Information modeling for cyber-physical production system based on digital twin and AutomationML

Abstract

Production systems play an important role in intelligent manufacturing. A large number of manufacturing resources are designed and developed with virtual (digital) ones, which will be associated with the physical ones throughout their lifecycle. With the recent emergence of information and communications technologies (ICTs), such as internet of things, big data, virtual reality, artificial intelligence, and 5G, the interconnection and interaction between physical resources and virtual ones become possible in production systems. Digital twin (DT) shows great potential to realize the cyber-physical production system (CPPS) in the era of Industry 4.0. In this paper, we present our vision on integrating various physical resources into CPPS via DT and AutomationML. To elaborate on how to apply ICTs, this paper firstly explores a generic architecture of CPPS based on DT. DT is a virtual and authoritative representation of physical manufacturing resource, since DT includes various models and manufacturing big data of resource. The proposed architecture is illustrated in detail as follows: (1) physical layer, (2) network layer, (3) virtual layer, and (4) application layer. A case of expert fault diagnose for aircraft engine is presented using the proposed information fusion in the architecture. Secondly, this paper proposes an approach of information modeling for CPPS based on AutomationML. Various manufacturing services can be encapsulated and defined in the standardized format (AutomationML), and then the corresponding virtual manufacturing resources (DTs) will be integrated into CPPS. Finally, this paper describes a case of information modeling for blisk machining and demonstrates the modeling approach in real-life scenarios for support manufacturing resource sharing via DT. Furthermore, the conclusion and further work is briefly summarized.