# Analysis of Production Process Parameters Using Computer Simulation at the Planning Stage
## 4 Results
As a result of the data obtained, generated by the simulation software, it was found that the longest production process execution time was 575 h and 46 min. The shortest duration of the simulated process was 540 h and 41 min. The discrepancy between the production process duration in the simulation software resulted from taking into account a potential delay factor of up to 5% of the operation duration. Based on the analyses performed, in five of the replications, the results showed that it was not possible to implement the production plan within the designated time interval of 562.5 h (Awt). Failure to perform a specific production batch size using the defined production resources does not indicate improper use of the method in the scope of the analytical determination of the production operation, but it did not take into account the inter-operational transport factor. As a result of the simulation performed without the use of means of transport, it was found that in each of the cases, it was possible to execute the assumed production plan, which is graphically presented in Figure 7.  
In the case of the analysis of the level of inter-operational stocks in the warehouses, it was found that in the case of warehouse number \(1\) (Queue 1) and number 3 (Queue 3)  
Figure 6: Simulation of the production process in the FlexSim simulation software. Figure 7: Duration of the production process based on the obtained simulation results. there is a high level of inter-operational stocks at the level of 97-99% of the duration of the manufacturing process (Figure 8). The highest percentage level of the utilization of the production stations was recorded for Operations 20 (turning process--station PO_20_1 \(\div\) 5) and 40 (polishing--station PO_40_1) and amounted to approximately 97% (Figure 9). The results obtained in terms of the high level of use of inter-operational warehouses and stations performing Operation 20 (turning process) and 40 (polishing) indicate the occurrence of a bottleneck in the manufacturing process. The occurrence of a bottleneck in the manufacturing process may result in a decrease in process efficiency, while increasing production costs. In the case analyzed, the total cost of the production process amounted to USD 207,110.4. In the fourth stage of the methodology, it was decided to implement additional production stations to perform Operations 20 (turning process), station PO_20_6, and 40 (polishing), station PO_40_2. The changes introduced were aimed at increasing the efficiency of the production process by reducing the bottleneck phenomenon, which was to ensure the implementation of the assumed production program within the designated time period. The use of FlexSim software to verify process parameters in connection with the planned change in the number of production resources was aimed at verifying the use of computer simulation at the stage of planning the production process and its evaluation. (Figure 10). Figure 8: Percentage of usage of inter-operational warehouses (queue). Figure 9: Percentage of utilization of production stations. As a result of the simulation (number of replications: 20), it was found that in each case, the duration of the production process ensured the implementation of the production plan of 3500 pieces within 562.5 working hours (Figure 11). As a result of using two additional production stations, a change was recorded in the area of the level of use of the inter-operational warehouses (Figure 12). In the case of warehouse number 3 (Queue 3), preceding operation number 40 (polishing), a reduction in the level of inter-operational stocks was observed from 99.57% to 11.26%. The decrease in the percentage share of the use of the inter-operational warehouse reduces the bottleneck phenomenon in the production process. It should be noted, however, that the implemented changes caused an increase in the level of inter-operational stocks on warehouses number 1, 2, and 4 (Queue 1, Queue 2, Queue 4).