Digital Twins in maintenance and asset management: evidence on the technology adoption from scientific literature and patents

The paper aims to assess the state of the art on adopting Digital Twins in maintenance and asset management. The research subject is scientific publications and patents in the indicated fields of interest, which have been included in publicly available databases such as Scopus and Google Patents. The paper aims to identify the current state of research and assess the trend regarding the growth rate of publications and patents from 2017 to 2024. The research method includes collecting relevant data and fitting them to S-curves using Fisher-Pry and Gompertz models. In addition, the collected publications are evaluated in terms of a general overview of topics and country of origin. The results provide high-level information about the current status of Digital Twin technology; in particular, they indicate that the technology diffusion is nowadays completing the slow growth phase (i.e., the initial stage) and is gradually entering the acceleration phase (i.e., the fast growth stage). The results should be extended by additional analyses in future research: the content analyses of topics in publications and patents should be detailed to assess the functionalities of Digital Twins in maintenance and asset management that could be promising for applications to innovate the industrial practice