Optimal Production Capacity Matching for Blockchain-Enabled Manufacturing Collaboration with the Iterative Double Auction Method

The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other. In this article, a blockchain-enabled manufacturing collaboration framework is proposed, with a focus on the production capacity matching problem for blockchain-based peer-to-peer (P2P) collaboration. First, a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain. Second, an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants. Third, a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information. It facilitates automation of the matching process while protecting users' privacy via blockchain-based smart contracts. Finally, simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4% compared to the Bayesian game-based approach, makes all participants profitable, and achieves 90% fairness of enterprises.

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Publication Details

Journal
IEEE/CAA Journal of Automatica Sinica
Published
2024-10-07
DOI
https://doi.org/10.1109/jas.2024.124626
Citations
2
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.70
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article

Optimal Production Capacity Matching for Blockchain-Enabled Manufacturing Collaboration with the Iterative Double Auction Method

Feilong Lin, Cailian Chen, Zhongyu Chen, Changbing Tang et al.
2 citations
IEEE/CAA Journal of Automatica Sinica
Scheduling and Optimization Algorithms
0.70
article

Optimal Production Capacity Matching for Blockchain-Enabled Manufacturing Collaboration with the Iterative Double Auction Method

Feilong Lin, Cailian Chen, Zhongyu Chen, Changbing Tang, Ying Chen
article en
2 citations

Abstract

The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other. In this article, a blockchain-enabled manufacturing collaboration framework is proposed, with a focus on the production capacity matching problem for blockchain-based peer-to-peer (P2P) collaboration. First, a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain. Second, an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants. Third, a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information. It facilitates automation of the matching process while protecting users' privacy via blockchain-based smart contracts. Finally, simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4% compared to the Bayesian game-based approach, makes all participants profitable, and achieves 90% fairness of enterprises.

IEEE/CAA Journal of Automatica SinicaVol. 12(3)
Zhejiang Normal University (CN), Shanghai Jiao Tong University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 26%
Scheduling and Optimization Algorithms
0.70
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