区块链驱动的智能制造优化

IF 2.6 3区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Simulation Modelling Pub Date : 2023-06-07 DOI:10.2507/ijsimm22-2-co10

S. Yang, M. Zhang

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引用次数: 0

摘要

智能制造自动化是未来的发展趋势，利用区块链技术优化生产资源控制是一个有意义的研究课题。现有研究存在PSCO-PC模型不统一、仿真模型灵活性不足等局限性。提出了一种新的基于区块链的智能制造PSCO-PC策略。详细介绍了PSCO-PC模型，提高了仿真系统功能匹配的合理性和适用性。引入自适应难度概念来解决数据吞吐量和共识机制问题。给出了求解PSCO匹配记录最优包收益的计算步骤。实验结果验证了所提出的仿真模型和PSCO-PC策略的有效性。（

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Blockchain-Driven Optimization in Intelligent Manufacturing

Intelligent manufacturing automation is a future trend, and optimizing production resource control using blockchain technology is a meaningful research topic. Existing studies have limitations, such as varying PSCO-PC models and insufficient flexibility in simulation models. This paper proposes a novel blockchain-based PSCO-PC strategy for intelligent manufacturing. It details the PSCO-PC model, improving the matching rationality and applicability of simulation system functions. The adaptive difficulty concept is introduced to address data throughput and consensus mechanism issues. Calculation steps for solving the optimal package revenue of PSCO matching records are provided. Experimental results confirm the effectiveness of the proposed simulation model and PSCO-PC strategy. (

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来源期刊

International Journal of Simulation Modelling ENGINEERING, INDUSTRIAL-ENGINEERING, MANUFACTURING

CiteScore

4.80

自引率

27.60%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Simulation Modelling (IJSIMM) provides a global forum for the publication of all forms of simulation modelling research work in academic institutions, in industry or in consultancy. The editors of the IJSIMM are searching primarily for original, high-quality, truly insightful, theoretical and application-oriented research papers dealing with simulation modelling, mainly within discrete-event simulation field in production engineering or industrial engineering.