A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect. (April 2019)

• Record Type: Journal Article
• Authors: Liu, Chao; Vengayil, Hrishikesh; Lu, Yuqian; Xu, Xun
• Is Part Of: Journal of manufacturing systems. Volume 51(2019)
• Page Start: 61
• Page End: 74
• Publication Date: 2019-04
• Subjects: Cyber-Physical Machine Tools -- Machine Tool 4.0 -- Digital twin -- OPC UA -- 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.2019.04.006
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: An OPC UA-enabled Cyber-physical Machine Tool (CPMT) based on a generic OPC UA information model for machine tools. A CPMT Platform enabled by OPC UA and MTConnect. Decision-making support applications for the CPMT Platform and CPMT powered cloud manufacturing. Abstract: Cyber-Physical Machine Tools (CPMT) represent a new generation of machine tools that are smarter, well connected, widely accessible, more adaptive and more autonomous. Development of CPMT requires standardized information modelling method and communication protocols for machine tools. This paper proposes a CPMT Platform based on OPC UA and MTConnect that enables standardized, interoperable and efficient data communication among machine tools and various types of software applications. First, a development method for OPC UA-based CPMT is proposed based on a generic OPC UA information model for CNC machine tools. Second, to address the issue of interoperability between OPC UA and MTConnect, an MTConnect to OPC UA interface is developed to transform MTConnect information model and its data to their OPC UA counterparts. An OPC UA-based CPMT prototype is developed and further integrated with a previously developed MTConnect-based CPMT to establish a common CPMT Platform. Third, different applications are developed to demonstrate the advantages of the proposed CPMT Platform, including an OPC UA Client, an advanced AR-assisted wearable Human-Machine Interface and a conceptual framework for CPMT powered cloud manufacturing environment. Experimental results have proven that the proposed CPMT Platform can significantly improve the overall production efficiency and effectiveness in the shop floor.