The tasks of using artificial intelligence in lean manufacturing

Abstract

Modern conditions of functioning of industrial enterprises associated with a high degree of market competitiveness, market conditions, necessitate the improvement of production process management in order to optimize production, reduce production losses and increase labor productivity. The prompt and effective solution of these tasks is possible through the use of artificial intelligence, which allows not only to collect, analyze and structure production information, but also to increase the effectiveness of people’s work, improve the quality of manufactured products, and increase the efficiency of the enterprise as a whole. In turn, the implementation of the lean manufacturing concept at the enterprise can be carried out with great success with the widespread use of artificial intelligence technologies. The purpose of this article is to determine the range of tasks that can be solved using artificial intelligence in the implementation of the principles of thrift. At the same time, artificial intelligence is considered as an additional tool in the tool kit of lean manufacturing, enhancing the resulting effect. As a result of the study, the tasks to which artificial intelligence technologies are involved in the framework of the well-known lean production tools are identified. The article notes that the idea of continuous improvement occupies a central place in the philosophy of lean manufacturing. It is about focusing on constant change. Readiness for changes in the enterprise should be maintained constantly, so that when there is an opportunity for improvement, appropriate measures can be implemented. This possibility can be determined in a timely manner using AI tools. According to the results of the study, it was concluded that artificial intelligence technologies, regardless of their size and the production technologies used, incorporated into the processes of thrift, allow to obtain a synergistic effect that affects the functioning of the entire enterprise.

Keywords

• artificial intelligence
• lean manufacturing
• production management tasks
• management levels
• hierarchical structure of tasks
• machine learning