Lately, artificial intelligence has become a tool that is not only suitable for personal and manufacturing needs, but also for optimization of business processes. Using purchasing of high-tech metallurgic goods as an example, this article demonstrates areas of application for artificial intelligence in a multi-stage international project. The analysis of the given purchase as an experiment is combined with inductive generalization of practical concerns and a systematization of experts’ views on the role and legal status of artificial intelligence. Rational use of IT does not exclude human decision-making from the process, but allows to focus the attention of the specialists on expert questions. Processing of large amounts of data and risk forecasting - these are the areas in which artificial intelligence is capable of decreasing costs and yielding better results. Modern metallurgy is one of the most promising industries for this approach.
Improving products while addressing the challenges posed by climate change can be a daunting task, particularly when considering the need to satisfy customer expectations while also protecting the environment. The objective of this research is to develop a method that supports the sustainable development of products within a circular economy (CE) framework. The method involves several steps, beginning with defining the aim of the analysis according to the SMARTER method and selecting a team of experts. The quality of the product is then assessed in light of any identified incompatibilities or defects, with each incompatibility analyzed in turn to determine possible causes using methods such as brainstorming, the Ishikawa diagram with the 5M rule, and multiple voting. Indirect causes that significantly impact the occurrence of incompatibility are then analyzed in the context of sustainability and circular economy criteria, using a correlation matrix to identify the main causes that have the most significant negative impact on the environment. Based on this analysis, the direction of product improvement can be determined within the context of sustainable development. The proposed method offers a novel approach to improving product quality and customer satisfaction while also promoting sustainable development practices.
The metallurgical sector is one of the main pillars of European industry. Steel is important not only for modern economies of developed countries but is an essential part of building infrastructure in developing countries, and thus in the coming decades, global demand for steel is expected to increase to meet growing social and economic needs. Currently, however, the steel industry is among the top three producers of CO2 emissions. Steel producers have a great opportunity to achieve greenhouse gas emission reductions and improve energy consumption efficiency, thereby increasing their competitiveness, mainly through optimizing, digitalization and innovating the production process by introducing low-carbon technologies and increasing the efficiency of raw material and energy resources. This scientific article is focused on developing advanced mathematical prediction models and analysis of steel production processes. By utilizing modern BAT and ITs technologies, this research aims to improve the competitiveness of the steel industry by optimizing production processes and through the integration of datasets and analysis techniques contribute to reducing the carbon emissions in steel production through energy consumption optimization and the implementation of sustainable practices. Through the utilization of mathematical prediction models and advanced analysis techniques, the article aims to optimize steel production processes and enhance the competitiveness of the metallurgical sector.
In 2016, China fully launched the supply-side reform of steel production capacity and carried out the work of reducing iron and steel production capacity. However, the China-United States trade war that began in 2018 and the global COVID-19 pandemic that began in 2020 have had a massive impact and uncertainty on the development of China and even the global economy, and the external business risks of enterprises have increased significantly. At the same time, this has caused the uncertainty of China's economic policy to rise rapidly. Based on the above background, this paper takes China's listed iron and steel enterprises as the research object, selects the period from 2018 to 2022, and explores the impact of China's economic policy uncertainty on the benefits of iron and steel enterprises.