DIGITAL TWIN OVERVIEW

Various definitions of Digital Twin can be found in scientific literature, industrial research, practice and several fields of application. Each definition refers to the co-existence of a physical asset and its digital counterpart, a model or set of several models. Physical assets and digital models interact and change adaptively through exchanging information and applying AI and machine learning technologies. Monitoring, simulation, testing, maintenance, integrated management, and risk analysis are areas and aims underlying the implementation of DT. In this respect, historical data sets provide the basis for the development of calculation models and prediction of future scenarios. This area represents one of the main challenges to DT deployment (table 2.1.). Discontinuities and inconsistencies in the gathering, organizing, and sharing of product lifecycle information are common features of production value chains, like the construction sector.