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

TLDR

Automakers are adopting smart factories with cellular manufacturing systems (CMS) to meet unpredictable demand and the shift to electric vehicles, prompting a re‑examination of CMS as a future production platform. This study investigates current CMS research, identifies five key enabling technologies for automotive smart manufacturing, proposes a five‑level smart factory framework, and discusses future directions to reach higher‑level factories. The authors describe five enabling technologies—digital twins, additive manufacturing, AI‑based monitoring and inspection, human‑robot collaboration, and advanced supply chain and logistics—detailing their status, applications, and the techniques and case studies underpinning each level of the proposed framework. The resulting framework provides a technology‑level roadmap that assists researchers and industry practitioners in planning long‑term smart factory implementation and development.

Abstract

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.