(untitled) (International Journal of Built Environment and Sustainability, 2025)
Ensuring the dimensional accuracy of constructed structures is crucial for quality control purposes in assessing whether the elements align with the design dimensions and tolerances and also to identify inconsistencies and deformations to prevent subsequent construction complications. This paper explores the integration of 3D laser scanner and Building Information Modeling (BIM) as an automated validation system for assessing dimensional quality. This method employs 3D laser scanner, point cloud registration and processing and scan-to-BIM techniques to facilitate dimensional deviation/tolerances analysis and verification. The paper presents a review of existing research on the automated dimensional quality assessment by using scientometric analysis and critical reviews. Firstly, three (3) key research themes are recognized and described based on the findings of scientometric analysis: a) reality capture to information integration, highlighting the transition from raw point cloud acquisition and registration to semantically enhanced BIM representations, b) dimensional conformance, which implements tolerance-aware comparisons between as-built data and design models to ensure traceability and compliance, and c) automation to site domain, which integrates the workflows into field application via automated system, machine learning, and deep learning to facilitate inspection, monitoring, and decision-making. Subsequently, existing assessment methodologies were evaluated and contrasted via critical review. The gaps between existing methodologies and actual needs are summarized. Finally, future directions in the field are anticipated correspondingly. Overall, this paper contributes to future research and applications concerning dimensional quality assessment through BIM application.