• 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.

• Progress in Superconductivity and Cryogenics
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• v.26 no.1
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• pp.25-30
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• 2024

High-temperature superconducting rotors offer advantages in terms of output-to-weight ratio and efficiency compared to conventional phase conduction motors or generators. The rotor can be cooled by conduction cooling, which attaches a cryocooler, and by refrigerant circulation, which uses circulating liquid or gas neon, helium and hydrogen. Recent work has focused on environmental issues and on high-temperature superconducting motors cooled with liquid hydrogen that can be combined with fuel cells. However, to ensure smooth supply and return of the cryogenic cooling fluid, a cryogenic rotational coupling between the rotating and stationary parts is necessary. Additionally, the development of a sealing structure to minimize fluid leakage applicable to the coupling is essential. This study describes the design and performance evaluation of a non-contact sealing method, specifically a labyrinth seal, which avoids power loss and heat load caused by friction in contact sealing structures. The seal design incorporates a spiral flow path to reduce leakage using centrifugal force, and computational fluid dynamics (CFD) simulations were conducted to analyze the flow path and rotational speed. A performance evaluation device was configured and employed to evaluate the designed seal. The results of this study will be used to develop a cryogenic rotational coupling with supply and return flow paths for cryogenic applications.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.269-279
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• 2024

The study explores the evolving landscape of overseas expansion strategies by Korean corporations, focusing on recent geopolitical tensions, the COVID-19 pandemic, and disruptions in global supply chains. It emphasizes the challenges faced by industries producing high-value products and delves into the concept of "Friend-Shoring" policies in the United States, leading major Korean companies to invest in local semiconductor, battery, and automotive factories. Recognizing the potential fragmentation of Korea's manufacturing sector, the paper introduces the "Mother Factory" strategy as a policy initiative, inspired by Japan's model, to establish core production facilities domestically. The discussion unfolds by examining the cases of major companies in Japan and the United States, highlighting the need for Korea to adopt a mother factory strategy to mitigate risks associated with friend-shoring policies. Inspired by Intel's "Copy Exactly" approach, the paper proposes a Korean mother factory model integrating smart factory technology and digital twin systems. This strategic shift aims to enhance responsiveness to geopolitical challenges and fortify the competitiveness of Korean high-tech industries. Finally, the paper proposes a Korean Mother Factory based on smart factory concepts. The suggested model integrates smart factory technology and digital twin frameworks to enhance responsiveness and fortify competitiveness. In conclusion, the paper advocates for the adoption of a comprehensive Korean Mother Factory model to address contemporary challenges, foster advanced manufacturing, and ensure the sustainability and competitiveness of Korean high-tech industries in the global landscape. The proposed strategy aligns with the evolving dynamics of the manufacturing sector and emphasizes technological advancements, collaboration, and strategic realignment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.541-542
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• 2012

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.176-185
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• 2018

With the recent development of manufacturing technology and the diversification of consumer needs, not only the process and quality control of production have become more complicated but also the kinds of information that manufacturing facilities provide the user about process have been diversified. Therefore the importance of big data analysis also has been raised. However, most small and medium enterprises (SMEs) lack the systematic infrastructure of big data management and analysis. In particular, due to the nature of domestic manufacturing companies that rely on foreign manufacturers for most of their manufacturing facilities, the need for their own data analysis and manufacturing support applications is increasing and research has been conducted in Korea. This study proposes integrated analysis platform for process and quality analysis, considering manufacturing big data database (DB) and data characteristics. The platform is implemented in two versions, Web and C/S, to enhance accessibility which perform template based quality analysis and real-time monitoring. The user can upload data from their local PC or DB and run analysis by combining single analysis module in template in a way they want since the platform is not optimized for a particular manufacturing process. Also Java and R are used as the development language for ease of system supplementation. It is expected that the platform will be available at a low price and evolve the ability of quality analysis in SMEs.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.61-68
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• 2020

In the era of the fourth industrial revolution, many production plants are gradually evolving into smart factories that apply information and communication technology to manufacturing, distribution, production, and quality management. The conversion from conventional factories to smart factories has resulted in the automation of production sites using the internet and the internet of things (IoT) technology. Thus, labor-intensive production can easily collect necessary information. However, implementing a smart factory required a significant amount of time, effort, and money. In particular, labor-intensive production industries are not automated, and productivity is determined by human skill. A representative industry of such industries is sewing the industry. In the sewing industry, wherein productivity is determined by the operator's skills. This study suggests that production performance, inventory management and product delivery of the sewing industries can be managed efficiently with existing production method by using smart buttons incorporating IoT functions, without using automated machinery.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.9
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• pp.527-533
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• 2017

Environmental concern about smart phone is growing because it has short product life span while having intensive production technology and cost. In this study environmental impact of the smart phone is quantified using the LCA methodology based on the ISO 14040 series standards. The assessment considers potential environmental impacts across the whole life cycle of the smart phone including; pre-manufacturing; manufacturing; distribution; product use; and end-of-life stages. The pre-manufacturing stage is the most dominant life cycle stage causing the highest environmental impacts among all 10 impact categories assessed. The global warming impacts of the smart phone in the pre-manufacturing, distribution, use, manufacturing, and end-of-life stages were 52.6% 23.9%, 15.7%, 7.0%, and 0.8%, respectively. Sensitivity of the life cycle impact assessment results to the system boundary definition and assumptions made were quite high. Three components of the smart phone, PCB, battery, and display module were identified as the key components causing majority of the potential environmental impact in the pre-manufacturing stage. As such the slim and light-weight design and the use of environmental friendly materials are important design factors for reducing the environmental impact of the smart phone.

• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.687-694
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• 2015

A photoluminescence (PL) imaging method using a vision camera was employed to inspect InGaN/GaN quantum-well light-emitting diode (LED) epi-wafers. The PL image revealed dark spot defective regions (DSDRs) as well as a spatial map of integrated PL intensity of the epi-wafer. The Shockley-Read-Hall (SRH) nonradiative recombination coefficient increased with the size of the DSDRs. The high nonradiative recombination rates of the DSDRs resulted in degradation of the optical properties of the LED chips fabricated at the defective regions. Abnormal current-voltage characteristics with large forward leakages were also observed for LED chips with DSDRs, which could be due to parallel resistances bypassing the junction and/or tunneling through defects in the active region. It was found that the SRH nonradiative recombination process was dominant in the voltage range where the forward leakage by tunneling was observed. The results indicated that the DSDRs observed by PL imaging of LED epi-wafers were high density SRH nonradiative recombination centers which could affect the optical and electrical properties of the LED chips, and PL imaging can be an inspection method for evaluation of the epi-wafers and estimation of properties of the LED chips before fabrication.

• 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 Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.73-85
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• 2020

While Korea became one of manufacturing powers in the world through a fast-follower strategy as well as implementing the approach of advancing manufacturing business focused on quantitative input, The advent of the fourth industrial revolution and demand becoming more complicated than ever both require a system that quickly detects the change of markets in advance and reflects it in the manufacturing strategy. Accordingly, the introduction of a smart factory is not optional but mandatory in order to strengthen the competitiveness of manufacturing business using ICT. This paper aims to investigate key factors having influence on the intention to continuously use a smart factory, the innovative IT device, on the basis of the technology acceptance model. This paper analyzed the influence of the leadership of CEO, organizational learning and perceived switching costs on the intention to continuously use a smart factory by the parameters of perceived ease of use and usefulness, the major belief valuables of the IT acceptance model.