A BIM-based framework for road construction quality control and quality assurance

ABSTRACT

Large-scale data processing for road construction monitoring may significantly improve the efficiency of quality control and quality assurance (QC&QA). However, the traditional construction data storage, management and analysis methods rely on paper documents and limited electronic files, leading to the low data utilisation, fuzzy data features and data value loss. This study proposes a BIM-based road QC&QA framework, which realises the real-time construction data integration in the information model, achieves data analysis and visualisation by the combination between the model and database, and uses structured construction data for QC&QA. Specifically, a BIM-oriented method for transmitting and storing road construction data in real-time, a BIM-oriented process for integrating road construction data, and a road QC&QA model based on AHP, ANN and GA throughout the entire road construction process are involved in the proposed framework. The proposed framework was tested through a case study using data from the Xintai Highway construction project. The results showed a significant improvement in data integration, visualisation and analysis during the QC&QA process. As a result, the overall construction quality of the Xintai project exceeded 95%, providing strong evidence of the effectiveness of the proposed framework.

KEYWORDS:

• Building information model
• construction data
• data integration
• visualisation
• quality control
• quality assurance

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The study is financially supported by the National Key Research and Development Project, grant number 2020YFB1600102 and 2020YFA0714302, the National Natural Science Foundation of China, grant number 51878164 and 51922030, Southeast University ‘Zhongying Young Scholars’ Project, Postgraduate Research & Practice Innovation Program of Jiangsu Province, grant number KYCX22_0283. The authors would also like to acknowledge the financial support provided by China Road and Bridge Engineering Co., Ltd (grant number CRBC/KHM/2021/053).