Earticle

초록

영어

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.

목차

Abstract
1. Introduction
2. Manufacturing innovation and Smart Factory
2.1 Manufacturing innovation
2.2 Framework for building a Smart Factory
2.3 Factors Affecting Smart Factory Implementation
2.4 Big data analysis and visualization
3. Infrastructure construction for big data utilization
3.1 Big Data Infrastructure Building Process
3.2 Big Data Platform
3.3. Big Data Modeling
3.4. Big Data Quality Management
3.5. International Standardization Trend
3.6. Big Data Building Consulting
4. Conclusion
Acknowledgement
References

키워드

저자

• Cheolrim Kim [ Ph.D. student, Dept. Of Smart Convergence Consulting, Hansung University, Seoul, Korea ]
• Seungcheon Kim [ Professor, Dept. of IT Convergence, Hansung University, Seoul, Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380