# Analysis of Production Process Parameters Using Computer Simulation at the Planning Stage
## 3 Materials and Methods
### Methodology of the Study  
The achievement of the assumed goal was possible thanks to the development of a five-stage methodology created by the authors of this study (Figure 3).  
During the first stage, an analytical method was used to define the number of production stations necessary to execute the assumed production plan \(\mathrm{P_{s}}\).  
\[\mathrm{P_{s}}=\frac{\mathrm{O_{P}}}{\mathrm{A_{wf}}}, \tag{1}\]  
where \(\mathrm{P_{s}}\)--complete occupation of the production station; \(\mathrm{A_{wf}}\)--available work time.  
\[\mathrm{O_{P}}=\left(\mathrm{n*t_{pc}+t_{u}*P_{v}}\right) \tag{2}\]  
where \(\mathrm{t_{pc}}\)--preparation and completion time; \(\mathrm{t_{u}}\)--unit time; \(\mathrm{n}\)--number of production batches; \(\mathrm{P_{v}}\)--production volume.  
The second stage consisted of selecting simulation software. For the purposes of the study, FlexSim 22.2.1 software was used, which has extensive capabilities in the area of simulation of production processes and analysis of their production parameters. The choice of FlexSim simulation software was motivated by its availability, as well as by the possibilities it offers, allowing for the achievement of the assumed goals of the study, which included the following:  
* The possibility of building the model logic in the form of programmed block diagrams;
* Analysis of the system through generated diagrams, reports, and spreadsheets;  
Figure 3: The methodology of the authors (five stages).  
* The possibilities of the software for use in the field of industrial production, i.e., analysis of the production line load, analysis of the size of inventories in the supply chain, mapping of the production flow, mapping of the process of supplying work stations with raw and other materials, and analysis of the load of production stations and inter-operational warehouses.  
In the third stage, data for the number of production resources necessary to execute the assumed production plan, which were obtained in the first stage, were implemented in the simulation software. The simulation carried out, reflecting the actual conditions of the production process, was aimed at identifying the parameters obtained by the production process in terms of its efficiency, the number of inter-operational stocks, and its production costs. As a result, it was possible to identify bottlenecks in the production process and indicate potential areas for improvement, which is emphasized in the studies [8; 9; 14; 15; 19].  
In the fourth stage, in the case of identifying areas that could be changed (e.g., bottlenecks), which would increase the efficiency of the production process, actions were taken to improve efficiency. The improvements introduced concerned changing the number of production resources and then verifying the results using computer simulation.  
In the fifth stage, a comparative analysis of the results obtained using analytical methods and those generated by the FlexSim simulation software was performed, and its evaluation was carried out in terms of the reduction of the production process duration.  
The proposed methodology (Figure 3) may constitute a basis for using the proposed strategy of actions in the analysis of data from other production processes.