Subject. The problem of increasing the economic efficiency and sustainability of industrial enterprises in the context of increasing uncertainty of the external environment and increasing the cost of equipment downtime. Objectives. Increasing the sustainability of enterprises through the development and testing of a practical approach to adaptive management of cyber-physical systems based on the integration of digital twins and LSTM algorithms. Methods. Methods of systems analysis, simulation modeling and deep learning (neural networks) were used. Original indicators of adaptive flexibility and dynamic stability were developed. Results. The CPPS architecture with a closed feedback loop has been developed. The simulation results confirm a 16.1% increase in the overall equipment efficiency index and a twofold increase in the dynamic stability index when using a proactive algorithm. Conclusions. The implementation of the proposed approach generates a sustainable economic effect equivalent to an increase in the operating time of the equipment without additional capital investments.
Keywords: cyber-physical systems, adaptive production, digital twin, dynamic planning
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