A blockchain-based cooperative modeling method for digital twin ontology model of the mechanical product

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.

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Multidimensional Data Modeling and Model Validation for Digital Twin Workshop

Journal of Computing and Information Science in Engineering ◽

10.1115/1.4049634 ◽

2021 ◽

Vol 21 (3) ◽

Author(s):

Weiwei Qian ◽

Yu Guo ◽

Kai Cui ◽

Pengxing Wu ◽

Weiguang Fang ◽

...

Keyword(s):

Model Validation ◽

Production Control ◽

Data Modeling ◽

Intelligent Manufacturing ◽

Multidimensional Data ◽

Actual Behavior ◽

Digital Twin ◽

Twin Model ◽

Tensor Models ◽

Control And Management

Abstract Digital twin workshop (DTW) is an important embodiment of intelligent manufacturing in the workshop level, which enables the smart production control and management of the workshop. However, there still exist problems including data modeling and verification of digital model in the process of DTW construction. To solve these problem, multidimensional data modeling and model validation methods of DTW are proposed in this article. First, five-order tensor models for representing manufacturing elements are established to unify the data from physical workshop (PW) and virtual workshop (VW). Then, the mathematical method for verifying DTW twin model is proposed from the recessive and explicit perspective. Finally, a case study of an aerospace machining workshop is carried out to verify the operability and effectiveness of the proposed method. The case analysis shows that the proposed methods can effectively evaluate whether the twin model accurately provides the description of the actual behavior process of physical workshop, and the proposed methods have good performance.

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A Hierarchical Integrated Modeling Method for the Digital Twin of Mechanical Products

Machines ◽

10.3390/machines10010002 ◽

2021 ◽

Vol 10 (1) ◽

pp. 2

Author(s):

Menglei Zheng ◽

Ling Tian

Keyword(s):

Structural Characteristics ◽

Modeling Method ◽

Virtual Space ◽

Smart Manufacturing ◽

Multiple Sources ◽

Model Framework ◽

Digital Twin ◽

Mechanical Products ◽

Information And Communication ◽

Application Requirements

With the development of information and communication technology, massive amounts of data are generated during the entire lifecycle of mechanical products. However, their isolated and fragmented state hinders further empowerment of smart manufacturing. Digital twins have attracted considerable attention as they enable a user to rebuild all elements of a physical entity in a virtual space, targeted at the effective fusion of data from multiple sources with different formats, while its modeling method still needs further research. In this context, we propose a native, full-element digital twin modeling method for mechanical products. This ontology-based method establishes a unified and computer-understandable model framework for mechanical products by abstracting the essential content and relationships of data and by storing them in a graph database efficiently. The developed model could serve as a data center for the entire lifecycle of the product or could be combined with existing data management systems, integrating the previously isolated, fragmented, and scattered data on various platforms. In addition, the model utilizes the structural characteristics of mechanical products and is developed as a hierarchical digital mapping to better meet the application requirements. Finally, a case study of a helicopter digital twin is presented to verify the proposed method.

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