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The article deals with the issues of modern technical service and its organizational system in the system of engineering and technical support of the agro-industrial complex. The efficiency of agricultural production is mainly influenced by the level of organization in the technical service industry.

The paper provides information on the causes of failures in automotive equipment and shows the ways to determine failures using digital technologies introduced into the diagnostic process. The implementation of forecasting as a separate stage in the process of diagnosing automotive equipment using machine learning technologies in the form of neural networks is analyzed. The results of the study reflect that the neural network while analyzing a huge amount of data received during remote diagnostics is able to more reliably predict failures of automotive equipment.

The technique and features of micrometering of cylinder liners are presented. The main factors influencing the wear of the cylinder liner and the rules for assigning planes and sections when conducting a micrometer of its inner surface are theoretically substantiated. On the example of a study of used cylinder liners of engines of the Yaroslavl Motor Plant, it was revealed that the greatest wear is manifested in the place where the upper piston ring stops in the upper part of the liner, and the amount of wear will be greater in the swinging plane of the connecting rod due to the action of normal force during pressure distribution at the beginning of the expansion stroke. High wear at the top is also due to high temperatures and lack of lubrication. It was found that the diameter of the upper non-wearing band can be used to judge the initial size of the sleeve hole. The underside of the cylinder liner is subject to wear due to the friction of the piston skirt against its surface.