• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.27-37
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• 2021

The use of additive manufacturing processes for the repair and remanufacturing of mechanical parts has attracted considerable attention because of strict environmental regulations. Directed energy deposition (DED) is widely used to retrofit mechanical parts. In this study, finite element analyses (FEAs) were performed to investigate the influence of the substrate phase and inclination angle on the heat transfer characteristics in the vicinity of Hastelloy X regions deposited via DED. FE models that consider the bead size and hatch distance were designed. A volumetric heat source model with a Gaussian distribution in a plane was adopted as the heat flux model for DED. The substrate and the deposited powder were S45C structural steel and Hastelloy X, respectively. Temperature-dependent thermal properties were considered while performing the FEAs. The effects of the substrate phase and inclination angle on the temperature distributions and depth of the heat-affected zone (HAZ) in the vicinity of the deposited regions were examined. Furthermore, the influence of deposition paths on depths of the HAZ were investigated. The results of the analyses were used to determine the suitable phase and inclination angle of the substrate as well as the appropriate deposition path.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.330-335
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• 2000

This paper deals with sensing ability of smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the two type of smart sensors for experiment. The first type of smart sensor is H2 type. The second type of smart sensor is HH type. The smart sensor was developed for recognition of material. And then we developed estimation method of sensing ability of smart sensors. The first method(Sensing Ability Index) is developed for H2 smart sensor. The second method($R_{SAI}$ Index) is developed for HH smart sensor. We estimated sensing ability of smart sensor with new SAI and $R_{SAI}$ method. This paper describes our primary study for a new method of estimate sensing ability of smart sensor, which is need for precision work system. This is a study of dynamic characteristics of smart sensor according to frequency and displacement changing with new SAI and $R_{SAI}$ method. Experiment and analysis are executed for proper dynamic sensing condition. First, we developed advanced smart sensors. Second, we develop new SAI and $R_{SAI}$ methods that have a sensing ability of distinguish materials. Dynamic characteristics of smart sensor are evaluated through new SAI and $R_{SAI}$ method relatively. We can use the new SAI and $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object(auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

• 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 the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.48-55
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• 2002

This paper deals with the sensing ability of the smart sensor that has the sensing ability to distinguish materials according to the input condition changing. This is a study of dynamic characteristics of sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. Experiments and analysis were executed to estimate ability to recognize objects according to the input condition. First, we developed the advanced smart sensor. Second, we developed the new method, which has the capability sensing of different materials. Dynamic characteristics of the smart sensor were evaluated relatively through a new $R_{SAI}$ method. According to frequency changing, influence of the smart sensor are evaluated through a new recognition index ($R_{SAI}$) that ratio of sensing ability index. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safely diagnosis of structure, etc.

• 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.

• Journal of Practical Engineering Education
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• v.13 no.3
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• pp.483-490
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• 2021

In this paper, we proposed the development of a smart factory intergrated technology education platform using smart factory based CPPS (Cyber Physical Production System) and VR (Vitrual Reality) technology and educational methods using the platform. A platform has been developed to learn how to integrate 3D digital twin and BOP (Bill of Process)-based manufacturing processes. In addition, Digital Twin established a smart factory-based integrated education platform by linking mechanical systems, digital twins, and virtual reality through the OPC-UA server. Based on this platform, the smart factory integration platform is proposed to have individual elements of the smart factory integration platform through BOP-based digital twin simulation, OPC-UA integration, MES system, SCADA system, and VR interworking.

• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.555-567
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• 2014

Over 40 years, the domestic manufacturing industry of Korea played the vital role in creating national wealth, employment and innovation in its economy. In 2011, industrial products made up 99.7 percent of exports, and formed 31.2 percent of GDP. Given those facts, the research of manufacturing systems engineering for higher manufacturing efficiency and its industrial applications have been essential for Korea's economic growth. In this paper, for celebrating the 40th anniversary of the foundation of Korea institute of industrial engineers (KIIE), the research results and its industrial applications of KIIE are reviewed and summarized in the area of manufacturing systems engineering over past 40 years. Directions of future manufacturing system and the role of industrial engineers for our continuous economic growth are also mentioned.