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The research is related to the increasing role of prognostic models in production systems management, which is associated with an increase in the requirements for managerial efficiency, the need to consider external factors affecting the system, the determination of the features of the systems in question, the examination of the processes in progress and the relationship between the chain of managerial decisions and the values of the selected control parameters.The purpose of the article is to consider and evaluate the consequences of decisions made as a chain of interrelated events in time with regard to the dynamics of the environment in which production systems operate and the variability of control parameters. The leading approach of the research considers the production system as one that is open "in terms of environment" and "in terms of the ultimate goal".The proprietary results demonstrate that the solutions obtained are of a probabilistic nature, the solutions should be set by ranges of possible values, the decision ranges can be arranged in such a way as to introduce variability into the decisions made, the choice of which will be based on factors not taken into account in the proposed method of analyzing production systems.The practical and theoretical significance of the research is that the described methodology allows to obtain optimal values of control parameters based on the objectives of the production system under consideration on the basis of its integrated assessment, taking into account the interaction and the mutual influence of the systemâ€™s parameters, their inertness and probabilistic nature, which makes it possible to increase the validity of managerial decisions and to consider the inertness of the processes taking place in the system during planning.

Production Planning with Parameters on the Basis of Dynamic Predictive Models: Interconnection and the Inertness of their Interaction