• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1467-1482
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• 2017

Recently, Interests on The Fourth Industrial Revolution has been increased. In the manufacturing sector, the introduction of Smart Factory, which automates and intelligent all stages of manufacturing based on Cyber Physical System (CPS) technology, is spreading. The complexity and uncertainty of smart factories are likely to cause unexpected problems, which can lead to manufacturing process interruptions, malfunctions, and leakage of important information to the enterprise. It is emphasized that there is a need to perform systematic management by analyzing the threats to the Smart Factory. Therefore, this paper systematically identifies the threats using the STRIDE threat modeling technique using the data flow diagram of the overall production process procedure of Smart Factory. Then, using the Attack Tree, we analyze the risks and ultimately derive a checklist. The checklist provides quantitative data that can be used for future safety verification and security guideline production of Smart Factory.

• Advances in nano research
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• v.17 no.2
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• pp.109-124
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• 2024

In the era of smart manufacturing, precise prediction of springback-a common issue in ultra-thin sheet metal forming- and forming limits are critical for ensuring high-quality production and minimizing waste. This paper presents a novel approach that leverages the Internet of Things (IoT) and Artificial Neural Networks (ANN) to enhance springback and forming limits prediction accuracy. By integrating IoT-enabled sensors and devices, real-time data on material properties, forming conditions, and environmental factors are collected and transmitted to a central processing unit. This data serves as the input for an ANN model, which is trained with crystal plasticity simulations and experimental data to predict springback with high precision. Our proposed system not only provides continuous monitoring and adaptive learning capabilities but also facilitates real-time decision-making in manufacturing processes. Experimental results demonstrate significant improvements in prediction accuracy compared to traditional methods, highlighting the potential of IoT and ANN integration in advancing smart manufacturing. This approach promises to revolutionize quality control and operational efficiency in the industry, paving the way for more intelligent and responsive manufacturing systems.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• Journal of Digital Policy
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• v.2 no.4
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• pp.17-23
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• 2023

In this paper, in order to improve production processing for small and medium-sized precision processing companies, we apply a manufacturing execution system to existing process methods and integrate precision processing data to strengthen process management within the company, increase facility operation efficiency, and realize a reduction in defect rates. The differences in productivity improvement and cost reduction rates were compared and analyzed. As a result, production productivity improved by 7.0% and product defect rate improved by 0.1% point due to the introduction of the manufacturing execution system. It was confirmed that manufacturing cost reduction improved by 10.0% and delivery compliance rate improved by 1.1%. If additional smart factory technology is applied based on the manufacturing execution system proposed in this study in the future, sales and profits in the processing industry are expected to increase due to an increase in the PQCD index.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1525-1530
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• 2021

By applying AI-based efficient inventory management and logistics optimization technology using the smart factory's production plan and manufacturing data, the company's productivity improvement and customer satisfaction can be expected to increase. In this paper, we proposed a system that collects data from the factory's production process, stores it in the cloud, and uses the manufacturing data stored there to apply AI-based supply chain optimization technology later. While the existing system supported approximately 10 to 20 data types, the proposed system is designed and developed to support more than 100 data types. In addition, in the case of the collection cycle, data can be collected 1-2 times per second, and data collection in TB units is possible. Therefore This system is designed to be applied to the existing factory of past in addition to the smart factory.

• Composites Research
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• v.35 no.3
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• pp.134-138
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• 2022

In this study, Ti powder/Polymer concrete composites were processed by adding the PZT powder, one of the piezoelectric materials, to improve the vibration damping effect of Polymer concrete. Ti powder was added at a constant ratio in order to maximize the vibration damping effect using the piezoelectric effect. Three types of composite material specimens were prepared: a specimen without PZT powder, specimens with 2.5 wt% and 5 wt% of PZT powder. The vibration characteristics and compression properties were analyzed for all specimens. As a result, it was confirmed that as the addition ratio of PZT powder increased, the Inertance value at the resonant frequency decreased due to the piezoelectric effect when the vibration generated from Ti powder/polymer concrete was transmitted. Especially, the Inertance value was decreased by about 19.3% compared to the specimen without PZT at the resonant frequency. The change in acceleration with time also significantly decreased as PZT powder was added, confirming the effect of PZT addition. In addition, through the compression strength test, it was found that the degree of deterioration in compression properties due to the addition of PZT up to 5 wt% was insignificant, and it was confirmed that the powder was evenly dispersed in the composites through the cross-sectional analysis of the specimen.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.208-219
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• 2021

In the era of the 4th industrial revolution driven by the convergence of ICT(information and communication technology) and manufacturing, research on smart factories is being actively conducted. In particular, the manufacturing industry prefers smart factories that autonomously connect and analyze data. For the efficient implementation of smart factories, it is essential to have an integrated production system that vertically integrates separately operated production equipment and heterogeneous S/W systems such as ERP, MES. In addition, it is necessary to double-verify production data by using automatic data collection technology so that the production process can be traced transparently. In this study, we want to show a case of data-centered integration of a large aircraft parts processing factory that requires high precision, takes a long time, and has the characteristics of processing large raw materials. For this, the components of the data-oriented integrated production system were identified and the connection structure between them was explained. And we would like to share the experience gained through the design and implementation case. The integrated production system proposed in this study integrates internal components based on data, which is expected to serve as a basis for SMEs to develop into an advanced stage, and traces materials with RFID technology.

• Journal of Appropriate Technology
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• v.6 no.1
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• pp.56-64
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• 2020

Recently, major manufacturers are focusing their efforts on securing global competitiveness through smart factory, but developing countries have many difficulties in applying smart factory due to financial and technical conditions. This study is a preliminary study on the development of an ICT-based power monitoring system applicable to developing countries. The questionnaire surveyed and analyzed workers' perceptions of smart factory in a garment manufacturing factory in developing countries, Indonesia. Before and after the installation of the power monitoring system, the survey was conducted for 126 local managers and workers, and the correlation was analyzed using SPSS. As a result of analysis, factory workers in developing countries such as Indonesia are also positively aware of the necessity of introducing smart factory technology, and it is expected that the introduction of these technologies will affect job satisfaction and improve the factory environment. In addition, the result of the survey conducted after the installation of the power monitoring system increased the job satisfaction score by 5.5% compared to before the installation, and the scores on the perception of the necessity of the power monitoring system and the positive effect of the application of the system on the factory environment were increased 13% and 5.9%, respectively. It was also confirmed that managers rather than workers and female rather than male showed positive perception for the introduction of smart factory technology. The result of this study is expected to be an important reference in the direction of development of appropriate smart factory technology applicable to developing countries and the introduction of smart factory by manufacturers operating factories in developing countries.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.1
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• pp.17-22
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• 2016

In smart factories, the entire manufacturing process from design to the final product is simulated in a virtual manufacturing environment and optimized before starting production. Suppliers and customers make decisions based on the simulation results. Therefore, effective rendering of the information of the virtual products to suppliers and customers is essential for this manufacturing paradigm. In this study, a method of rendering the surface roughness of the virtual products using a tactile display is presented. A tactile display device comprising a $3{\times}3$ array of individually controlled piezoelectric stack actuators is constructed. The surface topology of the virtual products is rendered directly by controlling the piezoelectric stack actuators. A series of experiments is performed to evaluate the performance of the tactile display device. An electrical discharge machined surface is rendered using the proposed method.