A Systematic Review of Digital Twin as a Predictive Maintenance Approach for Existing Buildings in the UK

Abstract

Digital Twin (DT) developments and applications in the Architectural Engineering Construction (AEC) Industry are emerging. However, insufficient publications synthesised the existing literature on DT of existing buildings, including energy retrofit and challenges as part of Net-zero strategies. When developing DT systems, it is vital to include the existing buildings primarily captured in 2-Dimensions (2-D) static data. To date, the implementation of DT has been minimal in applications in existing buildings in the UK. Despite DT benefits for maintenance (O&M) managers, facilities management (FM) as a comprehensive source of consistent data for predictive maintenance. This study explored the challenges faced by DT adoptions in existing buildings through a systematic review of the extant literature. A systematic approach is adopted to search the Scopus database using relevant keywords such as "Digital Twin.", "Built Environment" and "Existing Buildings.". the study focused on publications from the past five years (2018 to 2023) and prioritised articles in Scopus. The findings of this paper showed that the practitioners, O&M managers, and academics in built environments need more proper knowledge and technical expertise on digital twins as part of Industry 4.0 (I4.0). Evidence from the literature resulted in low empirical case studies and applications. The complexity of real-time data integration and interoperability were highlighted as part of the challenges despite the need for comprehensive knowledge of DT in the built environment. Scarce publication on the study was noted. The directions for comprehensive solutions and future research on digital twin applications in existing buildings towards achieving efficient energy retrofits, cost reductions, and net-zero goals were highlighted