• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.123-128
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• 2024

Major countries are trying to expand the construction of smart factories by introducing ICT such as the Internet of Things, cloud, and big data into the manufacturing sector to secure national-level manufacturing competitiveness in the era of the 4th industrial revolution. In addition, Germany is pushing for Industry 4.0 to build a fully automatic production system through the Internet of Things, and China is pushing for the expansion of smart factories to enhance the country's industrial competitiveness through Made in China 2025, Japan's intelligent manufacturing system, and the Korean government's manufacturing innovation 3.0. In this study, considering the increasing security connectivity of smart factories, we would like to identify security threats in the external connection part of smart factories and suggest security enhancement measures based on domestic and international standard security models to respond to the identified security threats. Eventually the proposed method can be applied by accurately identifying the smart factory security status, diagnosing vulnerabilities, establishing appropriate improvement plans, and expanding security strategies to respond to security threats.

• 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.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.733-739
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• 2019

Water level measurement is highly demanding in IoT monitoring areas such as smart factory, smart farm, and smart fish farm. However, existing water level indicators are limited to be used in industrial fields as commercial products due to the high cost of sensors and the complexity of algorithms used. In order to solve these problems, our paper proposed methods using an infrared distance sensor as well as a hall sensor for the water level measurement, both of which are contactless smart sensors. Data errors caused by the inaccuracy of existing sensors were decreased by applying new simple structures so that versatility is enhanced. The performance of our method was validated using experiments based on simulations. We expect that our new water depth indicator can be extended to a general-purpose water level monitoring system based on IoT technology.

• Journal of IKEEE
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• v.23 no.3
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• pp.1092-1095
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• 2019

In this paper, we propose the development of an embedded board for construction of smart factory. The proposed embedded board for construction of smart factory consists of main module, ADC module, I/O module. Main module is a main calculating device which includes communication pard that allows interface with external device with using industrial protocol and is ported operating system makes board operating into. ADC module takes part in transferring digital signal has converted from electrical signal to the main module from the external sensor which is installed on the field. I/O module is an input and output module which transfers to the main module about a status, alarm, command signal of field device and it has a function that blocks external noises from field device with isolation circuit into it. In order to evaluate the performance of the proposed embedded board for construction of smart factory, it has been tested by an authorized testing institute. As a result, quantity of interacting protocol was 5, speed of hardware clock synchronization was under 10us and operating time of battery without source power was over 8 hours. It produced the same result as the world's highest level.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.165-178
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• 2019

In an environment transformed by smart factories, measuring the current level of the manufacturing system, deriving improvement targets and tasks and increasing the level of manufacturing competitiveness become the basic activities of the company. However, research on the component analysis and maturity assessment to ensure the future competitiveness of the company is in progress and in the early stages. This study analyzed the existing research on various models, development process, and framework for manufacturing system. In addition, we designed a structural model by deriving the components of future manufacturing system through smart factory related maturity assessment studies. We designed a meta-model that includes an assesment model and a transformation model, and derived the framework development process to propose an integrated framework for the maturity assessment of the future manufacturing system. We verified it by applying it into an actual evaluation project of smart factory.

• Industry Promotion Research
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• v.4 no.2
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• pp.9-18
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• 2019

This study investigated the relationship between ICT environment and business performance. In the case of Korea's major industries, large corporations have already established and operate a considerable level of smart factories, leading the global market. However, SMEs, which account for 95% of the total companies, are not able to build smart factories themselves. Smart factory construction The total number of government-supported enterprises is 4.891 companies (3,984 companies, 907 companies in construction) 2.9% of factories and 97.1% (166,344 companies) There is a big problem to be improved. The result of this study is that the first research objective of this study, which suggests the theoretical system that the will of the manager is most important for the successful establishment of the smart factory, which is part of the corporate innovation to meet the rapidly changing environment. Second, it can be seen that financing for building a smart factory is a key factor in building a smart factory, as well as funding itself. Third, it was found that besides its own technology, technology support for government and external technology consulting support are very important for smart construction. Fourth, organizational participation of internal organizers showed that cooperative and positive positive participation is also a factor of success. As a follow-up study, we analyzed the cause of the company's operation, analyzed the cause of the problem with the 4M1E technique, developed the countermeasures, and compared it before and after the improvement, standardized the improvement and needed further study. It is meaningful that the study provided basic data for building a smart factory through the analysis of the relationship between the ICT environment and business performance of the company.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.199-211
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• 2021

This study analyzed the factors that influence the domestic SMEs that have introduced smart factories on their intention to accept at a higher level for qualitative advancement. 375 copies collected through an online survey were analyzed using SPSS and AMOS with UTAUT and the extended two-stage information system continuous model. Performance expectancy, effort expectancy, social influence, and facilitating conditions have a statistically significant effect on user satisfaction and user satisfaction and CEO's will have an effect on the intention to accept the advancement. However, the suppliers' technology didn't have a direct effect on the advancement acceptance intention and user satisfaction has a mediating effect between performance expectancy, effort expectancy, social influence, facilitating conditions and the advancement acceptance intention. SME's advancement for smart factory, it is important to improve the satisfaction level and the CEO's will to become smart.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1001-1010
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• 2021

Smart factories are complex systems which combine latest information technology (IT) with operation technology (OT). A smart factory aims to provide manufacturing capacity improvement, customized production, and resource reduction with these complex technologies. Although the smart factory is able to increase the efficiency through the technologies, the security level of the whole factory is low due to the vulnerability transfer from IT. In addition, the response and restoration of the business continuity plan are insufficient in case of damage due to the absence of factory security experts. The cope with the such problems, we propose an information security practice content for analyzing the damage by generating ransomware attacks in a digital twin-based smart factory similar to the real world. In our information security content, we introduce our conversion technique of physical devices into virtual machines or simulation models to build a practical environment for the digital twin. This content generates two types of the ransomware attacks according to a defined scenario in the digital twin. When the two generated attacks are successfully completed, at least 8 and 5 of the 23 virtual elements are take damage, respectively. Thus, our proposed content directly identifies the damage caused by the generation of two types of ransomware in the virtual world' smart factory.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.45-53
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• 2024

A Smart factories are systems that enable quick response to customer demands, reduce defect rates, and maximize productivity. They have evolved from manual labor-intensive processes to automation and now to cyber-physical systems with the help of information and communication technology. However, many small and medium-sized enterprises (SMEs) are still unable to implement even the initial stages of smart factories due to various environmental and economic constraints. Additionally, there is a lack of awareness and understanding of the concept of smart factories. To address this issue, the Cooperation-based Smart Factory Construction Support Project was launched. This project is a differentiated support project that provides customized programs based on the size and level of the company. Research has been conducted to analyze the impact of this project on participating and non-participating companies. The study aims to determine the effectiveness of the support policy and suggest efficient measures for improvement. Furthermore, the research aims to provide direction for future support projects to enhance the manufacturing competitiveness of SMEs. Ultimately, the goal is to improve the overall manufacturing industry and drive innovation.