Title: An integrated storage method of Industry 4.0 processing data based on big data mining

Authors: Xiaoyuan Luo; Jun Liu

Addresses: Faculty of Science, Heihe University, Heihe Heilongjiang 164300, China ' Faculty of Science, Heihe University, Heihe Heilongjiang 164300, China

Abstract: In order to overcome the problems of poor integration integrity and low storage security of traditional industrial processing data integrated storage methods, a new Industry 4.0 processing data integrated storage method based on big data mining is proposed in this paper. Firstly, the hierarchical clustering method in big data mining is used to mine processing data from Industry 4.0 data. Secondly, based on the mined processing data, the clustering attributes of different processing data are calculated to integrate clusters. Finally, Bayesian method is used to complete the integrated storage of Industry 4.0 processing data. The experimental results show that compared with the traditional integrated storage methods, the integration integrity and storage security of this method are significantly improved, and the maximum integration integrity can reach 97%.

Keywords: big data mining; Industry 4.0; processing data; integrated storage.

DOI: 10.1504/IJMTM.2023.131299

International Journal of Manufacturing Technology and Management, 2023 Vol.37 No.2, pp.115 - 125

Received: 18 Sep 2021
Received in revised form: 02 Nov 2021
Accepted: 12 Apr 2022
Published online: 06 Jun 2023 *

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