In recent years, several IT systems have been applied to collect different types of data concerning the full product lifecycle. As a result of Industry 4.0 developments, the amount of product information collected over the entire lifecycle has been growing. Information and communication technology is employed to digitally mirror the lifecycle of a corresponding physical product in Digital Twin applications. These applications are middleware architectures that apply physical world information to support real-time decisions. Therefore, a Digital Twin may be used to enhance simulation, to improve traceability, and to expand the value-added services offering along the lifecycle. However, studies on Digital Twin applications are mainly focused on the beginning of life (BOL) or manufacturing optimization. In this paper, Product Lifecycle Management (PLM) theory and Internet of Things (IoT) solutions and technologies are applied to build a Digital Twin able to collect and cast middle of life (MOL) information to the other lifecycle phases. Based on the scenario implementation in a Learning Factory, the objective is to discuss the information flow that is required for a Digital Twin to be considered for closing the information gap between the product in the use phase and other lifecycle phases. The results show how a middle of life Digital Twin can impact processes and information flow. Future research work should integrate the information of multiple IT systems from the entire product lifecycle in a comprehensive Digital Twin.