# Analysis of Production Process Parameters Using Computer Simulation at the Planning Stage
## 1 Introduction  
Modern enterprises are increasingly looking for methods aimed at improving productivity [1]. In industrial practice, the possibility of applying simulation tools is being considered, allowing for the optimization of processes and the identification and reduction of identified losses, as well as for the shortening of the working time and the achievement of the desired economic efficiency without the need to introduce costly changes [2]. In the literature on simulation issues, the analysis covers methods based on discrete event simulation (DES) [1; 3; 4], which are widely used in modeling health care systems [5], production processes [6], supply chain management, and logistics [7; 8], among others applications. Discrete event simulation models present the system in such a way that the decision maker can observe the way the process works, as well as propose improvements that have a significant impact on the process efficiency [1; 2].  
The methods of computer modeling and simulation are widely used in business practice due to the fact that analytical solutions are complicated, and direct experimentation on a real system is time-consuming, expensive, or sometimes impossible to carry out. The solutions used allow the decision maker to learn about different variants of the solutions and thus choose the variant that meets the decision maker's expectations. The software used allows for the creation of models for simulating production processes, transport, distribution, storage, or the individual needs of the decision maker, which indicates the wide application possibilities of modeling and simulation in solving complex problems in various branches of the economy.  
In connection with the above, the aim of the article was to verify the possibility of using computer simulation (FlexSim software) as a tool supporting analytical methods at the stage of planning the production process. For the purposes of the study, the actual parameters of the production process were analyzed in terms of selecting the appropriatenumber of production resources ensuring the shortening of the duration of the production process and the reduction of costs, among other benefits. The use of computer simulation within the existing production process can supplement the research conducted in the field possible simulation application at the stage of planning the production process, along with its evaluation. In industrial practice, analytical methods were used; therefore, the possibility of using computer simulation was proposed, using FlexSim software in the scope of the analyses in question, based on real data. The implementation of the assumed goal of the work will allow for filling the research gap in the scope of the possibilities of using computer simulation (FlexSim simulation software) to determine the number of production resources necessary to implement the assumed production plan.  
The production process subjected to analysis included the production of rotating parts for use in the machine industry. The process consisted of six production operations carried out on individual, non-automated production stations. Thanks to the data on the duration of individual production operations, which were provided by the company, as well as those related to the form of production organization and the layout of the production stations, the discussed production process was an appropriate model for conducting an analysis in the scope of the defined work goal.  
The article includes a literature section (Section 2), in which selected simulation software and areas of their application in the field of analysis of production process parameters were characterized. Section 3, presents a case study, which is the subject of the conducted analysis (a detailed description of the production process) and defines a five-stage methodology. In Section 4, simulations of the production process were carried out, and then discussions of the obtained results were conducted in Section 5.