• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1467-1482
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• 2017

Recently, Interests on The Fourth Industrial Revolution has been increased. In the manufacturing sector, the introduction of Smart Factory, which automates and intelligent all stages of manufacturing based on Cyber Physical System (CPS) technology, is spreading. The complexity and uncertainty of smart factories are likely to cause unexpected problems, which can lead to manufacturing process interruptions, malfunctions, and leakage of important information to the enterprise. It is emphasized that there is a need to perform systematic management by analyzing the threats to the Smart Factory. Therefore, this paper systematically identifies the threats using the STRIDE threat modeling technique using the data flow diagram of the overall production process procedure of Smart Factory. Then, using the Attack Tree, we analyze the risks and ultimately derive a checklist. The checklist provides quantitative data that can be used for future safety verification and security guideline production of Smart Factory.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.124-133
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• 2021

Smart factory is a future factory that collects, analyzes, and monitors various data in real time by attaching sensors to equipment in the factory. In a smart factory, it is very important to inquire and generate the status and history of equipment in real time, and the emergence of various smart devices enables this to be performed more efficiently. This paper proposes a multi device-based system that can create, search, and delete equipment status and history in real time. The proposed system uses the Android system and the smart glass system at the same time in consideration of the special environment of the factory. The smart glass system uses a QR code for equipment recognition and provides a more efficient work environment by using a voice recognition function. We designed a system structure for real time equipment monitoring based on multi devices, and we show practicality by implementing and Android system, a smart glass system, and a web application server.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.803-804
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• 2016

With the advent of Germany's Industry 4.0, research of smart factory to applying the ICT in manufacturing industries is in progress. But the current system controlled equipment using the data declared in the embedded systems. In this paper, we proposed equipment control method to implement smart factory based on IoT. This method is create D/B table of data declared in equipment. and equipment shall call all of control unit parameters. When using the present method, it is possible to efficiently control the number of equipment as less network resource. Also It can operating a factory efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2677-2682
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• 2015

Smart factory has the function of integrated management of production process management, logistics management as a intelligent factory, it is also emerging as the core of new industry which converges ICT and manufacturing business. We suggested Smart factory logistics management system which embedded position tracking technology and the system converges ICT and IoT. This suggested system can manage all the processes from production to release by tracking route and position based on signal strength of bluetooth 4.0 beacon tag. For the more, we will expect to apply to the various type of factory environments like detachable installation, optimized management using sensor.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.780-790
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• 2015

Studies for a plants factory is progressing for cultivating various plants by the needs of the times and industry around world. However most studies is carried out only in lab sized plants factory. It does not consider an economic feasibility. The study for a large scale plants factory is very required to get an economic gain. In this paper we has been studying a smart farm factory based on ICT using the hydroponics ginseng. The smart farm factory is to extend a concept of the general plants factory to full automated factory. The factory can collect the information about growing of plants and automate operating and management of factory like the existing plants factory. Also it is the total plants factory management system, which analyzes the collected information for optimized growth and development of plants and applies the result to the system back.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.551-567
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• 2021

Purpose: The purpose of this paper is to present implications by analyzing research trends on smart factories by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on smart factories. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "SMART FACTORY" and "Smart Factory" as search terms, and the titles and Korean abstracts were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, 739 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; Smart factory research slowed down from 2005 to 2014, but until 2019, research increased rapidly. According to the analysis by fields, smart factories were studied in the order of engineering, social science, and complex science. There were many 'engineering' fields in the early stages of smart factories, and research was expanded to 'social science'. In particular, since 2015, it has been studied in various disciplines such as 'complex studies'. Overall, in keyword analysis, the keywords such as 'technology', 'data', and 'analysis' are most likely to appear, and it was analyzed that there were some differences by fields and years. Conclusion: Government support and expert support for smart factories should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to smart factories. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.65-72
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• 2022

With the mark of the fourth industrial revolution, the smart factory is evolving into a new future manufacturing plant. As a human-machine-interactive tool, augmented reality (AR) helps workers acquire the proficiency needed in smart factories. The valuable data displayed on the AR device must be delivered intuitively to users. Current AR applications used in smart factories lack user movement calibration, and visual fiducial markers for position correction are detected only nearby. This paper demonstrates a marker-based object detection using perspective projection to adjust augmented content while maintaining the user's original perspective with displacement. A new angle, location, and scaling values for the AR content can be calculated by comparing equivalent marker positions in two images. Two experiments were conducted to verify the implementation of the algorithm and its practicality in the smart factory. The markers were well-detected in both experiments, and the applicability in smart factories was verified by presenting appropriate displacement values for AR contents according to various movements.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.109-121
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• 2020

As a decrease in labor became a serious issue in the manufacturing industry, smart factory technology, which combines IT and the manufacturing business, began to attract attention as a solution. In this study, we have designed and implemented a real-time remote management system for smart factories, which is connected to an IoT sensor and gateway, for plastic manufacturing plants. By implementing the REST API in which an IoT sensor and smart gateway can communicate, the system enabled the data measured from the IoT sensor and equipment status data to the real-time monitoring system through the gateway. Also, a web-based management dashboard enabled remote monitoring and control of the equipment and raw material processing status. A comparative analysis experiment was conducted on the suggested system for the difference in processing speed based on equipment and measurement data number change. The experiment confirmed that saving equipment measurement data using cache mechanisim offered faster processing speed. Through the result our works can provide the basic framework to factory which need implement remote management system.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.9-18
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• 2020

As the 4^th industrial revolution has been an emerging issue, the government and industry has paid increasing interest to smart factory. The Korean government has made efforts to establish smart manufacturing capabilities of small-to-medium sized firms by providing supports for smart factory. However, the effectiveness of the supports and satisfaction of firms have hardly been analyzed. This study aims to analyze firms' satisfaction by attributes of policy suuports for smart factory and identify priorities for government supports. The results show that 8 out of 11 attributes were one-dimensional and 3 were attractive attributes. Among the 11 attributes, funding support was the top priority. The attributes such as dispatching external experts, consulting for sophistication of smart-factory, and consulting for maintenance and repair were also high priorities. These results imply that firms prefer supports for maintenance and sophistication to adoption or initial establishment of smart factory.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.49-58
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• 2019

In this paper, we propose an edge cloud platform architecture for implementing smart factory. The edge cloud platform is one of edge computing architecture which is mainly focusing on the efficient computing between IoT devices and central cloud. So far, edge computing has put emphasis on reducing latency, bandwidth and computing cost in areas like smart homes and self-driving cars. On the other hand, in this paper, we suggest not only common functional architecture of edge system but also light weight cloud based architecture to apply to the specialized requirements of smart factory. Cloud based edge architecture has many advantages in terms of scalability and reliability of resources and operation of various independent edge functions compare to typical edge system architecture. To make sure the availability of edge cloud platform in smart factory, we also analyze requirements of smart factory edge. We redefine requirements from a 4M1E(man, machine, material, method, element) perspective which are essentially needed to be digitalized and intelligent for physical operation of smart factory. Based on these requirements, we suggest layered(IoT Gateway, Edge Cloud, Central Cloud) application and data architecture. we also propose edge cloud platform architecture using lightweight container virtualization technology. Finally, we validate its implementation effects with case study. we apply proposed edge cloud architecture to the real manufacturing process and compare to existing equipment engineering system. As a result, we prove that the response performance of the proposed approach was improved by 84 to 92% better than existing method.