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Research on a supply–demand matching method for cloud 3D printing services based on complex networks

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Abstract

With the rapid development and continual expansion of the 3D printing market and the scale of 3D printing devices, the limitations of traditional matching processing methods are becoming increasingly obvious. As a novel business paradigm, cloud 3D printing (C3DP) can effectively integrate and manage 3D printing resources. Based on this, this paper studies a dynamic and static data-based supply–demand matching method for C3DP service capability and designs a modeling framework to describe two models of a network node-matching method based on a Barabási-Albert (BA) scale-free network and a concept-matching method based on semantic similarity by model-based systems engineering. A wide array of 3D printing resource data are collected, and a task-service network based on multiobjective optimization in a dynamic hyper-network environment is used for comprehensive analysis and evaluation. The model can better extract the feature information of the multiobjective optimization by using the scheme of the real-time configuration service as well as the matching algorithm for the dynamic evolution of a manufacturing capability network and hyper-network algorithm. The results show that the supply–demand matching method for cloud 3D printing services based on complex networks has the advantages of high feasibility, high data accuracy, and high response speed, which can enhance the processing efficiency of mapping the relationships of the C3DP manufacturing capability and can improve the utilization of dynamic and static data-based supply–demand matching methods.

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Funding

This work is supported by the Natural Science Foundation of Shandong Province of China under Grant No. ZR2019PEE019, the High-Level Talents (High-Level Doctorate) Research Project of Linyi University (No. LYDX2019BS009) and the Intelligent Manufacturing Application Frontier Project Team of Wuhan City POLYTECHNIC (No. 2020whcvcTD02).

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Authors and Affiliations

  1. School of Mechanical and Vehicle Engineering, Linyi University, Linyi, 276000, China

    Chenglei Zhang, Qiushi Li, Hu Han, Jiajia Liu & Bo Xu

  2. Shandong Longli Electronic Co., Ltd, Linyi, 276000, China

    Chenglei Zhang

  3. Institute of Industrial Design and Intelligent Manufacturing, Linyi University, Linyi, 276000, China

    Chenglei Zhang & Jiajia Liu

  4. College of Mechanical Engineering and Electrical Automation, Wuhan City Vocational College, Wuhan, 437000, China

    Bo Yuan

Authors
  1. Chenglei Zhang
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  2. Qiushi Li
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  3. Hu Han
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  4. Jiajia Liu
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  5. Bo Xu
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  6. Bo Yuan
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Contributions

CZ conceived and designed the study. QL, BX, and BY performed the experiments. CZ and HHAN wrote the paper. CZ and HH reviewed and edited the manuscript. All authors read and approved the manuscript.

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Correspondence to Chenglei Zhang or Hu Han.

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Zhang, C., Li, Q., Han, H. et al. Research on a supply–demand matching method for cloud 3D printing services based on complex networks. Soft Comput 26, 13583–13604 (2022). https://doi.org/10.1007/s00500-022-07315-1

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