With increasing interest in automatic and intelligent systems to enhance the building and construction industry, digital twins (DT) are gaining popularity as cost-effective solutions to meet stakeholder requirements. Comprising real-time multi-asset connectivity, simulation, and decision support functionalities, many recent studies have utilised Industry 4.0 technologies with DT systems to fulfil construction-specific applications. However, there is no comprehensive review to our knowledge, holistically examining the benefits of using DT as a platform from the angles of Industry 4.0 technologies, project management, and building lifecycle. To bridge this gap, a systematic literature review of 182 papers on DT-in-construction works over the past 6 years is conducted to address the three perspectives. In this review, a unified framework is first modelled to incorporate Industry 4.0 technologies within the DT structure. Next, a Six M methodology (comprising of Machine, Manpower, Material, Measurement, Milieu, and Method) based on Ishikawa’s Diagram with building lifecycle considerations is proposed to highlight the advantages of DT in ensuring successful construction projects. Lastly, through the identification of 11 future directions, this work aims to serve as a reference for both industry and academia towards the use of DT systems as a fundamental enabler to realise the Construction 4.0 paradigm.

With the rapid advancement in Building Information Modelling (BIM) technology to strengthen the Building and Construction (B&C) industry, effective methods are required for the analysis and improvement of as-built BIM, which reflects the completed building project and captures all deviations and updates from the initial design. However, most existing studies are focused on as-designed BIM, while the analysis and inspection of as-built BIM rely on labour-intensive visual and manual approaches that overlook interdependent relationships among components. To address these issues, we propose a network analysis-based approach for managing and improving as-built BIM. Networks are generated from geometric attributes extracted from Industry Foundation Classes (IFC) documents, and network analytical techniques are applied to facilitate BIM analysis. In addition, a practical dataset is utilised to verify the feasibility of the proposed approach. The results demonstrate that our method significantly enhances the analysis and comparison of as-built BIM from model analysis and matching. Specifically, the innovative contribution leverages global information and interdependent relations, providing a more comprehensive understanding of the as-built BIM for effective management and optimisation. Our findings suggest that network analysis can serve as a powerful tool for structure and asset management in the B&C industry, offering new perspectives and methodologies for as-built BIM analysis and comparison. Finally, detailed discussion and future suggestions are presented.