• Korean small business review
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• v.41 no.4
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• pp.1-36
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• 2019

The purpose of this study is to identify the relationships among purposes and contents of smart factory building and continuous utilization of smart factory. Specifically, this study identifies two types of purposes of smart factory building as follows: (1) improving productivity, (2) increasing flexibility. In this study, three aspects of smart factory building contents were suggested like this: (1) automation area (facility automation vs. work automation), (2) big data system focus (radical transformation vs. incremental improvement), and (3) value chain integration area (internal value chain integration vs. external value chain integration). In addition, we looked at how firm size moderates the purposes - contents - continuous utilization of smart factory relationship. A questionnaire survey was conducted on 151 manufacturing companies. More specifically, out of 151 companies, 100 are small-and-medium-sized enterprises and 51 large-sized enterprises. All questionnaires were targeted at companies with Smart Factory level above level 2. The analysis results of this study using Smart PLS statistical programs are as follows. First, the purposes of smart factory building including increasing productivity and flexibility had positive impacts on all of the contents of smart factory building. Second, all of smart factory building contents had positive impacts on the continuous use of smart factory except big data system for incremental improvement of manufacturing process. Third, the impacts of smart factory building purposes implementation on smart factory building contents varied depending on whether the purpose is productivity improvement or flexibility. Fourth, it was founded that firm size moderated the relationships of purposes - contents - continuous utilization of smart factory in such a way that large-sized firms tend to empathize the link between flexibility and smart factory building contents for continuous use of smart factory, while small-and-medium-sized-firms emphasizing the link between productivity and smart factory building contents. Most of the previous studies have focused on presenting current smart factory deployment cases. However, it is believed that this research has made a theoretical contribution in this field in that it established and verified a research model for the smart factory building strategy. Based on the findings from a working-level perspective, corporate practitioners also need to have a different approach to smart factory building, which should be emphasized depending on whether their purpose of building smart factory is to increase productivity or flexibility. In particular, since the results of this study identify the moderating effect of firm size, it is deemed necessary for firms to implement a smart factory building strategy suitable for their firm size.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1832-1842
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• 2010

This paper introduces a new automatic processing system: "Contents Factory" for the mass production of contents. Through the contents factory, we provide an authoring environment to improve the usability and the efficiency in producing contents. The contents factory integrates recycling techniques for contents resources, contents development engines, authoring tools, and interfaces into a total processing system. Since it is multi-platform based including mobile devices as well as PCs, one can easily produce complete PC and mobile contents from raw resources. We produced an example, "Sejong square" via the contents factory in order to demonstrate its effectiveness and usability.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.229-234
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• 2024

A smart factory is defined as a cutting-edge, intelligent factory that integrates all production processes from product planning to sales with information and communication technology. Through these factories, each company produces customized products with minimal cost and time. The smart factory promotion project in Korea has produced positive results even in difficult environments such as the COVID-19 situation. Through the transition to a smart manufacturing production system, the competitiveness of small and medium-sized businesses has been greatly strengthened, including increased productivity and reduced costs. This study was based on surveyed data conducted by organizations related to smart factory promotion in 2020. Significant contents and major characteristics that emerged from the surveyed data were inferred and described. Since the meaningful contents reflect the reality of the company, more efficient promotion of smart factories will be possible in the future.

• Review of Korea Contents Association
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• v.15 no.2
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• pp.21-24
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• 2017

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.407-420
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• 2019

This study is an empirical study of 'the effect of Technological innovation through environmental factors of an enterprise on the implementation of a Smart Factory'. The purpose of the research is to improve the utilization and effectiveness of the Smart Factory by considering and implementing factors that will be promoted in an internal environment or focus when building. The research method was statistical analysis with SMART PLS by surveying the relevant personnel of the company that implemented the Smart Factory. The results of the study showed that internal organizational factors and self-efficacy have a positive effect on technological innovation, and technology innovation has a positive effect on the key factors of smart factory implementation. And the absorbing capacity, which is a moderating variable, has a positive effect in part on the key factors of smart factory implementation by interacting with technological innovation factors. This study can be used by companies that want to implement a smart factory, and it has the significance of laying the theoretical foundation for research on smart factory implementation through empirical analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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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.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.42-48
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• 2022

Currently, the world is facing severe inflation due to Corona and the war in Ukraine, and it is causing a lot of difficulties for us. Companies are facing a lot of restrictions on their economic activities compared to the past due to supply chain problems and foreign exchange rates. In this situation, many countries have been implementing various smart factory promotion projects to secure competitiveness through productivity improvement in the manufacturing industry. In this study, the contents of smart factory promotion in major countries were reviewed, and problems raised about the implementation of smart factory in Korea, which are being implemented based on this, were described. It is most reasonable to judge the success of a smart factory by the achievement of the performance indicators presented at the time of the project. Therefore, based on the performance index of the business, which is a key factor in determining the success or failure of a smart factory, we investigated whether the company's smart factory promotion can be carried out successfully through examples

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.171-176
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• 2020

This paper presents an implementation of a gesture recognition platform that can be used in a factory workplaces. The platform consists of signages that display worker's job orders and a control center that is used to manage work orders for factory workers. Each worker does not need to bring work order documents and can browse the assigned work orders on the signage at his/her workplace. The contents of signage can be controlled by worker's hand and arm gestures. Gestures are extracted from body movement tracked by 3D depth camera and converted to the commandsthat control displayed content of the signage. Using the control center, the factory manager can assign tasks to each worker, upload work order documents to the system, and see each worker's progress. The implementation has been applied experimentally to a machining factory workplace. This flatform provides convenience for factory workers when they are working at workplaces, improves security of techincal documents, but can also be used to build smart factories.

• Journal of Biosystems Engineering
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• v.43 no.1
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• pp.30-36
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• 2018

Purpose: The objective of this study is to evaluate the effect of cultivation conditions on the growth and glucosinolate content of Chinese cabbage and kale. Methods: Chinese cabbage and kale were grown in three different cultivation conditions, including a plant factory, greenhouse, and open field. Samples were collected at two harvesting times (10 d and 20 d after transplanting the seedlings). Nine growth parameters (plant height, plant width, number of leaves, petiole diameter, SPAD readout, leaf length, leaf width, stem diameter, and plant weight) were measured immediately after harvesting, and the samples were freeze-dried and stored until the glucosinolate content was analyzed. Mean values of the growth parameters and glucosinolate contents were evaluated using Duncan's multiple range tests. Results: The results indicated that the plant parameters of the Chinese cabbage and kale were greater for plants grown in the plant factory and greenhouse. The plant height, width, and weight showed significant differences in the Duncan's multiple range tests at a 5% level. The plant factory also produced greater contents of most of the glucosinolates. Conclusions: Three different cultivation conditions significantly affected the growth and glucosinolate contents of Chinese cabbage and kale. Further study is necessary to investigate other functional components and different vegetable varieties.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.273-278
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• 2022

Uncertainty is increasing around the world due to COVID-19 and Ukraine crisis. In this situation, each company is making countless efforts to survive. In Korea, smart factory projects targeting small and medium-sized businesses with difficulties have been continuously promoted. As for the smart factory business that has been promoted so far, the base expansion of the smart factory is also steadily increasing as the number of companies carrying out the project is increasing. It was also found that it contributed to productivity improvement and quality improvement. Despite these positive aspects, difficulties and operational problems are also appearing in the process of promoting smart factories. In this study, we investigated and analyzed operational problems and difficulties in the process of promoting smart factories. In addition, improvement plans for problems were presented according to the contents of this analysis, and improvement plans were presented by classifying them into introduction and supply companies, considering that the smart factory business is formed in the form of a consortium between introduction and supply companies.