Abstract
With the rapid increase of multi-source heterogeneous dynamic data of mechanical products, the digital twin technology is considered to be an important method to realize the deep integration of product data and intelligent manufacturing. As a digital archive of the physical entity in entire life cycle, the mechanical product digital twin model is cross-phased and multi-domain. Therefore, safe and stable cooperative modeling has become a basic technical problem that needs to be solved urgently. In this paper, we proposed a blockchain-based collaborative modeling method for the digital twin ontology model of mechanical products. First, an authorization network was constructed among stakeholders. Then modeling processes of the digital twin were mapped to ontology operations and formatted through extensible markup language. Finally, consensuses were obtained based on practical byzantine fault tolerance. And a material modification process of a helicopter damper bearing was taken as an example to verify. The proposed method enables all participants to accurately obtain the latest state of the digital twin model, and has the advantages of tamper-proof, traceability, and decentralization.
Highlights
With the development of the new generation of information and communication technology, digitization and networking have made the acquisition, use, control and sharing of data faster and cheaper
Since the rapid increase of multi-source heterogeneous dynamic data throughout the life cycle of mechanical products has become an important feature of intelligent manufacturing, these data have broad application prospects in various stages of the product, such as design, manufacturing, operation and maintenance
As a digital archive of product in the entire life cycle, the digital twin model has complex content with a long developing cycle, so this process is generally inseparable from cooperation
Summary
With the development of the new generation of information and communication technology, digitization and networking have made the acquisition, use, control and sharing of data faster and cheaper. As an important method for realizing the dynamic integration of product multi-source heterogeneous data and the deep integration of cyber-physical systems, digital twin technology has attracted increasing attention from scholars and the industry [1]. In order to better express the multidisciplinary and multi-domain coupling and interaction of mechanical products, ontology as a general knowledge representation method, its application in digital twin modeling has become one of the current research directions. Based on this method, the modeling of mechanical product digital twin can be realized by operating the nodes and edges of its ontology model.
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