• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.1-11
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• 2020

Purpose: This paper treats the survey result from the suppliers of smart factories. Based on the survey results, it is provided suggestions about government policies of the smart factory. Methods: For providing political suggestions, the survey of smart factory is conducted. The survey results are analyzed by the correlation and association methods based on the stratification. Results: The survey results are analyzed for extracting policy-level suggestions. Multiple policy-level suggestions are identified and presented in the conclusion. Conclusion: Six policy-level suggestions are presented for enhancing the management efficiency of suppliers of smart factory.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.675-684
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• 2019

Under the wave of the Fourth Industrial Revolution, developed countries around the world recognize Smart Factory as a core base and strive to enhance the nation's industrial competitiveness through related policies and industry development. Domestic ministries have also set up a strategy for manufacturing innovation 3.0 and are pushing for the expansion of smart factories with 30,000 targets by 2025. In this study, we analyze the practical cases of smart factory security related companies and present the application methods for the same industry. we also intend to contribute to the protectetion of important information in Smart Factory and stable operation.

• Asian Journal of Innovation and Policy
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• v.10 no.3
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• pp.380-403
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• 2021

Recently, smart factories have gained significant importance since the development of the fourth industrial revolution and the rise of global industrial competition. Therefore, the industries' survival to meet the global market trends requires accurate technological planning. Although, different works are available to investigate forecasting technologies and their influence on the smart factory. However, little significant work is available yet on the analysis of technological trends concerning the smart factory, which is the core focus herein. This work was performed to analyze the technological trends of the smart factory, followed by a detailed investigation of recent research hotspots/frontiers in the field. A well-known topic modeling technique, namely Latent Dirichlet Allocation (LDA), was employed for this study described above. The technological trends were further strengthened with the in-depth analysis of a smart factory-based case study. The findings produced the technological trends which possess significant potential in determining the technological strategies. Moreover, the results of this work may be helpful for researchers and enterprises in forecasting and planning future technological evolution.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.165-177
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• 2018

Smart technology has been utilized in various fields of all kinds of industries. Manufacturing industry has built its smart technology environment appropriate for its manufacturing fields in order to strengthen its manufacturing performance and competitiveness. The advance of smart technology for manufacturing industry needs to efficiently produce products, and response customer's demands and services in a global industrial environment. The smart technology capability of manufacturing fields is very crucial for the innovative production and efficient operation activities, and for efficient advancement of the manufacturing performance. We have necessitated a scientific and objective method that can gauge a smart technology ability in order to manage and strengthen the smart technology ability of manufacturing fields. This research provides a comprehensive framework that can rationally gauge the smart technology capability of manufacturing fields for effectively managing and advancing their smart technology capabilities. In this research, we especially develop a structural framework that can gauge the smart technology capability for a smart factory of manufacturing fields, with verifying by reliability analysis and factor analysis based on previous literature. This study presents a 13-item framework that can measure the smart technology capability for a smart factory of manufacturing fields in a smart technology perspective.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.153-158
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• 2017

The certification for Smart Factory supoort successful management of organization while providing strategic plans to the issue of manufacturing process. In Korea, these standards are prepared as the national standards since 2015, and also, there are actions being taken to adpot the certification for Smart Factory. However, to adopt such certification, it is required that the certification operation system needs to be organized, as well as that the society in general should understand about Smart Factory. Accordingly, it is even more required an review on the adoption of the system. This study has the purpose in surveying a variety of atakeholders' perception for the adoption of Smart Factory certification given the circumstance that the cetitification is implemented through literature review and in-depth interviews. This study will be provide significant implication to build a successful plan for the adoption of Smart Factory certification by reviewing perception of professional and problem, strategy of this certification.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.219-227
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• 2020

Smart Factory is one of the fastest developing and changing fourth industrial revolution fields. In particular, the degree of introduction and maturity level in the smart factory is an important part. In this paper, a cluster analysis of companies introduced smart factory was performed based on a new maturity assessment model. The 68% of 193 companies surveyed were at the basic level, with only 21% being the middle one. Most SMEs cited lack of funds as the main reason for not entering the middle one. As a result of the cluster analysis, it was found that all clusters had similar patterns but grouped into one of three levels of high, middle, and low depending on maturity level of smart factory operation, and process domain had the highest maturity and data domain was lowest among the 6 domains. Through this, analysis of more specific and quantified maturity levels can be performed using 6-domain smart factory maturity evaluation model.

• Journal of Convergence for Information Technology
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• v.8 no.2
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• pp.233-238
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• 2018

SMEs and small enterprises are making various attempts to manage SMEs in terms of equipment, safety and energy management as well as production management. However, SMEs do not have the investment capacity and it is not easy to build a smart factory to improve management and productivity of SMEs. In this paper, we propose a smart factory construction algorithm that partially integrates the factory equipment currently operated by SMEs. The proposed algorithm supports collection, storage, management and processing of product information and release information through IoT device during the whole manufacturing process so that SMEs' smart factory environment can be constructed and operated in stages. In addition, the proposed algorithm is characterized in that central server manages authentication information between devices to automate the linkage between IoT devices regardless of the number of IoT devices. As a result of the performance evaluation, the proposed algorithm obtained 13.7% improvement in the factory process and efficiency before building the Smart Factory environment, and 19.8% improvement in the processing time in the factory. Also, the cost of input of manpower into process process was reduced by 37.1%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.503-506
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• 2018

The concern about Smart Factory has increased according to the 4th revolution. The number of security threats targeting Smart Factory devices has increased over the last years and it is possible to cause the vulnerability of security about industry secret data. In this paper, we devide security requirements into four and analyze security vulnerability of Smart Factory devices and describe the attack type newly happened.

• Journal of Information Technology Applications and Management
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• v.28 no.4
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• pp.45-57
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• 2021

This research explores how the success of smart factory adoption is influenced by firm's dynamic capability. This research describes the underlying processes on how organizations manipulate or adapt organizational elements harmoniously to implement smart factory successfully. Although understanding of these processes is essential to many researchers and practitioners in the field, the information system research literature contains very few examples of this type. The research is conducted in the following sequence: first, the concept of dynamic capability is presented followed by research methodology; and then the analyses of case data are presented followed by discussions and future directions. The results of this research show that the firms with higher dynamic capability adopted smart factory more easily through alignment of various organizational elements.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1071-1082
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• 2021

Since the smart factory has been recently recognized as an industrial core requirement, various mechanisms to ensure efficient and stable operation have attracted much attention. This attention is based on the fact that in a smart factory environment where operating processes, such as facility control, data collection, and decision making are automated, the disruption of processes due to problems such as facility anomalies causes considerable losses. Although many studies have considered methods to prevent such losses, few have investigated how to effectively apply the solutions. This study proposes a Kubernetes based system applied in a smart factory providing effective operation and facility management. To develop the system, we employed a useful and popular open source project, and adopted deep learning based anomaly detection model for multi-sensor anomaly detection. This can be easily modified without interruption by changing the container image for inference. Through experiments, we have verified that the proposed method can provide system stability through nondisruptive maintenance, monitoring and non-disruptive updates for anomaly detection models.