An approach for semi-automated data quality assurance within BIM models

Abstract Successful Building Information Modelling (BIM) enabled projects that require large volumes of project data to be embedded within BIM models. However, with this wealth of data, relevance and accuracy have been identified as important issues affecting the BIM performance of the project. Currently, Quality Assurance (QA) in the industry has focused on geometric data, including scrutinising physical and spatial clashes. However, as BIM practices progress in the industry, the requirements for nongeometric model data and their quality have become more necessary. This study aimed to ascertain the feasibility of using visual programming for semi-automating the BIM QA process in a practical case study on using BIM in infrastructure projects. This paper outlines a generic semi-automated QA methodology and its application in a construction project case study. The validity of this method was tested and evaluated in practice through (n=2) workshops. The methodology was implemented within an integrated engineering consultancy, employing visual programming methodology to generate QA summaries and additionally highlight model elements with data quality issues based on a defined set of parameters. Based on the evaluation findings, the proposed process was feasible and provided a pathway for low-cost and low-skill QA of BIM model data within the architecture, engineering and construction (AEC) industry. The paper’s main scientific contribution is a conceptual framework for using visual programming to achieve automatic quality assurance.