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

<p>In the field of architectural decoration engineering, construction quality control is the main issue, which has a significant impact on project safety, cost and schedule. Under the background of the increasing maturity of big data technology, its application in the quality control of architectural decoration engineering has become a new trend in the industry, which is expected to improve quality management through technological innovation. This study analyzes the construction quality control measures of architectural decoration projects using big data technology to improve the efficiency and effectiveness of project quality management. The study utilizes PDCA and SDCA quality control theories, BIM technology, and extensive data analysis to fully monitor and assess the construction process of building decoration projects. The construction quality control mode using big data technology performs significantly better in improving project quality than traditional mode. The project’s second phase adopts the new model, and its construction quality score is higher than that of the first phase by more than 5 points on average, and the frequency of quality problems is reduced by 23%. A multi-layer fuzzy comprehensive evaluation model evaluates the quality control effect, and the construction quality control effect is rated as “excellent” with an affiliation value of 62.1%. The introduction of data technology significantly improves the efficiency and effectiveness of construction quality control in architectural decoration projects, and provides an effective management model for the industry.</p>
</abstract>

In the field of architectural decoration engineering, construction quality control is the main issue, which has a significant impact on project safety, cost and schedule. Under the background of the increasing maturity of big data technology, its application in the quality control of architectural decoration engineering has become a new trend in the industry, which is expected to improve quality management through technological innovation. This study analyzes the construction quality control measures of architectural decoration projects using big data technology to improve the efficiency and effectiveness of project quality management. The study utilizes PDCA and SDCA quality control theories, BIM technology, and extensive data analysis to fully monitor and assess the construction process of building decoration projects. The construction quality control mode using big data technology performs significantly better in improving project quality than traditional mode. The project’s second phase adopts the new model, and its construction quality score is higher than that of the first phase by more than 5 points on average, and the frequency of quality problems is reduced by 23%. A multi-layer fuzzy comprehensive evaluation model evaluates the quality control effect, and the construction quality control effect is rated as “excellent” with an affiliation value of 62.1%. The introduction of data technology significantly improves the efficiency and effectiveness of construction quality control in architectural decoration projects, and provides an effective management model for the industry.

Analysis of Construction Quality Control Measures of Building Decoration Engineering Based on Big Data Technology

Applied Mathematics and Nonlinear Sciences

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

In the field of architectural decoration engineering, construction quality control is the main issue, which has a significant impact on project safety, cost...

Analysis of Construction Quality Control Measures of Building Decoration Engineering Based on Big Data Technology

Online veröffentlicht: 01. Apr. 2024

Seitenbereich: -

Eingereicht: 07. Feb. 2024

Akzeptiert: 16. Feb. 2024

DOI: https://doi.org/10.2478/amns-2024-0834

Schlüsselwörter
Architectural and Decorative Engineering, Industrial Quality Control, Data Technology, Control Theory

© 2024 Ying Hong et al., published by Sciendo

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

Analysis of Construction Quality Control Measures of Building Decoration Engineering Based on Big Data Technology

Online veröffentlicht: 01. Apr. 2024

Seitenbereich: -

Eingereicht: 07. Feb. 2024

Akzeptiert: 16. Feb. 2024

DOI: https://doi.org/10.2478/amns-2024-0834

SchlüsselwörterArchitectural and Decorative Engineering, Industrial Quality Control, Data Technology, Control Theory

© 2024 Ying Hong et al., published by Sciendo

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

Schlüsselwörter
Architectural and Decorative Engineering, Industrial Quality Control, Data Technology, Control Theory