A study on LiDAR + BIM enhanced QA/QC workflows for precast concrete moulds - Toh, Jocelynn Yun Wen (Nanyang Technological University, 2022)
In the construction business, a real-time quality control system and early defect detection remain the most effective strategies for decreasing project schedules and cost overruns. Precast concrete moulds are currently subjected to insufficient quality assurance and quality control (QA/QC) for the following reasons: they are labour-intensive, ineffective, and prone to human error since they are produced through a manual process that necessitates both workforce and measuring devices. As a result, it is critical to automate this process through the use of digital models that combine modern technologies and processes. The goal of this research study is to create a Cloud-based system that combines Light Detection and Ranging (LiDAR) and Building Information Modelling (BIM) technologies to create a seamless on and off-site solution for the precast concrete mould QA/QC process. As part of the paper, the author analysed and presented the two main technologies, LiDAR and BIM, and demonstrated four different case studies in which (1) LiDAR is used in QA/QC processes and its limitations; (2) demonstrate the integration of LiDAR into the BIM development of staircase formwork for QA/QC processes; and (3) demonstrate the integration of LiDAR into the BIM development of staircase formwork for QA/QC processes. The proposed LiDAR + BIM QA/QC framework for precast concrete moulds was broken down into two sections: an overview of the Scan-to-BIM procedures for both onsite and offsite operations and an examination of this method applied to a precast column C3101AX mould. This paper also includes key findings and limitations of the Scan-to-BIM process. Keywords: Building Information Modelling (BIM), Light Detection and Ranging (LiDAR), Quality Assurance and Quality Control (QA/QC), Precast Concrete Mould