• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.76-76
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• 1995

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.421-421
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• 1994

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.36-48
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• 1994

• IE interfaces
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• v.15 no.1
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• pp.10-19
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• 2002

New trends such as electronic commerce, virtual organizations, e-business applications, etc. increase the dependence of production management on information software systems and contribute to the needs for global, distributed object systems. This paper presents a component based approach for production management systems under the multi-tier distributed information system architecture using UML(Unified Modeling Language), CORBA(Common Object Request Broker Architecture) and XML(eXtensible Markup Language) technologies, and propose rules for mapping a UML class diagram to a XML DTD (Document Type Definition). And we adapt it to the prototype system implementation. The components are implemented by CORBA and we use XML messages for the information exchange between components.

• Fisheries and Aquatic Sciences
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• v.12 no.2
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• pp.111-117
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• 2009

To develop sustainable management strategies for oyster farms in Pukman Bay, Korea, we estimated primary production using a numerical model. Because oysters are filter feeders, estimations of primary production (PP) are essential in developing management strategies. The daily PP ranged from 0.07 to 1.5 gC/$m^2$/d and showed significant spatial variations. The spatial distribution of PP was strongly associated with hydrodynamic features, and distinct patterns were observed in three different regions. In the inner bay, high PP was directly influenced by urban and agricultural sewage. The middle part of the bay had low PP, whereas PP in the outer area was high. PP was relatively low during the main oyster growth season, from late autumn to early winter. These findings represent important information for developing a management model for oyster farms in Pukman Bay.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.54-61
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• 2009

General manufacturing process of the manufacturing time and manufacturing process problems have a problem. In the past, in the manufacturing process the data by hand has been. Therefore, the production performance management information, and materials input, output information, equipment information of the failure of the management problems emerged. Through this research, improvements in real-time production information to collect distribution and overall productivity will increase the efficiency of the system. the production process to improve the quality of management, efficient production methods are presented. is a stable quality control. POP system The new building should be. This is the executive or administrative decisions support. It increases productivity, efficiency, and reduce production costs, increase product reliability. This will increase the company's reputation. This increases the competitiveness of enterprises. POP system toward the future with the new destroyer to prepare for our company. Collectively POP system build this research improves the reliability of the product. Improves the quality of customer service. The expansion of product sales is. increase the competitiveness of enterprises. companies should prepare for the future of the business.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

• Journal of Environmental Science International
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• v.30 no.3
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• pp.289-293
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• 2021

This study was conducted to investigate the distribution of duck production in duck housing as a function of the breeding period. The items in duck production distribution included body weight, feed intake, feed conversion ratio, and average duck production. All data were based on eight cycles (June and December, 2017; February, June, August, September, and November, 2018; February, 2019) at Farm Site 1 through 7. The most optimal results in the duck production distribution were observed at Site 1 for weight gain, feed intake, and feed efficiency. This could be explained by the fact that Site 1 was well managed in environmental improvement and sustainability. Based on these data, selective alternatives to improve duck production in duck farms are recommended as follows: first, proper management and recording of litter used as a flooring material are required, and second, continuous management such as temperature, relative humidity and ventilation is needed. Lastly, it is necessary to change duck facilities by introducing environmental management techniques. Furthermore, efforts to improve the overall facilities and management of duck breeding farms through additional field studies are needed in the future.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.159-165
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• 2023

The entire industry is increasing the use of big data analysis using artificial intelligence technology due to the Fourth Industrial Revolution. The value of big data is increasing, and the same is true of the production technology. However, small and medium -sized manufacturers with small size are difficult to use for work due to lack of data management ability, and it is difficult to enter smart factories. Therefore, to help small and medium -sized manufacturing companies use big data, we will predict the gross production time through machine learning. In previous studies, machine learning was conducted as a time and quantity factor for production, and the excellence of the ExtraTree Algorithm was confirmed by predicting gross product time. In this study, the worker's proficiency factors were added to the time and quantity factors necessary for production, and the prediction rate of LightGBM Algorithm knowing was the highest. The results of the study will help to enhance the company's competitiveness and enhance the competitiveness of the company by identifying the possibility of data utilization of the MES system and supporting systematic production schedule management.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.42-43
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• 2019

In-situ production of PC (precast concrete) members can reduce costs by about 14.5% -21.6% compared to in-plant production due to the reduction of transportation costs, factory profits and overhead costs. However, in-situ production of PC members presents a variety of risks, including member production and yard area securing, and lead time for production within the installation period. To solve this, it is necessary be able to analyze and control and monitor the risk factors that influence in-situ production for PC member. The purpose of this study is to develop a dynamic simulation model for in-situ production and erection integrated management for PC members. For this study, risk factor identification, causal loop diagram, and dynamic simulation model construction were performed sequentially. The results of this study will be used as a basis for developing a risk management model for PC in-situ production.