Analysing the Value of Digital Twinning Opportunities in Infrastructure Asset Management

• Type: Article in International Scientific Journal
• Date: 2024-09-11

Authors

João Vieira (Author) Other; Nuno Marques de Almeida (Author) Other; João Poças Martins (Author) FEUP; Hugo Patrício (Author) Other; João Morgado (Author) Other

Journal

Title: Infrastructures

Pages: 158-158

Publisher: MDPI

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-016-X2J

DOI: 10.3390/infrastructures9090158

Abstract (EN): Many studies and technology companies highlight the actual or potential value of Digital Twins, but they often fail to demonstrate this value or how it can be realised. This gap constitutes a barrier for infrastructure asset management organisations in their attempt to innovate and incorporate digital twinning opportunities in their decision-making processes and their asset management planning activities. Asset management planning activities often make use of existing value-based decision-support tools to select and prioritise investments in physical assets. However, these tools were not originally designed to consider digital twinning investments that also compete for funding. This paper addresses this gap and proposes a value-based analysis for digital twinning opportunities in infrastructure asset management. The proposed analysis method is tested with three rail and road infrastructure case studies: (i) real-time monitoring of a power transformer; (ii) BIM for the design, construction, and maintenance of a new railway line; and (iii) infrastructure displacement monitoring using satellite data (InSAR). The study shows that the proposed method provides a conceptual construct and a common language that facilitates the communication of digital twinning opportunities in terms of their relevance in different contexts. The proposed method can be used to support the investment decision-making process for investments in both physical and non-physical assets and help derive maximum value from the limited available resources.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 25