## 4 Discussion  
Based on the knowledge learned from the long-term research in the field and the practical experience gained in dealing with the projects in the industry, we can anticipate the development of simulation environment requirements for the factories of the future. Due to the fast onset of solutions of Industry 4.0 and the extensive use of sensors the main task for future simulation environments is the ability to model and simulate the behaviour of complex systems. When using a large number of sensors, processing data in real-time and the autonomous  
Figure 13: Example of the ANN training process. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**X1** & **X2** & **Y1-Simulation** & **Y1-ANN** \\ \hline
17 & 5 & 268.51 & 268.6991 \\
18 & 9 & 387.27 & 387.7591 \\
22 & 4 & 185.78 & 196.6634 \\
27 & 11 & 338.75 & 338.5108 \\
29 & 14 & 379.01 & 378.5756 \\
35 & 10 & 262.80 & 262.2215 \\
38 & 16 & 345.35 & 344.4772 \\
42 & 6 & 153.04 & 154.3730 \\
46 & 18 & 328.02 & 327.5044 \\
51 & 13 & 240.94 & 241.3330 \\
58 & 17 & 267.40 & 266.8995 \\
63 & 7 & 124.98 & 125.6077 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of the results of the simulation and trained ANN. behaviour of the elements of the manufacturing system, the factories of the future will experience emergent phenomena. This change will cause the simulation systems today to be used to simulate an emerging complexity. Therefore, one of the crucial tasks for the creators of simulation systems will be to develop solutions to simulate complexity in manufacturing systems. For the dynamism of the autonomous behaviour of the elements of manufacturing systems, the principles of multi-agent systems can be used in simulations, which today represents the agent simulation. Another suggested development will be the effort to \"simplify\" complex problems, in which way, one of the routes can be the use of simulation metamodelling. Several types of research work addressed in our department declare this development trend. One of the crucial requirements for a new simulation environment will be its ability to offer the functionality of the emulatory environment. The integration of the real manufacturing system with its digital and virtual models will enable both offline and online optimisation, and the simulation will become part of real-time control systems. The future simulation environment will naturally reflect the requirements of the factory of the future. In its creation, all modelling and statistical support tools, which are now commonly used in the simulation, will be used. However, this will fundamentally change the way the simulation is implemented. Three main approaches to simulations (event orientations, process orientation and activity orientation) have traditionally been used, while new simulation algorithms will be built on distributed, autonomous principles. Due to the requirement for the reconfigurability of manufacturing systems, new simulation systems will have to offer entirely new functionalities and thematic templates, as shown in the example of the research and development of the agent simulator for future hospitals or the development of a multi-agent control (and simulation) system of complex logistics systems. Methods and tools supporting the transformation of physical systems into virtual ones are evolving. The dynamics of the development of such systems are displayed in Figure 14.  
As to further perspectives for the development of modelling and simulation in factories of the future, the Department of Industrial Engineering sees, in the following period, further integration of the various industrial engineering methods and tools used in the industry into computer simulation software tools. The concept of planning and control of future factories, through the use of computer simulations, forecasting of demand and monitoring of enterprise performance indicators (e.g., productivity), must also be developed within the framework of the approach mentioned above.