• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.79-94
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• 2022

Purpose - The purpose of this study is to examine firm-level attributes related to Korean manufacturing small and medium-sized enterprises' (SMEs') decisions to implement smart factories. Design/methodology/approach - This study uses the provided by the Ministry of SMEs and Startups of Korea and the Korea Federation of SMEs. Manufacturing SMEs' decisions to implement smart factories in 2018-2019 were analyzed using multinomial logit and ordered logit models. Findings - The findings of this study suggest that firms' decisions to implement smart factories were positively related to firm size, R&D intensity, international market scope, and transactional relationships with customers. However, smart factory implementation decisions were not related to firm age and CEO gender. Research implications or Originality - This study illuminates firm-level attributes that may drive organizational innovation in the era of Industry 4.0 and thus contributes to the innovation adoption literature. This study also contributes to growing research on smart factories by analyzing the actual, progressive decisions to implement smart factories, as opposed to perceived intentions to implement them.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.1-15
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• 2019

Purpose: The purpose of this study is to support SMEs' introduction of smart factories during the $4^{th}$ Industrial Revolution era. Through this study, we developed the readiness assessment framework for SMEs. This study draws practical implications for improving the readiness of SMEs to introduce smart factories. Methods: Readiness Assessment Framework Design method, Case Studies Analysis Results: This study identified SMEs suitable for smart factories and identified key issues for nonconforming companies. And the diagnostic framework has been determined whether it works in a real-life SME environment. Conclusion: In order to succeed in the smart factory deployment, readiness assessment for SMEs should be performed as necessary. Prior to the introduction of smart factories, quality innovation activities should be carried out according to factory level.

• Convergence Security Journal
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• v.23 no.3
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• pp.49-56
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• 2023

A smart factory is recognized as a very important requirement for the survival and growth of a company, and it can be said to be an important factor in improving productivity and strengthening competitiveness of a company. In particular, many small and medium-sized manufacturing companies in Korea are making efforts to meet the needs of various markets through smart factories. Building and utilizing smart factories is very important for improving and innovating the production environment of small and medium-sized manufacturing companies. This is important for many companies as well as small and medium-sized manufacturing companies to introduce and utilize smart factories in the future to induce active participation by members of the organization without feeling reluctance or anxiety about changes in smart factories, thereby increasing the utilization of smart factories. was able to confirm.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.551-567
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• 2021

Purpose: The purpose of this paper is to present implications by analyzing research trends on smart factories by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on smart factories. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "SMART FACTORY" and "Smart Factory" as search terms, and the titles and Korean abstracts were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, 739 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; Smart factory research slowed down from 2005 to 2014, but until 2019, research increased rapidly. According to the analysis by fields, smart factories were studied in the order of engineering, social science, and complex science. There were many 'engineering' fields in the early stages of smart factories, and research was expanded to 'social science'. In particular, since 2015, it has been studied in various disciplines such as 'complex studies'. Overall, in keyword analysis, the keywords such as 'technology', 'data', and 'analysis' are most likely to appear, and it was analyzed that there were some differences by fields and years. Conclusion: Government support and expert support for smart factories should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to smart factories. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.32-46
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• 2023

Recently, small and medium-sized manufacturing companies have shown increased interest in and participation in smart factories in order to survive in market competition. However, many SMEs build smart factories without a systematic review or preparation, which leads to them not being able to use them properly. This study considers the main reason for the low utilization rate of smart factories to be a lack of sufficient reflection of user requirements. Therefore, a method and procedure for deriving the priority of smart factory requirement functions and operating performance indicators based on QFD is proposed as a solution to this issue.

• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.17-28
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• 2020

Purpose: The purpose of this study is to confirm the strategic direction of the firm regarding the capabilities of the organization and its employees in order to increase the utilization and business performance of employees by that introduce smart factories in the domestic manufacturing industry. Research design, data, and methodology: This study derived a structured research model to confirm the mediating effect of recognition responses between the quality characteristics of smart factories and dynamic capabilities. For the analysis, a total of 143 valid questionnaires were used for 200 companies that introduced smart factories from domestic SME's. Results: Quality Characteristics of Smart Factory and Dynamic Capabilities had a statistically significant effect on Usefulness. Recognition Response had a statistically mediating on the relationship between quality characteristics of smart factory and business performance. Recognition Response had a statistically significant effect on business performance. Conclusions: It suggests that firms introducing smart factory reflect them in their empowerment strategic because the recognition responses of its employees differ according to the quality characteristics and dynamic capabilities of smart factories. It also means that the information derived from the smart factory system is useful and effective to business performance and employees.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.1-9
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• 2021

This study examines the trends of domestic and foreign smart industries and discusses safety and security issues. Based on the actual situation survey and interview of the smart factory, we would like to examine the perspectives on risks and threats. We will examine safety and health issues related to new harmful and risk factors that may occur in smart factories and suggest institutional development directions for future safety and health. First, a safety and health-related work environment for smart factory workers is investigated and interviews are conducted. Second, we investigate new risk factors and threats to prevent industrial accidents for workers in smart factories. The purpose of this study is to examine what are the new risk factors in the smart factory. In addition, we will try to find reasonable improvement measures by finding out the risks and threats of smart factories through case studies in advanced countries, on-site interviews and surveys.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.29-34
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• 2017

The operating environments of factories and manufacturing units have changed dramatically due to globalization, population, and customization. The existing factories are converted into smart units using information and communications technology (ICT). These smart factories can produce, control, repair, and manage themselves. The manufacturing processes are efficiently optimized using the monitoring and analysis methods of ICT. In this experimental study, we carried out a survey on the system solution providers and consumer companies to determine the field conditions and requirements necessary for assembling a smart factory. Using the results of this survey, we effectively devised smart factory solutions and implemented them on the existing conditions in various factories.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.