• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.227-234
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• 2020

This paper introduces the state definition and diagnostic algorithm for autonomic control of manufacturing facilities. Smart factory systems through cyber-physical systems and digital twin technology are increasing the productivity and stability of existing manufacturing plants, which has become an issue recently. A Smart factory system is one of the key technologies that make up a smart factory system, to improve productivity, enable workers to make better decisions, and to control abnormal process flows. However, performing an autonomic control process based on large number of integrated plat data requires significant advance work. Therefore, in this paper, we define an abstracted facility state for manufacturing facility autonomic control and propose an algorithm to diagnose the current state. This makes the autonomic control process simpler by autonomic control based on the facility status rather then integrated facility data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.342-343
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• 2009

Paper factories use a large amount of water and same amount of wastewater is generated. It is important to purity and recycle the wastewater because of water shortages and water pollution. The existing water treatment facilities like precipitation process need large-scale equipment and wide space to purity the wastewater of paper factory. High gradient magnetic separation (HGMS) system has the merits to purity rapidly because of large voids at filter and to occupy small space. In this paper, two types of superconducting magnets were used for HGMS systems. Cryo-cooled Bi-2223 superconducting magnet system with 70 mm room temperature bore and 200 mm of height was prepared. Cryo-cooled Nb-Ti superconducting magnet with 100 mm room temperature bore and 600 mm of height was used for magnetic separator. Magnetic filters were designed by the analysis of magnetic field distribution at superconducting magnets. The various magnetic seeding reactions were investigated to increase the reactivity of coagulation. The effects of magnetic separation of wastewater were investigated as variation of magnetic field strength and flow rate of wastewater.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.05a
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• pp.4-4
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• 2009

Paper factories use a large amount of water and same amount of wastewater is generated. It is important to recycle the wastewater because of water shortages and water pollution. The existing water treatment facilities like precipitation process need large-scale equipment and wide space to purify the wastewater of paper factory. High gradient magnetic separation (HGMS) system has the merits to purify rapidly because of large voids at filter and to occupy small space. In this paper, two types of superconducting magnets were used for HGMS systems. Cryo-cooled Bi-2223 superconducting magnet system with 70 mm room temperature bore and 200 mm of height was prepared. Cryo-cooled Nb-Ti superconducting magnet with 100 mm room temperature bore and 600 mm of height was used for magnetic separator. Magnetic filters were designed by the analysis of magnetic field distribution at superconducting magnets. The various magnetic seeding reactions were investigated to increase the reactivity of coagulation. The effects of magnetic separation of wastewater were investigated as variation of magnetic field strength and flow rate of wastewater.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.218-223
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• 1993

In this paper, we present a full digital control scheme which controls currents and speed of the permanent magnet AC servo motor with large range of bandwidth and high performance. The current equations of the permanent magnet AC servo motor are linearized by feedback linearization technique. Both acceleration feedforward terms and IP controllers, whose gains are functions of motor speed, are used in order to control motor currents. In addition the phase delays in current control loops are compensated by placing phase lead-lag compensators after current commands, which make it possible to avoid high gains in the current controllers. Unity power factor can be achieved by the proposed current controller. Pulsewidth modulation is performed by way of the well-known comparison with a triangular carrier signals. The velocity controller is designed on the basis of the linearized model of the permanent magnet AC servo motor by the proposed current controller. The performance of the entire control system is analyzed in the presence of uncertainty in the motor parameters. The proposed control scheme is implemented using the digital signal processor-based controller composed of an Analog Device ADSP 2111 and a NEC78310. The pulsewidth modulation (PWM) signals are generated through a custom IC, SAMSUNG-PWM1, which has the outputs of current controllers as input. The experimental results show that the permanent magnet AC servo motor can be always driven with high dynamic performance by the proposed full digital control scheme of motor speed and motor current.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1832-1842
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• 2010

This paper introduces a new automatic processing system: "Contents Factory" for the mass production of contents. Through the contents factory, we provide an authoring environment to improve the usability and the efficiency in producing contents. The contents factory integrates recycling techniques for contents resources, contents development engines, authoring tools, and interfaces into a total processing system. Since it is multi-platform based including mobile devices as well as PCs, one can easily produce complete PC and mobile contents from raw resources. We produced an example, "Sejong square" via the contents factory in order to demonstrate its effectiveness and usability.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.59-71
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• 2020

The paper reports on a systematic literature review results concerning the smart factory research in Korea. 144 papers were identified from the articles published in Korean journals listed in the Korean citation index by keyword search related to smart factory. Bibliometric analyses were conducted by way of co-occurrence and network analysis using the VOSViewer. Automation, intelligence, and bigdata were identifed as three critical clusters of research while, operating systems, international policy and cases, concept analysis as other three clusters of research. Internet of Things turned out to be a key technology of smart factory linking all of these areas. Servitization studies were small in numbers but seemed to have a lot of potential. Security researches seemed to be lacking connections with other areas of studies. Results of this study can be used as a milestone for identifying future research issues in smart factories.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.69-75
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• 2018

The key technology of Industry 4.0, Smart factory is evaluated as the driving force of our economic development hereafter and a lot of researches have been established. Various entities including devices, products and managers exist in smart factory, but roles of these entities may be continuous or variable and can become extinct not long after. Existing methods for access control are not suitable to adapt to the variable environment. If we don't consider certain security level, important industrial data can be the targets of attacks. We need a new access control method satisfying desired level of efficiency and security without excessive system loads. In this paper, we propose a new RBAC-PAC which extend AC defined for PKC to the authority attribute of roles. We distribute PACs for roles through block chain method to provide the efficient access control. We verified that RBAC-PAC is more efficient in the smart factory with large number of entities which need a frequent permission update.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.189-196
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• 2011

The main issues of the researches are monitoring environment such as weather or temperature variation and natural accident, and sensor gateways which have mobile device, applications for mobile health care. In this paper, we propose the SFMS(Smart Factory Management System) that can effectively monitor and manage a green smart factory area based on M2M service and smart phone with android OS platform. The proposed system is performed based on the TinyOS-based IEEE 802.15.4 protocol stack. To validate system functionality, we built sensor network environments where were equipped with four application sensors such as Temp/Hum, PIR, door, and camera sensor. We also built and tested the SFMS system to provide a novel model for event detection systems with smart phone.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.667-676
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• 2002

Digital environment that is represented to Internet is displacing business way of industry and business achievement way with the fast speed being giving great change on life whole. Improve existent business process utilizing Internet and Web connection technology, information superhighway to tradition industrialist manufacturer and e-Transformation's propulsion that wish to maximize productivity and administration efficiency is spread vigorously. In this paper, administration efficiency raising of Web-based factory monitoring system to do monitoring when everywhere integrating operation present condition current point of time of discrete factories in inside and outside of the country by purpose design and implemented. That is, do to normalize system structure and achievement function, and administration data of Web-based, and design using VML (Unified Modeling Language) and take advantage of ASP (Active Server Pages) and implemented web function. Implemented Web-based factory monitoring system is applying two factory (Kl, K2) of K CO., LTD. tire operation division to caravan, and application result was evaluated by very efficient thing to grasp operation situation of whole factory synthetically.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.219-227
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• 2019

Manufacturing methods have been changed from labor-intensive methods to technological intensive methods centered on manufacturing facilities. As manufacturing facilities replace human labour, the importance of monitoring and managing manufacturing facilities is emphasized. In addition, Big Data technology has recently emerged as an important technology to discover new value from limited data. Therefore, changes in manufacturing industries have increased the need for smart factory that combines IoT, information and communication technologies, sensor data, and big data. In this paper, we present strategies for existing domestic manufacturing factory to becom big data based smart-factory through technologies for distributed storage and processing of manufacturing facility data in MongoDB in real time and visualization using R programming.