Developing an IFC-Based Database for Construction Quality Evaluation

• Main Authors: Zhao Xu, Ting Huang, Bingjing Li, Heng Li, Qiming Li
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: Advances in Civil Engineering
• Online Access: http://dx.doi.org/10.1155/2018/3946051

Quality evaluation and control are increasingly important concerns in construction projects. Construction quality evaluation, as a systematic method, must be discussed in light of quality information extraction and storage, while a traditional construction quality control program cannot meet these requirements. In moving beyond quality indicators to evaluate quality performance that is comparable across construction entities, two fundamental factors must be considered: quality information standardization and multiquality data integration. The purpose of this study is to extend the interoperability of a construction quality database in the evaluation process by employing the industry foundation classes (IFC) data model. Taking a cast-in-place steel-concrete structure as an example, this study explores the implementation of building information modeling (BIM) in quality management and proposes integrated solutions to improve current quality management processes with the assistance of an IFC-based working environment. To better utilize the performance of the BIM model and database on construction quality control, various BIM-based evaluation frameworks are proposed. Also, this paper discusses how these IFC and neutral network models operate together to facilitate construction quality management. Project participants can better understand quality progress and collaborate more effectively, thanks to a visualized data format. The objective of evaluating the proposed model is to understand the effectiveness of an IFC-based database when implemented in practice. A questionnaire was developed considering the opinions of construction firms and design institutes regarding identified factors. In designing an IFC-based quality database, the method proposed in this study reduces the complexity of the database substantially and improves quality evaluation efficiency.