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Applying the blockchain-based deep reinforcement consensus algorithm to the intelligent manufacturing model under internet of things

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Abstract

“Industry 4.0”, namely intelligent manufacturing (IM), includes intelligent production (IP) and smart factory (SF). The study aims to improve the efficiency of the traditional business model, reduce the production cost, and transform the commercial manufacturing mode towards automation, intelligence, and timely on-demand distribution. Accordingly, a deep reinforcement consensus algorithm (DRCA) is established by adjusting the blockchain consensus algorithm (CA) using deep reinforcement learning (DRL) to IM applications. The results show that the proposed DRCA can process data more intensively, with faster calculation, higher accuracy, and robust security. Thus, it effectively improves the decentralization performance of the blockchain system. Compared with the traditional CAs, the proposed DRCA helps implement IM accurately and rapidly. Therefore, optimizing blockchain CA by DRL can effectively and accurately guide IM development and improve the efficiency of the manufacturing industry. The experimental data provide a reference for the relevant follow-up research.

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Funding

This work was supported by the Soft Science Funded Project of Shaanxi Province (No.2020ZLYJ47).

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  1. School of Economics and Management, Xidian University, Xi’an, 710126, China

    Tongtong Geng & Yueping Du

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  1. Tongtong Geng
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  2. Yueping Du
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Correspondence to Yueping Du.

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Geng, T., Du, Y. Applying the blockchain-based deep reinforcement consensus algorithm to the intelligent manufacturing model under internet of things. J Supercomput 78, 15882–15904 (2022). https://doi.org/10.1007/s11227-022-04514-3

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  • DOI: https://doi.org/10.1007/s11227-022-04514-3

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