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Key Enabling Technologies for Smart Factory in Automotive Industry: Status and Applications

Jongsuk Lee, Ping Chong Chua, Lequn Chen, Poh Huat Nicholas Ng, Yerim Kim, Qiong Wu, Sumin Jeon, Jihwan Jung, Siheon Chang, Seung Ki Moon

发表年份
2023
引用次数
67

摘要

In line with the unpredictable variety of demands and acceleration into the electric vehicle era, automakers have efforted on smart factories utilizing new manufacturing platforms with a cellular manufacturing system (CMS). Research on the CMS has been underway for a long time, but with the rapid development of state-of-the-art technologies, the CMS has begun to be re-examined as a future production platform in an automotive industry. In this paper, we investigate current research on CMS and identify five key enabling technologies for smart manufacturing in the automotive industry. Digital twins, additive manufacturing, AI-based monitoring and inspection, human-robot collaboration, and advanced supply chain and logistics are selected and described with status and applications. Moreover, a five-level framework is proposed for an automotive smart factory (SF) based on the essential keywords from the trend of each technology. The proposed levels are described with necessary techniques and application cases comprehensively. Lastly, based on the framework, the future direction of technologies to achieve a higher-level SF is discussed. The proposed SF level framework can help research and industry practitioners to identify the technology-level-based roadmap required for long-term planning for smart factory implementation and development.

关键词

Automotive industryManufacturing engineeringFactory (object-oriented programming)Key (lock)Industry 4.0Supply chainTechnology roadmapComputer scienceEngineeringSystems engineering

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