# A Five-Step Approach to Planning Data-Driven Digital Twins for Discrete Manufacturing Systems
## 4 Results and Discussion
### Discussion  
According to the literature and the results, the presented approach is very useful and suitable for different types and sizes of manufacturing systems. The approach is especially useful for discrete manufacturing systems, which sometimes impose limitations. In our case, the results were based on a linear assembly line with different building blocks.  
In the first step of the approach, the manufacturing building blocks were classified into four groups. The results show that each building block of the manufacturing system can be classified into one group. Unlike the paper [22], where the building blocks of the manufacturing system were divided into three groups, we used four groups. This division  
Figure 18: Visualization of the processes for the case study for different building blocks in the fourth scenario: (**a**) Machine vision, (**b**) Robot 1, (**c**) Assembly station 1, and (**d**) WBPFP.  
proved to be very useful, as we described each building block with its own parameters that we need in the following steps.  
In the second step, we defined all the processes in the manufacturing system. The result of the second step is a sequence of processes that follow from the first process (start of assembly) to the last process (the product is stored in the warehouse). We have developed a functional diagram that includes only the most important information about the processes.  
The result of the third step is the definition of the parameters for each building block. Based on the parameters and already established methods for planning digital models, a digital model of the manufacturing system was created. The focus of this step is on defining the appropriate parameters rather than developing the digital model. The detailed procedure of developing a digital model is presented in other papers [46; 47]. Using the aforementioned papers and [16; 24], we found that there is a lack of approaches to defining parameters. The papers talk about data management, data transfer, data storage in general, but do not define exactly which parameters are required for a comprehensive description of the manufacturing system. The results of this step clearly show which parameters are needed to develop a digital model of the conveyor belt. By defining the parameters in this way, we can describe different sizes, types and shapes of the conveyor belt, regardless of the simulation software tool used.  
The result of the fourth step is the connection of the digital model to the real manufacturing system, thus establishing a digital twin with automatic data transmission and two-way communication. Although several attempts to establish a digital twin [30; 31; 32; 33; 34] can be found in the literature, the presented literature does not give a clear answer on what data needs to be exchanged and in what form. In our approach, the digital twin obtains data from a real system with inductive sensors, a camera and RFID tracking technology. The example shows the setup and operation of a digital twin. Various digital agents play an important role in the operation of the digital twin.  
The fifth step focuses on the visualization of the real manufacturing system. Nowadays, visualization is very important for different participants, from operators to management. The presented visualization shows a combination of results from a real manufacturing system enriched with data from the digital twin. A significant advantage is that the digital twin is the same for all participants, only the interpretation of the results is different. There are many studies in the literature that focus on process visualization [26; 28], but there is a lack of comprehensive representations of visualization for different participants. This resonates with our reasons we developed the visualization the way we did.