ALGORITHMS FOR FORECASTING THE LIFE OF MODERN TECHNOLOGICAL MACHINES
Keywords:
Service life, technological machines, forecasting algorithms, wear dynamics, physical and mathematical modeling, artificial intelligence, digital twin, big data analysis, maintenance, production efficiency.Abstract
This scientific article is devoted to the development and implementation of algorithms for forecasting the life of modern technological machines. The study analyzed the dynamics of wear and damage that occur during the operation of machines under mechanical, thermal and vibration loads. The possibilities of accurately assessing the duration of operation by integrating real-time monitoring systems, sensor data, historical performance statistics and the results of physical and mathematical modeling are highlighted. Using algorithmic approaches developed on the basis of artificial intelligence, big data analysis and digital twin technology, mechanisms for obtaining accurate forecasts of the life of machines, optimizing maintenance processes and minimizing production stops are shown. Also, the possibilities of increasing the economic efficiency of production, optimizing spare parts management, and improving constructive solutions at the design stage are scientifically revealed.
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