Chapter 11 - Fault diagnosis in digital twin manufacturing

Abstract

Modern technologies like artificial intelligence (AI), big data analytics, cloud technology, and the Internet of Things (IoT) have significantly accelerated the growth of industrial automation. Cyber-physical convergence, which manufacturers are continuously embracing, is a necessary foundation for smart production. Industry 4.0 works to encourage more autonomous intelligent processes while enhancing customer experience, cost-effectiveness, and adaptability. It needs to effectively process the information from manufacturing processes and networks to deliver on its promises. AI seems to be an excellent choice for managing all created data and assisting with automating and metrification. This article describes the digital twin (DT) as the genuine embodiment of an Industry 4.0 cyber-physical system (CPS), demonstrating the role of AI in this idea. CPS and DTs have attracted a lot of attention from researchers and practitioners as the preferred method of such integration. CPS and DTs can provide industrial systems more intelligence, robustness, and efficiency by creating feedback loops where physical processes influence cyber parts and vice versa. The fundamental ideas of a close cyber-physical link, immediate communication, performance of a system, and in-depth collaboration are similar in CPS and DTs.