*2.1. The Concept of the Digital Twin*

The concept of the "digital twin" (DT) comes from NASA. In the early days of space exploration, they were pioneers in studying what was called "pairing technologies". Maintaining, repairing, and operating systems without physical access to them, were the challenges at that time. Indeed, the first twin was a hardware twin, and it consisted of two identical space vehicles, one in the space and the other on ground to enable engineers to better assist astronauts in orbit [15]. The use of digital twins is now very common at NASA, using a virtual environment to build and test their equipment, including spatial robots. Only after a total approval in the virtual environment, does the physical construction begin. The final result and the virtual twin are then linked through the sensors for a continuous improvement process. The general digital twin model of a product consists of the physical entities, the virtual models, and the connected data which tie physical and virtual worlds [16]. However, far away from this case, in general, current research on product lifecycle data mainly focuses on physical products rather than virtual models. The connection between physical and virtual product data is needed to support product design, manufacturing, and service [17].

Similarly to equipment or products, manufacturing systems are becoming more autonomous. They need access to realistic models and real-time information about the processes for smart production management and control [18]. The use of model-based simulation is necessary not only during design and planning, but also during the production phases for such purposes as diagnosis, control, and optimization [10]. Given the uncertainty involved during the process of machinery degradation, proper design and adaptability of a digital twin model remain challenges [19]. Digital twins can be applied from initial factory planning and design to commissioning and maintenance, giving them value throughout the production lifecycle [20,21]. The digital twin can be also used for risk prediction and prevention pertaining to operators in processing plants [22]. In this sense, robots are perfect candidates for digital twin applications.
