• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.155-160
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• 2022

In recent years, Unreal Engine has been increasingly included in the animation process produced in the studio. In this case, there will be more than one of main software, and it is very important to accurately transfer data between the software and Unreal Engine. In animation data, not only the animation data of the character but also the animation data of objects interacting with the character must be individually produced and transferred. Most of the objects that interact with the character have a condition of constraints with the part of character. In this paper, I tried to stipulate the production process for extracting animation data of constrained objects, and to analyze why users experience difficulties due to the complexity of the regulations in the process of executing them. And based on the flowchart prescribed for user convenience, I created a program using a Python script to prove the user's convenience. Finally, by comparing the results generated according to the manual flowchart with the results generated through the script command, it was found that the data were consistent.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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• pp.531-539
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• 2009

The environment of automobile industry in the world is rapidly changing. It is changing of high oil price, technology, environment and construction of competition by newly rising an economic district. Automobile company is focusing on three issue because they want to reinforce competition of automobile industry in the world. That is innovation of production profit management through quality management and Lean. Chance of success is separated in R&D, providing distribution, manufacture, distribution, selling in automobile industry. Emphasis on development process, distribution process, manufacture process, circulation and selling process for strengthening the competitiveness and guarantee. In this thesis, we try to analysis the data set period of automobile production by using survival analysis. While using mean comparison of general statistics commit mistakes, survival analysis can used for including censored data in order to heighten analysis efficiency.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.1-8
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• 2021

This study proposes a systems engineering approach for the development of an advanced planning & scheduling (APS) system for a cosmetic case manufacturing factory. The APS system makes production plans and schedules based on the injection process, which consists of 27 plastic injection machines in parallel to control recommended inventory of products. The system uses machine operation/failure information and defective product/work-in-process tracking information to support intelligent scheduling. Furthermore, a genetic algorithm model is applied to handle the complexity of heuristic rules and machine/quality constraints in this process. As a result of the development, the recommended inventory compliance rate is improved by scheduling the 30-day production plan for 15 main products.

• 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 Environmental Science International
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• v.9 no.1
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• pp.75-80
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• 2000

Kinetic data for the acid phase anaerobic digestion were presented in this study and the constants were determined with acid production rate and gas production rate. Process models based on continuous culture theory were used to describe the characteristics of the acid forming microorganisms and to enable further development toward utilization of the process in a more rational manner. Acid phase digestion can be separated with appropriate manipulation of hydraulic retention time in anaerobic digestion. Kinetic analysis of data from the various hydraulic retention times using a phase specific model obtained form the acid phase indicated maximum specific growth rate of 0.40/h, saturation constant of 2,000mgCOD.$\ell$, yield coefficient of 0.35 mgVSS/msCOD utilized and decay constant of 0.04/h for the acid production rate. Similar analysis of data for the gas production rate indicated maximum specific growth rate of 0.003/h, saturation constant of 2,200mgCOD/$\ell$, yield coefficient of 0.035 mgVSS/mgCOD utilized and decay constant of 0.06/h.

• The Journal of Information Systems
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• v.26 no.2
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• pp.143-164
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• 2017

Purpose The purpose of this study is to investigate to investigate the effects of cloud system on the efficiency improvement and cost-saving of production processes. It also tries to provide small- and medium-sized companies and IT practitioners with a practical guideline for a successful implementation of could systems. Design/methodology/approach This study was conducted by observing and analyzing a case of implementing a cloud system at a small-sized company having multiple job sites in terms of the improvement in data-sharing efficiency and cost-saving of production processes. Findings This study found that cloud system was an effective way of sharing data between and among production processes of geographically scattered job sites and thus, helped the company to remedy problems of work schedule and load-balance along sequential production processes. Cloud system also allowed the company to reduce the number of visits made by 3-inspectors to four job sites by 75% and the personnel cost related to inspectors' site visit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1082-1086
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• 2007

This research has a purpose of constructing the data monitoring system that makes two-tier work state in the brick production factory to unification by reusing cinder. Monitoring system automatically manages data by using data managing processes such as a state managing process, a location managing process, a badness managing process, a circumstances managing process. In this research, the data management monitoring system manufactures state information of each processes received from RFID and transmits them to data monitoring system. Analyzed data through this system reuses the cinder, so it can effectively manage the production process of the factory which produces bricks through processing automation, faulty-ratio minimization, real-time monitoring and loading managing.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• 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.