal solution.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.207-209
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• 2003

Quantifying crop production is one of the most important applications of remote sensing in which the temporal and up-to-date data can play very important role in avoiding any immediate insufficiency in agricultural production. A combination of climatic data and biophysical parameters derived from Landsat7 ETM+ was used to develop a mathematical model for wheat yield forecast in different geographically wide Wheat growing districts in Egypt. Leaf Area Index (LAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) with temperature were used in the modeling. The model includes three sub-models representing the correlation between the reported yield and each individual variable. Simulation results using district statistics showed high accuracy of the derived correlations to estimate wheat production with a percentage standard error (%S.E.) of 1.5% in El- Qualyobia district and average (%S.E.) of 7% for the whole wheat areas.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.447-449
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• 2003

Remotely sensed data can be used to estimate biomass production using methodologies relating vegetation indices to light absorption or to leaf photosynthetic capacity. The considerations of both light absorption and photosynthetic capacity in remote sensing-based modeling to estimate biomass production or NPP was introduced based upon Monteith model NPP is one of a evaluation of land degradation. NPP was estimated from annual maximum NDVI by MODIS data. It was known that NPP of the grassland that except the forest and the farming ground was distributed between 50-200g /m2.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.600-601
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• 2015

Both the importance and process of estimating Nuclear-power plant construction time and cost have increased in significance as energy user costs themselves have become more significant. In estimating construction time, few parameters are more significant than work item production rates and factors significantly affecting the rates. A standardized data collection tool was used to acquire a total of 401 data points from a S Nuclear-power plant project, for selected critical works: form-work, rebar-work, and concrete-pouring. With the data, several hypothesized drivers of the man-hour production rates and crew-day production rates were also analyzed. Findings from this study will enable industry professionals to enhance accuracy of time and cost estimation for nuclear power plant construction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• The International Journal of Costume Culture
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• v.3 no.3
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• pp.235-245
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• 2000

The purposes of this study were 1) to investigate usage level of production strategies based on group of production environment, 2) to investigate usage level of production systems based on group of production strategy, and 3) to analyze each of company performance based on group of production strategy and system. For this study, the questionnaires were administered to 215 apparel manufactures in metropolitan area from Feb. to Mar. 1998. Employing a sample of 201, data were analyzed by factor analysis, descriptive statistics, cluster analysis, discriminant analysis, and multivariate analysis of variance. The following are the results of this study. 1. Concerning production strategy due to group of production environment, the stable group and the complicated group prefer to rice/quality centered strategy but the level of usage for strategies is so pretty that it is not significant to carry out them. 2. Concerning production system due to group of production strategy, the workers centered group is occupied high in the price/quality centered group & the complex group. And also the product centered system is occupied high in the flexibility centered group. 3. Concerning company performance due to group of production strategy and system, the price/quality centered group holds low position of performance comparing to another groups. And the performance of the managers centered group is higher than that of the workers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.874-880
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• 2018

3D modeling is extensively used in the field of architecture, machinery and contents production such as movies. Modeling is a time-consuming task. In order to compensate for these drawbacks, attempts have recently been made to reduce the production period by applying 3D scanning technology. 3D scanning for small objects can be done directly with laser or optics, but large buildings and sculptures require expensive equipment, which makes it difficult to acquire data directly. In this study, 3D modeling data for a large object is acquired using photometry with using drones to acquire the image data. The maintenance method for uniform spacing between the sculpture and the drone, the measurement method for the flight line were presented. In addition, we presented a production environment that can utilize the obtained 3D point cloud data for animation and a rendered animation result to find ways to make it in various environments.

• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.116-122
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• 2019

In recent years, small and medium-sized businesses are rapidly changing to an industrial structure where process/quality/energy data aggregates can be automatically or real-time to achieve global competitiveness. In particular, real-time information analysis produced in the production process of small businesses is evolving into a new process process that analyzes, predicts, prescribes and implements significant performance of small businesses. In this paper, we propose a platform-building model that can transform the automated production information system of small businesses into big data so that they can upgrade data that is generated by small businesses. The proposed model has the capability to support operational efficiency (consulting and training) and strategic decision making of small businesses by utilizing a variety of data on the basic information of products produced by small businesses for data collection by smart SMEs. In addition, the proposed model is characterized by close cooperation between small and medium-sized businesses with different regional characteristics and areas of information sharing and system linkage.