• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.274-280
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• 2024

The smart factory promotion project is a project that improves the entire management environment system, including the production process, using ICT technology. According to the 2019 Smart Factory Survey and Analysis Research Report of the Ministry of SMEs and Startups, small and medium-sized enterprises that introduced smart factories reported positive effects such as increased productivity, improved quality, and reduced costs on average. On the other hand, the survey results of companies that promoted the project despite positive results showed that there was room for improvement. This study dealt with the contents of the survey conducted on companies by the smart factory promotion agency in 2020 regarding the infrastructure configuration for promoting smart factories. We examined the meaningful contents implied by the data related to the infrastructure configuration. These meaningful survey results can lead to more efficient business promotion in the future when promoting smart factory projects.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.281-294
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• 2023

Purpose - The purpose of this study is to explore the determinants of the organizational level for the advancement of smart factory. We suggested three determinants of the organizational level such as CEO's entrepreneurship, high-involvement human resource management, and cooperative industrial relations. Design/methodology/approach - The population of our survey was manufacturing SMEs, and we took a sample and conducted a survey of 232 companies. Since the level of smart factory advancement, which is a dependent variable, was measured on an ordinal scale, ordinal logistic regression analysis was used to test the hypothesis. Findings - The higher the level of high-involvement human resource management, the higher the level of smart factory advancement. As the level of high-involvement human resource management increases by one unit, the probability of smart factory advancement increases by 22.8%. On the other hand, the CEO's entrepreneurship did not significantly affect the level of smart factory advancement. Interestingly, the cooperative industrial relations negatively affected to the level of smart factory advancement, contrary to the hypothesis prediction. Research implications or Originality - This study explored determinants at the organizational level that affect the advancement of smart factories. Through this, various implications are presented for related research and policy fields.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.107-115
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• 2017

Recently, much attention in building smart factory have been dramatically increased. Despite the growing interest in smart factory, few guidelines exist how to successfully build smart factory. The purpose of this study is to investigate successful cases in building smart factory in Korea. Drawing on the analysis of successful cases, we suggest the valuable guidelines and directions toward success of smart factory. As a result, in the case of large-size firms, it is an effective strategy that expanding from a model factory to whole factory for successful smart factory building. In addition, in the case of medium and small-size firms, it is an effective strategy that upgrading from low-level step to high-level step for successful smart factory building. Therefore, this study provides companies and government with specific and practical success strategies as well as industrial policy improvements.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.43-57
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• 2021

Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.97-117
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• 2020

Five years have passed since the introduction of the smart factory amid the new opportunities for growth and job creation in relation to domestic manufacturing companies. Nevertheless, there is a lack of analysis on SMEs introduction smart factories. This study empirically analyzed the effects on the introduction of smart factories of domestic metal processing SMEs by distinguishing the characteristics of enterprises In this study, 103 companies which introduced smart factories and another 106 companies which did not introduce them were sampled. The Introduction of the Smart Factory was analyzed by four categories such as the Company characteristics (R&D capability, product production capability, organizational change), entrepreneur characteristics (risk sensitivity), relational characteristics (trust, dependence, cooperation, Influence), and structural characteristics (competition). As a result of the research, we found out product production capacity, risk sensitivity, trust and cooperation, Influence, and competition are statistically significant in the introduction of smart factory. But competition was characterized by a negative (-) sign opposite to the hypothesis. This study is meaningful in that the scope of the analysis has been expanded by analyzing whether smart factory was introduced or not considering the characteristics of the company. And there should be continuous research on its utilization as well as the introduction of smart factory.

• Journal of the Korea Safety Management & Science
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• v.24 no.2
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• pp.135-142
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• 2022

The smart factory is an important system that can reduce defects, maximize productivity, and respond to customer needs, from the labor-intensive era of traditional small and medium-sized manufacturing companies through the automation era to CPS using ICT. However, small and medium-sized manufacturers often fall short of the basic stage due to economic and environmental constraints, and there are many companies that do not even recognize the concept of a smart factory. In this situation, to expand the smart factory of small and medium-sized enterprises, the project to support the establishment of a smart factory for the win-win between large and small enterprises. The win-win smart factory construction support project provides a customized differentiation program support project according to the size and level of the company for all domestic manufacturing SMEs regardless of whether or not they are dealing with Samsung. In this study, we analyze the construction status and introduction performance of companies participating in the win-win smart factory support project to find out whether they have been helpful in management and to find efficient ways to improve support policies, and to suggest the direction of continuous support projects to improve the manufacturing competitiveness of SMEs in the future.

• The Journal of Information Systems
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• v.31 no.1
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• pp.197-218
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• 2022

Purpose This study examines the roles of firm-level smart factory implementation in the relationship between organizational competence and organizational performance in the context of Korean small and medium Enterprises (SMEs). To achieve this goal, this study presents and empirically tests a research model with evaluation data conducted by industrial experts on how organizational competence can be exploited to positively influence organizational performance through smart factory implementation. Design/methodology/approach Organizational competence are based on the research construct developed by Odważny et al.(2018). Research constructs on smart factory are based on the measurement model developed by Korea Technology and Information Promotion Agency for Korea small and medium Enterprises (TIPA) (2020) and organizational performance are based on the performance construct developed by Kwon(2019). To complete the investigation, we collected 31 firm data conducted by industrial experts in Korea from Dec 2018 to Dec 2020. Most of firm was implemented officially by government budget granted for smart factory of Korea SMEs. To test our hypotheses, partial least squares (PLS) method was employed. Findings The findings indicate that organizational competence is antecedent to influence smart factory implementation, while smart factory implementation has significant relationship with organizational performance. This study provides a better understanding of the connection between organizational competence and organizational performance through smart factory implementation. So companies should focus on enhancing organizational competence and implementing smart factory to obtain sustainable competitiveness.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.11-26
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• 2018

Purpose: This study is to help the construction of smart factories of other manufacturing enterprises through IDIS 's case of smart factory construction. Methods: We introduce the four phases of implementing smart factory building by IDIS company, which produces a small quantity of multi-odd units. Results: Through the smart factory construction, the cost of product is reduced due to the improvement of total productivity such as office work, production work, and energy saving, and sales are enhanced by customized production, quality / delivery reliability improvement. Conclusion: We present the actual examples needed to build the manufacturer's smart factory.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.133-152
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• 2017

Smart factory has been regarded as a big opportunity for manufacturing industries. However, little literature has been studied for the current status of Korean smart factory. Our paper tries to find gaps between research and real world by summarizing the recent literature and cases in Korean context. As the present level of smart factory introductions in Korean small manufacturing firms is lower than what a variety of literature says, our study points out that more efforts, investments and government support are required to catch up with the knowhow and technologies of developed countries although real-time control, enhanced productivity have been obtained. In future research, we will continue the smart factory study with the accumulated real data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.131-139
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• 2021

It can be said that smart factory is the most prominent area in the fourth industrial revolution. Developing processes or algorithms required for smart factory requires data values from smart factory, but there are many real challenges in obtaining such data. Therefore, this study developed a data generator that can more realistically simulate data from different processes in smart factory to help research on smart factory. In addition, functions such as setting presets and intuitive UI configurations were developed for the convenience of data creators. This data generator will help you simulate smart factory environments by providing more realistic data easily and simply when you create the different systems needed for smart factory environments.