## 3 Simulation Model Results
### Simulation Results
The values, the percentages of these bottlenecks in the total production time, and the loading degrees of the workstations are presented in Figure 8. All material flow objects and all moving objects enter their statistics values into the _Resource Statistics Table_, the _Product Statistics Table_, or the _Complete Statistics Table_. After running the simulation, there is a relatively large dispersion of the loading degrees of the workstations in the system (21.20-100%), a feature of a flexible manufacturing system. It expresses the level at which production capacities are used. For ideal operation, it is 95-100%; the rest are auxiliary times. The lower the load levels, the higher the asynchronisms in the system and interruptions in operation. Management measures are required to reduce wait times in the system. By running simulations considering another scenario of real-time operation, improvements can be achieved. This solution has produced favorable effects in terms of balancing the production line, trying to equalize the load of workstations and ensuring a continuous flow of production (Figure 9). At this stage, in order to simplify the process, neither the input sources of the parts in the system (Source) nor the output sources of the system (Drain) were taken into account. Figure 9 shows statistics for improving workstation activity by optimizing production time and by reducing wait times in the production process. Plant Simulation opens a table that contains all values it collected during a simulation run (Figure 10). The statistics tab displays a snapshot in time. Each time that you view this tab, while a simulation is running, the statistics change. Figure 10 shows statistics obtained from optimization by increasing the working times on each workstation and by reducing the wait times in the production process. It can be seen that all of the workstations in the system work at maximum capacity (90-100%). By running the simulation and by balancing the system using several scenarios, visible improvements were obtained in terms of blockage rate and workstation loading. The presented simulation program also performs animation features of movements carried out into the flexible manufacturing line. All material flow objects and all moving objects enter their statistics values into the Resource Statistics Table, the Product Statistics Table, or the Complete Statistics Table (Siemens AG 2015, Siemens Product Lifecycle Management Software Inc., Germany [44]). Figure 8: Bottleneck Analyzer: the percentage of workstation usage. Tests that can be performed by computer simulations lead to solutions to optimize the operation of FMS and thus to eliminate bottlenecks. Among the solutions for solving and eliminating a bottleneck, the following can be mentioned: increasing the number of overtime hours, working in several shifts, arranging workstations in parallel, implementing quality control methods, implementing automations, and using modern management methods such as Lean Production, issues that will be addressed in future research projects. In many companies, there is a lack of a support framework between engineers and process information. The creation of this framework could contribute to the elimination of waste, wait times in attempts to balance production lines, and reconfiguration of the system.