Currently, quality management throughout various project stages—such as collision checks of architectural, structural, mechanical, and electrical drawings during the design phase, and delivery of design results—is primarily based on paper documents like 2D drawings, notices, and contact forms. During construction preparation, activities such as drawing reviews, design disclosures, construction measurements, and construction plan optimization also rely heavily on these traditional methods. Similarly, during construction, process control and intermediate product inspection and acceptance, as well as completion acceptance, follow the same pattern. In the operation and maintenance phase, tasks like equipment maintenance, building renovations, and demolition continue to depend on paper-based documentation. This reliance on physical documents makes information storage and retrieval cumbersome and often unclear, which can easily lead to information loss and misunderstandings.
By leveraging Building Information Modeling (BIM) technology, all stakeholders can use a visual platform to better understand design intent, anticipate potential quality management issues, and enhance the predictability and control of construction project quality. This collaborative approach enables more efficient workflows and teamwork among all parties involved, ultimately improving the overall project quality.
BIM technology offers significant advantages in visualization, information integration, and collaboration, fundamentally transforming construction project quality management methods. It supports the comprehensive quality management concept by assisting professionals and stakeholders in managing project quality throughout the entire lifecycle. BIM changes traditional quality management approaches, effectively boosting efficiency and enhancing the predictability and controllability of construction project quality.
Often called the “source code of big data in the construction industry,” BIM defines every component and task within a project. Through the cyclical accumulation of multiple project datasets, BIM makes it easy to generate big data. As a reliable data source, BIM enables multi-dimensional extraction, storage, analysis, and value mining of quality information. This process produces essential performance indicators that feed into BIM-based quality management systems, strengthening project quality control capabilities. By integrating big data theory and analytical methods with BIM quality management principles, this approach enriches the theoretical foundation of construction project quality management.
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