<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper uses big data analysis technology to construct a digital intelligent manufacturing system. Firstly, the K-mean algorithm is used to cluster the enterprise manufacturing data, and then the fuzzy C-mean algorithm is combined to detect the abnormal data and realize the preferential selection and control of product features. A semi-parametric algorithm is introduced to establish index weights to achieve optimal resource allocation. The results show that after manufacturing enterprises produce through the digital intelligent manufacturing system, qualified products account for 82% of the total output and productivity increases by approximately 44% on average. Big data analysis technology enables enterprises to analyze data effectively and enhances the development of the manufacturing industry in the digital economy.</p>
</abstract>

This paper uses big data analysis technology to construct a digital intelligent manufacturing system. Firstly, the K-mean algorithm is used to cluster the enterprise manufacturing data, and then the fuzzy C-mean algorithm is combined to detect the abnormal data and realize the preferential selection and control of product features. A semi-parametric algorithm is introduced to establish index weights to achieve optimal resource allocation. The results show that after manufacturing enterprises produce through the digital intelligent manufacturing system, qualified products account for 82% of the total output and productivity increases by approximately 44% on average. Big data analysis technology enables enterprises to analyze data effectively and enhances the development of the manufacturing industry in the digital economy.

Path identification and effect assessment of digital economy-driven manufacturing quality development in the context of big data analysis

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper uses big data analysis technology to construct a digital intelligent manufacturing system. Firstly, the K-mean algorithm is used to cluster the...

Path identification and effect assessment of digital economy-driven manufacturing quality development in the context of big data analysis

Online veröffentlicht: 23. Okt. 2023

Seitenbereich: -

Eingereicht: 31. Dez. 2022

Akzeptiert: 03. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00764

Schlüsselwörter
Intelligent manufacturing system, K-mean algorithm, Fuzzy C algorithm, Indicator weights, Digital economy

© 2023 Yu Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Path identification and effect assessment of digital economy-driven manufacturing quality development in the context of big data analysis

Online veröffentlicht: 23. Okt. 2023

Seitenbereich: -

Eingereicht: 31. Dez. 2022

Akzeptiert: 03. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00764

SchlüsselwörterIntelligent manufacturing system, K-mean algorithm, Fuzzy C algorithm, Indicator weights, Digital economy

© 2023 Yu Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Intelligent manufacturing system, K-mean algorithm, Fuzzy C algorithm, Indicator weights, Digital economy