The widespread adoption of digital technologies in factories has resulted in the generation of a vast amount of data, which has the potential to enhance efficiency and effectiveness in the manufacturing industry. However, collecting and analyzing these data require approaches and tools to design and operate complex digital models and infrastructures, also requiring transversal competencies. The Digital Twin approach can be exploited to couple assets with their digital counterparts to support analyses and decisions. In particular, a Digital Twin can be associated with a product, a specific machine tool or process, a production system, or an entire factory. This paper focuses on the application of Digital Twins in factories, proposing a framework to identify data flows and relevant digital tools for applications throughout the different phases of the factory lifecycle. Despite the great potential, Digital Twin in manufacturing is still hindered by certain limitations. Therefore, by drawing upon relevant literature, we define and highlight the key challenges that need to be addressed. Finally, the framework and the challenges are exploited to characterize three case studies, which demonstrate the application of Digital Twins during the design and execution phases.
