• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.64-70
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• 2021

The future society will be changed through an artificial intelligence (AI) based intelligent revolution. To prepare for the future and strengthen industrial competitiveness, countries around the world are implementing various policies and strategies to utilize AI in the manufacturing industry, which is the basis of the national economy. Manufacturing AI technology should ensure accuracy and reliability in industry and should be explainable, unlike general-purpose AI that targets human intelligence. This paper presents the future shape of the "autonomous factory" through the convergence of manufacturing and AI. In addition, it examines technological issues and research status to realize the autonomous factory during the stages of recognition, planning, execution, and control of manufacturing work.

• Korean Journal of Materials Research
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• v.6 no.12
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• pp.1199-1212
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• 1996

본 연구는 주조성, 내압성, 내열성 등이 우수하여 군용 및 민수용 기계소재로 이용되고 있는 AI-Si-Mg계 AC4C 합금에 세라믹(AI2O3, AI2O3-TiC)을 강화시키는 복합재료제조에 관한 기초연구의 일환으로 수행하였다. 연구내용은 세라믹 강화재의 젖음성을 높이기 위하여 수소환원법에 의한 AI2O3입자의 Ni 피복과 기존의 프리폰 제조방법보다 간단하고 경제적인 자전연소합성법에 의해 AI2O3-TiC 다공성 pellet을 제조하여, 이들 강화재와 AC4C 기지금속을 이용하여 고대-compocasting 및 squeeze casting법으로 복합재료를 제조하고 미세조직, 계면생성물, 기계적 성질, 내마멸성 등의 특성을 조사하였다. 고대-compocasting법에 의해 제조된 AI2O3Ni 입자 강화 복합재료에서 강화재들은 응집체로 존재하지 않고 비교적 균일하게 분산되었고 AI2O3-TiC 강화재를 이용하여 squeeze casting으로 가압주조 하므로써 기지금속과 강화재의 젖음성이 향상되었다.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.647-664
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• 2022

Purpose: The purpose of this study is to derive major policies that domestic small and medium-sized manufacturing companies should consider to maximize productivity and quality improvement by utilizing manufacturing data and AI, and to find priorities and implications. Methods: In this study, domestic and international issues and literature review by country were conducted to derive major considerations such as manufacturing AI technology, manufacturing AI talent, manufacturing AI data and manufacturing AI ecosystem. Additionally, the questionnaire survey targeting 46 experts of manufacturing data and AI industry were conducted. Finally, the major considerations and detailed factors importance were derived by applying the Analytic Hierarchy Process (AHP). Results: As a result of the study, it was found that 'manufacturing AI technology', 'manufacturing AI talent', 'manufacturing AI data', and 'manufacturing AI ecosystem' exist as key considerations for domestic manufacturing AI. After empirical analysis, the importance of the four key considerations was found to be 'manufacturing AI ecosystem (0.272)', 'manufacturing AI data (0.265)', 'manufacturing AI technology (0.233)', and 'manufacturing AI talent (0.230)'. The importance of the derived four viewpoints is maintained at a similar level. In addition, looking at the detailed variables with the highest importance for each of the four perspectives, 'Best Practice', 'manufacturing data quality management regime, 'manufacturing data collection infrastructure', and 'manufacturing AI manpower level of solution providers' were found. Conclusion: For the sustainable growth of the domestic manufacturing AI ecosystem, it should be possible to develop and promote manufacturing AI policies in a balanced way by considering all four derived viewpoints. This paper is expected to be used as an effective guideline when developing policies for upgrading manufacturing through domestic manufacturing data and AI in the future.

• Industry Promotion Research
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• v.9 no.3
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• pp.101-117
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• 2024

This study empirically analyzed the factors affecting the intention to utilize manufacturing AI in SM-sized manufacturers by applying the TOE framework. Independent variables that are expected to influence were applied, focusing on TOE factors and managerial characteristics that reflect the characteristics of SME manufacturers. In addition, the mediating effect of technology trust and the moderating effect of factory location were analyzed. The results are as follows. First, the relationship between the independent variables and the dependent variable was tested, and the direct effects of the independent variables(complexity, organizational innovation, IT ability, competitive pressure, partner support, and managerial innovation) on the dependent variable were all statistically significant, except for compatibility. Second, the mediation effect of technology trustness was verified to have a full mediation effect between compatibility and utilization intention, and a partial mediation effect between managerial innovation and utilization intention. Third, among the seven independent variables, the moderating effect of factory location(metropolitan and non-metro) between the three independent variables of IT ability, competitive pressure, and partner support and the utilization intention was found to be significant. To increase the intention to utilize manufacturing AI for SM-sized manufacturers, it is recommended that more diverse and broader studies are needed, not only the factors identified in this study, but also the understanding and awareness of manufacturing AI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.471-477
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• 2021

In the field of display, a smart factory means more efficient display manufacturing using AI/BIG DATA technology not only for job automation, but also for existing process management, moving facilities, process abnormalities, and defect classification. In the past, when defects appeared in the display manufacturing process, the classification of defects and coping with process abnormalities were different, a lot of time was consumed for this. However, in the field of display manufacturing, advanced process equipment must be used, and it can be said that the competitiveness of the display manufacturing industry is to quickly identify the cause of defects and increase the yield. In this paper, we will summarize the cases in which smart factory AI/BIG DATA technology is applied to domestic display manufacturing, and analyze what advantages can be derived compared to existing methods. This information can be used as prior knowledge for improved smart factory development in the field of display manufacturing using AI/BIG DATA.

• Korean Journal of Materials Research
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• v.6 no.11
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• pp.1090-1098
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• 1996

개조한 가스 금속 아아크 용접공정을 이용하여 SiC/AI 금속기 복합재료를 제조하고 그 특성을 조사하였다. AI 모재위에 강화입자의 크기와 부피분율을 변화하여 다양한 SiC/AI 복합재료층을 제조하였고, 만들어진 복합재료층의 특성은 미세조직관찰과 미소경도시험을 통하여 이루어졌다. 복합재료층의 두께는 약 7-8mm로 측정되었고 균일한 강화입자의 분포도를 얻을 수 있었다. 분산입자의 부피분률은 Ar가스의 유량에 의하여 조절하였고 분산입자의 부피분률이 증가하고 크기가 작아짐에 따라 기지의 수지상 응고조직은 더욱 미세화되었다. 복합재료의 부피경도는 분산입자의 부피분률이 감소함에 따라 낮아졌으나 입자 크기에는 크게 변화가 없는 것으로 나타났다.

• Proceedings of the Membrane Society of Korea Conference
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• 1993.04a
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• pp.34-34
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• 1993

세라믹 분리막은 유기질 막에 비하여 열적, 기계적 및 화학적으로 안정하기 때문에 기존의 유기질 막을 사용하기 어려운 작업 조건 하에서도 응용의 잠재성을 가지고 있다. 본 실험은 disk형태의 다공성 $Al_2O_3$ 담체위에 CVD 법과 Evaporation Oxidation 법에 의해 $Al_2O_3$를 코팅하여 세라믹 분리막을 제조하였다. CVD법에 의한 제조는 Al-isopropoxide를 350$\circ$C에서 담체위에 증착시켜 제조하였으며, Evaporation-Oxidation 법에 의한 제조는 Al을 담체위에 evaporation 시킨 후 dry oxidation 시켜서 제조하였다.

• Korean Journal of Materials Research
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• v.7 no.11
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• pp.951-956
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• 1997

Vacuum Hot Pressing을 이용하여 제조한 TiNi형상기억섬유 강화 6061 AI기지 복합재료를 제조하고 미세조직 및 기계적 특성 등을 연구하였다. 제조된 복합재의 항복응력은 예비변형량, 섬유체적율 및 열처리에 따라 증가하였다. 복합재의 지적특성은 예비변형이 가하여진 후 재가열되었을 때 기지 내 TiNi 섬유의 형상기억효과에 의한 압축잔류응력 발생에 기인된다. 미세조직 관찰 섬유와 기지 사이에는 AI$_{3}$Ti및 AI$_{3}$Ni의 금속간화합물층이 관찰되었다. 또한 시험온도 증가와 더불어 TiNi섬유강화된 복합재의 유동강도는 높은 값을 나타내었다.

• 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.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.2 no.2
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• pp.63-70
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• 1992

$AI_2O_3/Ca-TZP$ composites was prepared by using the starting powder of alumina and Ca-TZP synthesized by hydrothermal reaction and investigated to its characteristics. The ratio of tetragonal zirconia to monoclinic within $AI_2O_3$ matrix was decreased with an addition of Ca-TZP content, but the absolute amount of tetragonal phase in composites was increased with an addition of Ca-TZP content. The value of fracture toughness in $AI_2O_3/Ca-TZP$composites was proportional to the amounts of transformed tetragonal phase which formed by crack propagation in fracture, and therefore, it was gradually increased with an addition of Ca- TZP content.