The Digital Twin (DT) is a promising concept which aims at creating a virtual replica of an individual system, that can provide information otherwise not available. This paper presents a DT of a vertical transportation system, focusing on how to model this DT, and using it to evaluate the system condition and potential corrective solutions. Exploiting the advantages of object-oriented modeling, this DT has been built ensuring that it may be dynamically adapted to different monitoring scenarios. Moreover, its adaptability is tested showing that reduced models behave similarly. The resulting reduced models are used to estimate installation parameters in a bottom-up way, using the measurements of a scaled test bench. The estimated parameters are used to update a high-fidelity model and simulate the effect of corrective actions.