Title: Intelligent manufacturing system based on data mining algorithm

Authors: Xiaoya Liu; Qiongjie Zhou

Addresses: School of Business, Xinyang Vocational and Technical College, Xinyang 464000, Henan, China ' School of Management, Wuhan Donghu University, Wuhan 430212, Hubei, China

Abstract: This article focuses on the evaluation model of intelligent manufacturing system based on data mining algorithm. Combining data mining algorithm with intelligent manufacturing system, the evaluation model of intelligent manufacturing system is established successfully. According to the characteristics of intelligent manufacturing system, the data is divided into training set, cross-validation set and test set, and then the training set is used to perform neural network training, adjustment and optimisation and verification set. The experiment found that the accuracy rate of the training group was higher than that of the test group, the highest accuracy rate of the training group was 69%, and the highest accuracy rate of the test group was 32.5%. The results show that using data mining algorithms for recognition can effectively cluster control chart patterns and improve recognition efficiency.

Keywords: data mining algorithm; intelligent manufacturing system; evaluation model; error analysis.

DOI: 10.1504/IJGUC.2021.119554

International Journal of Grid and Utility Computing, 2021 Vol.12 No.4, pp.396 - 405

Received: 30 Jul 2020
Accepted: 31 Aug 2020
Published online: 09 Dec 2021 *

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