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

<p>The research of quality control strategy of marine engineering using big data technology is to better promote the enterprise to reduce cost and increase efficiency. In this paper, starting from the project quality control system, a quality control risk evaluation model is constructed based on hierarchical analysis and fuzzy comprehensive evaluation by means of the fuzzy comprehensive evaluation of affiliation degree. For the model constructed based on AHP-FCR in this paper, experimental analysis of quality control influencing factors and fuzzy comprehensive evaluation examples were conducted by establishing indicators. From the influence factors, the severity of engineering personnel risk and engineering machine risk are 19.289 and 20.216, respectively, both of which are significant levels of influence. From the fuzzy comprehensive evaluation, 49.09% of the experts voted that the level of quality control risk of S Company’s offshore engineering module oilfield construction project is now low and in an acceptable state. It can be concluded that the AHP-FCR model with big data technology can realize the quality control risk assessment of offshore engineering and also provides theoretical support for companies to solve the risk.</p>
</abstract>

The research of quality control strategy of marine engineering using big data technology is to better promote the enterprise to reduce cost and increase efficiency. In this paper, starting from the project quality control system, a quality control risk evaluation model is constructed based on hierarchical analysis and fuzzy comprehensive evaluation by means of the fuzzy comprehensive evaluation of affiliation degree. For the model constructed based on AHP-FCR in this paper, experimental analysis of quality control influencing factors and fuzzy comprehensive evaluation examples were conducted by establishing indicators. From the influence factors, the severity of engineering personnel risk and engineering machine risk are 19.289 and 20.216, respectively, both of which are significant levels of influence. From the fuzzy comprehensive evaluation, 49.09% of the experts voted that the level of quality control risk of S Company’s offshore engineering module oilfield construction project is now low and in an acceptable state. It can be concluded that the AHP-FCR model with big data technology can realize the quality control risk assessment of offshore engineering and also provides theoretical support for companies to solve the risk.

Research on the quality control strategy of marine engineering based on big data technology

Applied Mathematics and Nonlinear Sciences

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

The research of quality control strategy of marine engineering using big data technology is to better promote the enterprise to reduce cost and increase...

Research on the quality control strategy of marine engineering based on big data technology

Online veröffentlicht: 30. Sept. 2023

Seitenbereich: -

Eingereicht: 28. Okt. 2022

Akzeptiert: 10. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00415

Schlüsselwörter
Hierarchical analysis, Fuzzy comprehensive evaluation, Marine engineering, Quality control, AHP-FCR model

© 2023 Jianping Yuan et al., published by Sciendo

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

Research on the quality control strategy of marine engineering based on big data technology

Online veröffentlicht: 30. Sept. 2023

Seitenbereich: -

Eingereicht: 28. Okt. 2022

Akzeptiert: 10. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00415

SchlüsselwörterHierarchical analysis, Fuzzy comprehensive evaluation, Marine engineering, Quality control, AHP-FCR model

© 2023 Jianping Yuan et al., published by Sciendo

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

Schlüsselwörter
Hierarchical analysis, Fuzzy comprehensive evaluation, Marine engineering, Quality control, AHP-FCR model