*3.1. System Architecture*

In general, a traditional robotic cell is composed by one or more robots, conveyor belts, the cell controller, physical safety systems, the human–machine interface (HMI), etc. If the cell is collaborative, more human factors need to be considered: safety, optimized task distribution, and human–robot interaction/adaptive control [39]. Here is where the digital twin becomes a key element for process automation design, enhanced implementation, and real-time monitoring in operation. As the digital twin mirrors real behavior, it should receive information about the movements of the robots and the other elements of the cell, including people. Therefore, additional sensors and a real-time connection between the real cell and the virtual one are necessary. Although the digital twin framework can be used afterwards to control the real manufacturing cell, it has not been considered in this work. It would only be necessary to add certain actuators in the cell which would receive the commands from the digital twin.

These components are structured and connected according to the architecture presented in Figure 2. The hardware is grouped in seven subsystems:

**Figure 2.** System architecture with the seven subsystems.


The main advantage of this architecture is its modularity. If in a future application, for example, the VR visualization is not required, this module will not be necessary. If additional capabilities are

necessary, new modules can be added to increase comprehension, intelligence, and services. Moreover, these subsystems can be developed independently and permit the integration of robots from different manufacturers in the living digital twin of the whole cell, which results in a novel and intelligent tool for design, simulation, real-time monitoring, training, and safe human–robot collaboration. These processes have been traditionally separated, which means that there was not a unique framework covering all the steps; thus different applications were necessary for each step and for each robot. The proposed approach covers all the steps with a unique application, increasing the efficiency of the automation of industrial manufacturing processes.
