ORGANIZATION AND MANAGEMENT OF BUSINESS PROCESSES OF INDUSTRIAL ENTERPRISES ON THE BASE OF ARTIFICIAL INTELLIGENCE
Authors:   Engineering Educational and Scientific Institute named by Yuriy Potebni Zaporizhzhia National University, Shapurov Olexandr , Stoiev Volodymyr ,   Engineering Educational and Scientific Institute named by Yuriy Potebni Zaporizhzhia National University, Muratov Yurii ,   Engineering Educational and Scientific Institute named by Yuriy Potebni Zaporizhzhia National University
Published: January 2025

The growing use of artificial intelligence (AI) and machine learning (ML) in the metallurgical industry opens up new opportunities for increasing production efficiency, optimizing processes and improving resource management. On the basis of modern research and practical examples, the role of AI and ML in achieving sustainable development of the metallurgical sector is considered, in particular through the improvement of monitoring of the quality and shape of products, support of technical maintenance of equipment and optimization of material properties. The integration of smart service and Industry 4.0 concepts contributes to increased energy efficiency, efficient use of resources and reduced environmental impact, which is in line with the UN Sustainable Development Goals until 2030 and the European Green Deal launched in 2020. At the same time, there are both technological and non-technological barriers to the full implementation of AI in the metallurgical industry, including infrastructure limitations, the need for advanced computing resources, as well as issues of cyber security and trust in AI solutions. An important aspect remains the investment in "human capital" through improving the qualifications of employees, introducing training programs and attracting young specialists, since the effective use of AI requires new competencies and interdisciplinary knowledge. The analysis also notes that innovative solutions, such as the development of soft sensors, modeling of material behavior and prediction of mechanical properties using ML algorithms, can fill gaps in existing knowledge and improve resource management at all stages of the production cycle. The implementation of AI in metallurgy has the potential to promote a circular economy and industrial symbiosis, which increases the sustainability of the industry, providing not only economic, but also environmental and social benefits for the whole society. Research and practical examples show that AI and ML play an important role in improving product quality and product monitoring accuracy, which can reduce waste and increase overall production efficiency. The implementation of smart service technologies and Industry 4.0 approaches, such as digital twins and predictive analytics, helps reduce energy consumption and optimize resources. At the same time, there is a growing need to train qualified personnel capable of adapting to technological changes and working with interdisciplinary tools, which provides a more sustainable and innovative environment for the development of the industry. This approach not only strengthens the competitiveness of metallurgical enterprises, but also contributes to the achievement of environmental goals established by the UN Sustainable Development Goals and the European Green Deal.