• 실천공학교육논문지
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• 제13권3호
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• pp.483-490
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• 2021

본 논문에서는 스마트팩토리 기반의 CPPS(Cyber Physical Production System) 및 VR(Virtual Reality) 기술을 활용한 스마트팩토리 통합 기술 교육 플랫폼 개발과 플랫폼을 활용한 교육 방법들을 제안하였다. 3D 디지털 트윈과 연동이 가능하며 BOP(Bill of Process) 기반의 제조 공정을 통합하는 방법을 학습할 수 있도록 플랫폼을 개발하였다. 또한 디지털 트윈은 OPC-UA 서버를 통해 메카니컬 시스템과 디지털 트윈 뿐만 아니라 가상 현실까지 연계하여 통합 스마트팩토리 기반의 교육 플랫폼을 구축하였다. 이러한 플랫폼을 기반으로 스마트팩토리 통합 플랫폼은 BOP 기반 디지털 트윈 시뮬레이션, OPC-UA 통합, MES 시스템, SCADA 시스템, VR 연동으로 스마트팩토리 통합 플랫폼의 개별 요소들을 가지도록 제안하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제16권2호
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• pp.203-208
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• 2024

The convergence of deep learning and smart factory is drawing a lot of attentions from not only industrial but also academic circles. The objective of this article is to quantitatively review on deep learning and smart factory from 2010 to 2023. This research analyzed the 138 articles, extracted from the Core Collection of Web of Science, in terms of four dimensions such as the main trend in article publications, the main trend in article citations, the distribution of article publications by research area, and the keywords representing the main contents of published articles. The quantitative review results reveal the following four points: First, the article publications drastically grew from 2019 to 2022 in its annual trend. Second, the article citations have rapidly grown since 2018. Third, Engineering, Computer Science, and Telecommunications are the top 3 research areas composing the 138 articles. Fourth, it is the top 10 keywords such as 'deep', 'learning', 'smart', 'detection', factory', 'data', 'system', 'manufacturing', 'neural', and 'network' that represent the main contents of the 138 articles published from 2010 to 2023 in deep learning and smart factory. These findings revealed by this quantitative review will be significantly useful for deepening and widening relevant future research on deep learning and smart factory.

• Journal of Information Technology Applications and Management
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• 제27권1호
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• pp.75-95
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• 2020

Smart Factory is the decisive factor of the Fourth Industrial Revolution and is a key field for national competitiveness. Until now, most smart factory research has focused on policy and technology. In order to spread more technology, it is necessary to study what factors influence the adoption of smart factory technology in the enterprise. Nevertheless, little research has been done. In this study, based on the UTAUT (Unified Theory of Acceptance and Use of Technology), which has been proved through many years of research, I have studied the factors that influence the acceptance of smart factory technology. As a result of research, performance expectancy, social influence, and facilitating conditions of UTAUT model had a positive(+) effect on behavior intention. Their relationship of influence was in the order of performance expectancy (β = .459)> facilitating conditions (β = .212)> social influence (β = .210). However, it was found that the effort expectancy did not affect the behavior intention, and the impact of the newly perceived risk on the behavior intention to use was not confirmed. The main reason is that the acceptance of smart factory technology is not a matter of personal interest but a matter of organizational choice. Trust, on the other hand, was found to be partially mediated between performance expectancy, facilitating conditions, social influence and behavior intention. For many years, many researchers have validated the UTAUT, which has been validated through various empirical studies. It is academically meaningful to begin the study of factors affecting the acceptance of smart factory technology in terms of the UTAUT. In practice, it is necessary to provide SME employees with more information related to the introduction of smart factories, to provide advanced services related to the establishment of smart factories, and to establish a standardized model for each industry.

• 한국멀티미디어학회논문지
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• 제22권5호
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• pp.601-612
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• 2019

As the $4^{th}$ industrial revolution is accelerating, IT convergence application technologies are attracting attention in various fields. In the manufacturing industry, Smart Factory technology, which is blended with IT technology, has been developed to solve the problem casued by the decrease of the labor force, and a monitoring server is required to remotely control the equipment or to inquire about the operation status of the factory. In this paper, we designed and implemented RESTful API for data sharing between factory equipment and monitoring server in Smart Factory. In order to verify the designed API, a testbed was operated for an actual plastics manufacturing plant. As a result, it was confirmed that the testbed can be operated normally in actual operating environment.

• 정보보호학회논문지
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• 제26권5호
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• pp.1323-1333
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• 2016

현대의 공장은 스마트기기의 확산과 통신 기술의 발달로 스마트화 됨에 따라 보안 문제가 대두되고 있다. 그 중에서 스마트공장은 기기 간 정보가 상호 교환되기 때문에 스마트공장에서 발생할 수 있는 보안위험을 식별, 평가 및 통제하기 위한 위험관리 방안이 필요하다. 본 논문에서는 국내 스마트공장(기초수준)을 현장에서 확인 한 결과를 토대로 스마트공장 위험우선순위(SFRPN, Smart Factory Risk Priority Number) 모형을 적용하여 국내 스마트공장(기초수준)에서 적용 가능한 최소보안요구사항을 연구 제안한다.

• 한국전자통신학회논문지
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• 제16권5호
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• pp.783-788
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• 2021

스마트제조는 제품기획, 설계, 생산, 품질, 재고, 조달 등 스마트공장 내 제조 프로세스의 정보화, 최적화 및 생산 시스템의 자동화를 ICT기반 스마트 기술로 실현하는 제조 공정으로 정의된다. 본 논문에서는 스마트공장과 스마트제조 시스템의 운영시 발생하는 제조 데이터와 관련된 국내 표준화 동향에 대해 소개한다. 표준화의 범위가 매우 넓기 때문에 스마트공장 및 제조 ICT시스템과 관련된 일반적인 표준화 내용 및 제조 데이터를 거래시 필요한 표준에 관련된 사항을 다룬다. 이를 기반으로 하여 제조 데이터의 활용을 위해 필요한 사항에 대해 논의한다.

• International Journal of Internet, Broadcasting and Communication
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• 제16권1호
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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.

• 융복합기술연구소 논문집
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• 제7권2호
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• pp.21-23
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• 2017

Smart Factories could be regarded as a result of the integration of various key technologies of the fourth industrial revolutions. In smart factory, the IoT (Internet of things) is applied to capture the data generated by the production facility, store and analyze data generated in real time using Big Data technology. In addition, 3D printers are used to print expensive and complex parts, industrial robots supply materials and parts to the production site, store finished products in warehouses. In this paper, we introduced the definition of smart factory and change of job market. Also, we summarize several national policies to support enhancing transformation process of smart factory.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.206-211
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• 2022

Recently, the world is facing many difficulties in all areas as a result of price instability and the Russian-Ukraine war. Personally, as many jobs disappear, household income is declining sharply. In particular, the possibility of such bankruptcies is relatively increasing in small and medium-sized enterprises (SMEs), and it is highly likely that this will continue for the time being. In this situation, countries around the world are continuously making efforts to improve corporate productivity. In Korea, the smart factory support project implemented by the Smart Manufacturing Innovation Promotion Team has been continuously promoted for the past several years, providing opportunities for SMEs in need to improve productivity and change the corporate structure. In this study, the current status of smart factory promotion at home and abroad was examined, and problems and improvement measures were studied for the insufficient efficiency in the smart factory promotion system implemented in Korea.

• 시스템엔지니어링학술지
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• 제13권2호
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• pp.57-64
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• 2017

A new paradigm based on distributed manufacturing services is emerging. This paradigm shift can be realized by smart functions and smart technologies such as Cyber Physical System (CPS), Artificial Intelligence (AI), and Cloud Computing. Most architectures define stack levels from Level 0 (equipment) to Level 4 (business area) and specify the services to be provided between them. Because of their a rough technical specification, there is a limitation on how to actually utilize a technology to actually implement a smart factory service with this architecture. In this paper, we propose a smart factory architecture that can be utilized directly from the perspective of a smart service system by making the use of System Engineering Process and System Modeling Language (SysML).