Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 7, Issue 12, Pages 11884-11894Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3005729
Keywords
Blockchain; Industrial Internet of Things (IIoT); Industry 40; intelligent manufacturing system (IMS); manufacturing blockchain of things (MBCoT)
Categories
Funding
- National Natural Science Foundation of China [51975463]
- Natural Science Basic Research Plan in Shaanxi Province of China [2019JM-057]
- Fundamental Research Funds for the Central Universities [xzy022019066]
Ask authors/readers for more resources
Configuring intelligent manufacturing systems (IMSs) is significant for manufacturing enterprises to take a step toward Industry 4.0. However, most current IMS is configured based on the Industrial Internet of Things (IIoT) with a centralized architecture, which results in poor flexibility to handle manufacturing disturbances and limits capacity to support security solutions. To solve the above issues, this article combines IIoT with the permissioned blockchain and proposes a novel manufacturing blockchain of things (MBCoT) architecture for the configuration of a secure, traceable, and decentralized IMS. Then, hardware infrastructures and software-defined components of MBCoT are designed to provide an insight into the industrial implementation of IMS. Furthermore, the consensus-oriented transaction logic of MBCoT is presented based on a crash fault-tolerant protocol, which empowers MBCoT with a strong but resource-efficient encryption mechanism to support the autonomous manufacturing process. Finally, the implementation of an MBCoT prototype system and its application examples justify that the proposed approach is practical and sound. The evaluation experiment demonstrates that MBCoT equips IMS with a secure, traceable, stable, and decentralized operating environment while achieving competitive throughput and latency performance.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available