• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.257-270
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• 2022

In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.267-274
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• 2024

In this paper, we investigated the number of domestic patent applications by year, the number of domestic patent disclosures by year, and the number of domestic registrations by year regarding smart factories. The number of patent applications by applicant type was investigated. Based on the patents studied, it was found that the IPC appearing in the most patents was G05B 19/418. In addition, through social network analysis of smart factory patented IPCs, it was found that G05B 19/418 was the IPC with the highest degree of centrality. From the above, if the IPC of the core technology of the patent submitted for smart factory is G05B 19/418, the technology combined with G05B 23/02, that is, the technology combining "factory control" and "monitoring" is the most patented. When the IPC of the core technology was G06Q 50/04, it was confirmed that the technology combined with G06Q 50/10, that is, the technology combining "manufacturing" and "service" was the most applied for patents. Through this, it was found that in order to apply for a patent for a smart factory, it would be necessary to file a patent application that takes into account the connectivity between IPCs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.237-244
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• 2018

The Smart Factory level of manufacturing factories of SMEs now lacks a system for grasping the accurate inventory amount associated with inventory movements in managing warehouses at the basic level. Also, it is difficult to manage accurate materials for loss of data due to worker manual work and production method due to experience. In order to solve this problem, in this paper, automatic acquisition of inventory to minimize manual work to grasp workers' Inventory and improve automation is done. In the smart warehouse management system using the IoT-based autonomous mobile module, the autonomous mobile module acquires the data of the inventory storage while moving through the line. In order to grasp the material of the Inventory storage, The Camera module recognizes the name of the inventory storage. And Then, If output matches, the data measured by the sensor is transferred to the server. This data can be processed, saved in a database, and real-time inventory quantity and location can be grasped in a web-based monitoring environment for administrators. The Real-time Automatic Inventory (RAIC) systems is reduce manual tasks and expect the effects of automated inventory management systems.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.177-182
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• 2017

As major ICT technologies such as IoT, cloud computing, and Big Data are being applied to manufacturing, smart factories are beginning to be built. The key of smart factory implementation is the ability to acquire and analyze data of the factory. Therefore, the need for a big data analysis platform is increasing. The purpose of this study is to construct a platform for big data analysis of manufacturing process and propose integrated method for analysis. The proposed platform is a RHadoop-based structure that integrates analysis tool R and Hadoop to distribute a large amount of datasets. It can store and analyze big data collected in the unit process and factory in the automation system directly in HBase, and it has overcome the limitations of RDB - based analysis. Such a platform should be developed in consideration of the unit process suitability for smart factories, and it is expected to be a guide to building IoT platforms for SMEs that intend to introduce smart factories into the manufacturing process.

• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.1-14
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• 2018

The 4th Industrial Revolution has been rapidly changing the environment of all industries and the new technologies as included in the 4th Industrial Revolution has taken the lead in this change. Domestic SME need to change according to the 4th Industrial Revolution. Specially, it is necessary to introduce smart factories to the SME. Thus, this study suggests strategies for successful introduction of smart factories to SME through SWOT analysis about the situation of the SME. As strategies for utilizing its strengths, first, it is an activation through superior competitiveness. Second, the utilization of excellent technology and information is considered. Third, it is suggested to utilize global network-based environment. The strategies for making up for weakness are provided as follows. First, it is suggested to raise awareness of information security. Second, it is considered to establish technical standardization for the construction of evaluation system. Third, the promotion of manpower to secure professional manpower is suggested. The implication of this study is that it suggests the necessity of smart factory to understand and prepare for effective strategies for SME and various external strategies for the fourth industrial revolution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.135-141
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• 2019

South Korea's smart factory drive is at a very important point. While large-scale funds and manpower are invested to secure international competitiveness and revitalize manufacturing, software investments that are only approached by IT suppliers may end up creating systems that do not meet the actual conditions of the field. As a result, there are problems in the manufacturing sector that can cause consumers to feel the fatigue of innovation in the manufacturing sector. SMEs should check from scratch and establish a gradual integration system so that they can reduce failures in IT investments and implement OT-oriented smart factories that are well utilized in the field. To this end, a process visualization solution was proposed and a step-by-step innovation was proposed at the basic level and the ICT unapplied level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.742-743
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• 2017

The smart factory market is expected to show high growth rate in the future, supported by demand for manufacturing innovation in order to overcome structural low growth. Especially in the future manufacturing industry, robots are combined with IT, becoming the most important core technology. In this paper, we proposed and implemented state information classification method for IoT-based robot control in smart manufacturing environment.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.509-515
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• 2022

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.429-438
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• 2023

Recently, demand for smart factories is increasing in response to the era of the 4th industrial revolution. Smart factory is basically a manufacturing industry based on massive data, which requires IT services for processing a lot of data, which is accelerating the construction of data centers. Data center computing equipment requires a different approach from the cooling technology of general facilities in terms of heat load and usage time. This study investigates the factors to be reviewed in the recent data center cooling system design and technological change trends, compares and reviews various technological methods for facility configuration of case companies, derives the design decision process, and draws up a conceptual design corresponding to the conclusion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.650-661
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• 2020

The digital transformation of the 4th industrial revolution is leading to changes and innovations in the global economy. Various countries are focusing on reviving their manufacturing industries and economic recovery through smart factories. The purpose of this study is to empirically identify technological determinants for the successful implementation of the smart factory and to verify teose effects on manufacturing operations and the firms' operational/environmental performances. Five factors, including sensor network, platform technology, information system, intelligent automation, and safety, were defined as core technologies. The SEM analysis results of 157 small and medium-sized manufacturing firms that have implemented smart factories are as follows. First, sensor network, platform technology, and information system had significant effects on smart manufacturing operations. Second, smart manufacturing operations have improved firm performance. This study is valuable in that it has confirmed the effectiveness of government-funded projects and systemized key technologies for implementing smart factories. Meanwhile, it is helpful for practitioners to support an efficient and effective decision-making for the new adoption.