4.7 Article

Blockchain-based data management for digital twin of product

Journal

JOURNAL OF MANUFACTURING SYSTEMS
Volume 54, Issue -, Pages 361-371

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jmsy.2020.01.009

Keywords

Product lifecycle management; Data management; Digital twin; Blockchain technology

Funding

  1. Great Project of Ministry of Industrialization and Information of China [JCKY2016602B007]
  2. National Natural Science Foundation of China [51975056]
  3. State Scholarship Fund of the China Scholarship Council [201706030116]
  4. Graduate Technological Innovation Project of Beijing Institute of Technology [2017CX10040]

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The concept of digital twin was originally proposed to assist product lifecycle management through the high-fidelity virtual product. In product lifecycle, there are many participators constructing a complicated network with enormous product lifecycle data. It is difficult to manage data of digital twin efficiently and securely from the perspectives of data storage, data access, data sharing, and data authenticity among the complicated network. Moreover, the virtual product is always updated to the latest state of the physical product by overwriting the history virtual product that records the development process of digital twin. To address abovementioned data management problems simultaneously, a data management method for digital twin of product based on blockchain technology is proposed in this paper. A peer-to-peer network is constructed to enhance data sharing efficiency among participators. The basic structure of blockchain is introduced, including block, chain, and transaction. The blockchain is used for data storage through cryptography that ensuring only eligible participators can access the corresponding data. The change sensitive characteristic of blockchain can ensure data authenticity as well. In addition, the concept of smart contract can be used to execute some actions automatically to increase data sharing efficiency. A case study is presented to demonstrate the effectiveness of the proposed data management method. The results show that the proposed method can solve the abovementioned data management problems simultaneously.

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