Cloud Manufacturing Dynamic Composition Reconfiguration Method Under Resource Exception

The initial production plan formulated by the cloud platform in actual production is prone to various uncertain interference such as equipment failure and order cancellation, resulting in the realization of the established production plan. Therefore, this paper proposes a dynamic reconfiguration method for cloud manufacturing resources under abnormal condition. First, the fundamental manufacturing scheme is generated ac-cording to the initial functional optimization objectives. Then, for the uncertain interference factors in the cloud manufacturing environment, three optimization strategies are used to dynami-cally reconstruct the manufacturing scheme of the interference points based on the principle of minimum change, and an improved differential evolution algorithm is used to optimize the reconstruction scheme. Finally, the effectiveness of the proposed method is verified by numerical simulation.

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Publication Details

Published
2024-08-21
DOI
https://doi.org/10.1109/iai63275.2024.10730302
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00

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article

Cloud Manufacturing Dynamic Composition Reconfiguration Method Under Resource Exception

Ting Wang, Junjie Zhu, Ziquan Yu, Youmin Zhang et al.
Digital Transformation in Industry
article

Cloud Manufacturing Dynamic Composition Reconfiguration Method Under Resource Exception

Ting Wang, Junjie Zhu, Ziquan Yu, Youmin Zhang, Bin Jiang
article en

Abstract

The initial production plan formulated by the cloud platform in actual production is prone to various uncertain interference such as equipment failure and order cancellation, resulting in the realization of the established production plan. Therefore, this paper proposes a dynamic reconfiguration method for cloud manufacturing resources under abnormal condition. First, the fundamental manufacturing scheme is generated ac-cording to the initial functional optimization objectives. Then, for the uncertain interference factors in the cloud manufacturing environment, three optimization strategies are used to dynami-cally reconstruct the manufacturing scheme of the interference points based on the principle of minimum change, and an improved differential evolution algorithm is used to optimize the reconstruction scheme. Finally, the effectiveness of the proposed method is verified by numerical simulation.

Concordia University (CA), Nanjing University of Aeronautics and Astronautics (CN)
National Key Research and Development Program of China
Decent work and economic growth
Openalex Percentile: Top 73%
Digital Transformation in Industry
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Cloud Manufacturing Dynamic Composition Reconfiguration Method Under Resource Exception — Ting Wang, Junjie Zhu, et al. · (2024) | TGRS Research Map | TGRS