A systematic development method for cyber-physical machine tools. (July 2018)

• Record Type: Journal Article
• Authors: Liu, Chao; Vengayil, Hrishikesh; Zhong, Ray Y.; Xu, Xun
• Is Part Of: Journal of manufacturing systems. Volume 48(2018)Part C
• Page Start: 13
• Page End: 24
• Publication Date: 2018-07
• Subjects: Machine tools -- Machine tool 4.0 -- Cyber-physical systems -- Cyber twin -- MTConnect; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2018.02.001
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: A systematic development method for Cyber-Physical Machine Tools. Generic system architecture to advance existing CNC to Cyber-Physical Machine Tools. Machine Tool Cyber Twin as the core of Cyber-Physical Machine Tools. Abstract: Machine Tool 4.0 introduces a new generation of machine tools that are smarter, well connected, widely accessible, more adaptive and more autonomous. Cyber-Physical Machine Tools (CPMT), based on recent advancements of the Information and Communication Technology, provides a promising solution for Machine Tool 4.0. This paper proposes a systematic development method for CPMT. Generic system architecture is developed to provide guidelines for advancing existing Computer Numerical Control (CNC) machine tools to CPMT. The proposed architecture allows machine tool, machining processes, real-time machining data and intelligent algorithms to be deeply integrated through various types of networks. The development methodologies for the core of the CPMT, the Machine Tool Cyber Twin (MTCT), are studied and discussed in detail. MTCT enables different types of feedback loops among the physical world, the cyber space and humans to be realized. An MTConnect-based CPMT prototype is developed to validate the proposed CPMT. Experimental results have proved great interoperability, connectivity and extensibility of the proposed CPMT. The potential of implementing artificial intelligence in CPMT is also discussed.