Analysis of the Use of Neural Networks for the Automated Development of Technological Processes for Processing Materials by Cutting

The rapid development of artificial intelligence (AI) is affecting more and more areas of human activity, opening up new opportunities for them. Data classification, pattern recognition, data analysis, prediction based on historical data, natural language processing are only a small part of the abilities of modern artificial intelligence. The study of AI's capabilities attracts many scientists around the world, and large countries such as the United States and China have already appreciated the benefits of introducing AI into science, medicine, and manufacturing. However, the introduction of AI into production is still local in nature, since not all companies can afford investments in the development and maintenance of artificial intelligence. In addition, AI is still not perfect, sometimes making errors when processing requests, or performing only one task inherent in its logic. One of the industries in which AI can optimize technological processes is mechanical engineering. Modern machine-building enterprises have automated systems capable of performing various jobs instead of people, such as CNC machines, manipulators, robots, and others. But there is always a person behind the organization of the entire equipment. The manufacturing process of the parts takes place in accordance with the technological process that the engineer-technologist is developing. The development of technological processes is a complex of complex tasks, which include calculating allowances and processing modes, selecting materials, determining operations and transitions, and estimating production costs. The introduction of AI into industry would make it possible to optimize the fulfillment of all listed tasks, optimize technological processes, reduce the time for operations, reduce production costs and improve the quality of products.