Abstract
Manufacturing process management is a complex problem characterized by decision-making throughout the entire production process and is reduced to finding the best set of possible (alternative) in terms of some criterion or criteria for the use of available resources. The goal of the production process optimization is to analyze a set of alternative production options in complex systems and to determine the most rational possible state depending on the selected management strategies. The system contains many connections between elements and is influenced by random factors. It is not possible to create a real model for the system that is described analytically, but it can be investigated by using simulation modeling. In the mathematical modeling of the production process cluster analysis methods are used which allow to process a large amount of data from all possible states of the system and divide them into similar aggregates according to several characteristics. The analysis of the formed groups is carried out and the regularities that have the most significant impact on the occurrence of states into clusters are revealed.
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