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The article discusses the use of artificial intelligence (AI) technologies to optimize technological processes in the manufacturing sector. The main purpose of the study is to analyze the potential of using AI to increase efficiency and automate production operations. The work uses methods of system analysis, mathematical modeling and computer simulation to assess the possibilities of implementing AI solutions in various industries. The research materials include data on existing AI systems used in production, as well as the results of experiments and testing of new algorithms and approaches. In particular, such technologies as machine learning, computer vision, natural language processing and expert systems are considered. The results of the study show that the use of AI can significantly increase labor productivity, reduce costs and minimize the risks of emergency situations. Thus, the use of AI algorithms to predict equipment failures based on real-time analysis of sensor data makes it possible to reduce downtime by 20-30%. The introduction of robotic complexes with computer vision elements into assembly lines allows to increase the speed of operations by 25% and reduce the number of defects by 15%. The use of chatbots and virtual assistants to automate interaction with customers and suppliers ensures a 40% increase in communication efficiency. The article also highlights the potential limitations and risks associated with the use of AI in production, such as the high cost of development and implementation, the need to retrain personnel, and issues of data security and confidentiality. In conclusion, it is emphasized that, despite the existing challenges, AI technologies have significant potential for transforming production processes and increasing the competitiveness of enterprises in the context of Industry 4.0.
Keywords:artificial intelligence, production optimization, automation, machine learning, computer vision, natural language processing, expert systems, Industry 4.0.
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