PROSPECTS FOR THE USE OF INTELLIGENCE SYSTEMS TO ENSURE THE QUALITY OF THE SURFACE LAYER OF MACHINE PARTS

The study objective is to find the possibility of using intelligence systems together with vibration turning technology to ensure the quality of the surface layer and improve the performance properties of products in industries such as automotive, aircraft, space technology, mining and metallurgical engineering, etc. The task to which the paper is devoted is to ensure the operational properties of machine parts by vibration turning. To a greater extent, the operational properties depend on the quality parameters of the surface layer, which determine the wear resistance, fatigue strength and other operational properties of machine parts. Research methods. Theoretical analysis of literature references on the formation of regular microrelief on the contacting surfaces of machine parts, which makes it possible to improve the operational properties of machine parts and equipment. The novelty of the work is in the fact that neural network models will be obtained that allow determining surface treatment modes based on a given shape of a regular microrelief, degree, and depth of the surface layer. The practical significance is in the development of a technology that will allow obtaining the required regular microrelief, degree, and depth on the surface of the parts, providing them with the necessary operational characteristics. Study results. As a result of the theoretical analysis, the prospects of using vibration turning together with intelligence systems to ensure the quality of the surface layer of machine parts during the formation of a regular microrelief are presented. Conclusions: one of the main directions of developing modern mechanical engineering is creating automated product lifecycle management systems based on artificial intelligence. Special attention is paid to the prospects of using vibration cutting to form a regular microrelief. The assumption is substantiated about the expediency of creating an intelligence quality assurance system for the surface layer of machine parts based on artificial neural networks, which makes it possible to provide a regular microrelief of a given shape on the surface of the part at the required degree and depth.