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The proposed methodology is designed to function in line with intellectual decision support system (DSS), which is used for managing of the production process. The methodology is designed to function in automatic mode, which uses highly specialized intelligent vocabulary interface. Function process of DSS includes training mode, where standard phonemes of speech characteristics are created for each feature vector. Where feature vectors are recorded into the database via corresponding components of DSS. Neural network was based on genetic algorithm, and was developed using standard established speech phonemes, Control mode was integrated, i.e. operator, who has been authorized to manage the object, displays a message as regards the state of the object and/or control command via intelligent interface. According to the proposed methodology the quantitative characteristics of feature vectors are recognized by neural networks. Using automated control mode the semantic part of the command is then recognized and transferred to the main part of DSS, which processes the information dependent on the object status. After executing the command, the feedback is provided through intelligent interface, i.e. operator receives verbal communication with regard to tasks implementation. DSS, which was developed on the basis of the proposed methodology, can be used for intelligent control units in various sectors, e.g. in coal, steel industries.