## 3 Simulation Model Results
### Simulation Results  
Based on the analytical model previously developed, a simulation model of the system operation was made, using the simulation software from Tecnomatix Plant Simulation, with a 2D simulation sequence being presented in Figure 5. A digital model makes it possible to perform several scenarios, tests, or experimentation both in the design phase and in the implementation phase without directly intervening in the production process. The simulation analysis tools offered by this software allowed quick and easy interpretation of the simulation results. The simulations performed indicated the bottlenecks of the entire production process and allowed the experimentation of optimizations to ensure continuous flow in manufacturing. The input database contains the following information about the analyzed system:  
* production volume, expressed as a number of processed parts;
* generalized technological sheets for processing of the representative items to represent the generalized item of the manufacturing task (family of parts) taken into account;
* types of technological handling and processing equipment, and other specific FMS components;
* typological diversity of the items processed in the system; and
* frequency of visits of any item to any workstation in the system. Identification of Production Bottlenecks  
A major influence on the system evolution is represented by the development of disturbances (functional or organizational bottlenecks, blocking times (\(\mathrm{t_{bi}}\)), auxiliary times (\(\mathrm{t_{aux\,i}}\)),adjustment times (\(\mathrm{t_{ad\,i}}\)), the number of blockage cases (\(\mathrm{n_{bi}}\)), the frequency of blockages (\(\mathrm{f_{bi}}\)), the number of workstations (\(\mathrm{q_{k}}\)), blocking probability (\(\mathrm{p_{i}}\)), asynchrony size (\(\mathrm{\Delta t_{ik}}\)), etc., that occur in the system and can be found in the disturbing external environment (\(\mathrm{EE_{d}}\)). Unlike the input quantities in the system, for whcich the influence can be modeled by various methods, disturbances cannot be modeled and they influence the output sizes in a way that we cannot control because they are unpredictable, random, and variable in time. To prevent the disturbances from causing unwanted developments of the output sizes, the system is provided with a feedback loop. For the analyzed manufacturing system, the bottlenecks in production were identified. The diagram in Figure 6 shows the results collected during the simulation. Advanced analytical tools, such as bottlenecks analysis, statistics, and diagrams, can be used to perform different production scenarios. In this way, the resources at the level of the manufacturing process can be optimized. Figure 5: Simulation model 2D: A intermediate sequence. The simulation results showed that it is possible to increase the reduced capacity of the process by adding another parallel workstation for the operation that induces the biggest bottleneck. In the analyzed process, it is the grinding station of the bearing rings (\"Parallel Station\" in Figure 6). In Figure 6, small charts are shown over each station showing the amount of time that the station spends in each state. The diagram can be analyzed as time spent in each work station in each state, with the following colors:  
* gray bar--waiting, green bar--working, and yellow bar--blocked;
* red bar--failed and blue bar--paused. Statistical analysis of each workstation performed for the entire production process showed that only an average of 25% of production capacities are used. This is a phenomenon that adversely affects the dynamic operation of the system. It means that the stations are underloaded, only one being fully loaded. It is necessary to balance the production line.