[연구] 석사과정 김진엽, SCI 논문지(MDPI applied sciences/Q2) 게재
- 스마트팩토리융합학과
- 조회수5487
- 2022-07-29
석사과정 김진엽 학생(지도교수: 정종필)의 연구(Design and Implementation of an HCPS-Based PCB Smart Factory System for Next-Generation Intelligent Manufacturing)가 MDPI applied sciences(Impact Factor: 2.838 (2021); 5-Year Impact Factor: 2.921 (2021))에 게재됐다.
https://www.mdpi.com/2076-3417/12/15/7645 / https://doi.org/10.3390/app12157645
논문요약 - The next-generation intelligent smart factory system that is proposed in this paper could improve product quality and realize flexible, efficient, and sustainable product manufacturing by comprehensively improving production and management innovation via its digital network and intelligent methods that reflect the characteristics of its printed circuit board (PCB) manufacturing design and on-site implementation. Intelligent manufacturing systems are complex systems that are composed of humans, cyber systems, and physical systems and aim to achieve specific manufacturing goals at an optimized level. Advanced manufacturing technology and next-generation artificial intelligence (AI) are deeply integrated into next-generation intelligent manufacturing (NGIM). Currently, the majority of PCB manufacturers are firms that specialize in processing orders from leading semiconductor and related product manufacturers, such as Samsung Electronics, TSMC, Samsung Electro-Mechanics, and LG Electronics. These top companies have been responsible for all product innovation, intelligent services, and system integration, with PCB manufacturers primarily playing a role in intelligent production and system integration. In this study, the main implementation areas were divided into manufacturing execution system (MES) implementation (which could operate the system using system integration), data gathering, the Industrial Internet of Things (IIoT) for production line connection, AI and real-time monitoring, and system implementation that could visualize the collected data. Finally, the prospects of the design and on-site implementation of the next-generation intelligent smart factory system that detects and controls the occurrence of quality and facility abnormalities are presented, based on the implementation system.