In this article, the conditions and determinants of the introduction and development of the circular economy (CE) in Poland were presented against the background of the widely discussed essence of circular economy, with particular emphasis on the Polish mining sector. In addition, the European Green Deal—an action plan for a sustainable economy for the entire European Union, was discussed. Particular attention was paid to the role of human resources in the area of supporting research and stimulating innovation, and in the area of activating education and training. These issues are further discussed in the next chapter by presenting the forms, ways and scope of education for sustainable development in the international context. Another chapter describes the EIT Raw Materials KAVA 5 RIS competition in Poland (in Kraków) at AGH-UST from 2019 to 2022, an international project in a consortium of four universities whose main objective is to strengthen entrepreneurship in the V4 countries in line with the recommendations of the “Green action plan for SMEs” in a way to meet the requirements of circular economy. The initiatives and trainings carried out within the framework of this project were discussed, and the results of the student survey on the level of knowledge achieved regarding entrepreneurship in the area of the raw materials industry were analysed. The validity and necessity of continuous education in eco-responsible citizenship has thus been confirmed.

Fast-growing methods of automatic data acquisition allow for collecting various types of data from the production process. This entails developing methods that are able to process vast amounts of data, providing generalised knowledge about the analysed process. Appropriate use of this knowledge can be the basis for decision-making, leading to more effective use of the company’s resources. This article presents the approach for data analysis aimed at determining the operating states of a wheel loader and the place where it operates based on the recorded data. For this purpose, we have used several methods, e.g., for clustering and classification, namely: DBSCAN, CART, C5.0. Our approach has allowed for the creation of decision rules that recognise the operating states of the machine. In this study, we have taken into account the GPS signal readings, and thanks to this, we have indicated the differences in machine operation within the designated states in the open pit and at the mine base area. In this paper, we present the characteristics of the selected clusters corresponding to the machine operation states and emphasise the differences in the context of the operation area. The knowledge obtained in this study allows for determining the states based on only a few selected most essential parameters, even without consideration of the coordinates of the machine’s workplace. Our approach enables a significant acceleration of subsequent analyses, e.g., analysis of the machine states structure, which may be helpful in the optimisation of its use.

The article presents research on the possibilities of utilising the Lean Management method to increase the profitability of coal mining operations through cost rationalisation and production optimisation. The Lean Management method has its roots in the automotive industry, but its significant benefits can allow it to be transferred to other industries. Based on the analysis of global literature describing examples of its application in general mining, as well as the authors’ own observations related to Polish hard coal mining, it was determined that the Lean Management method is not being utilised in this field. This article outlines the course and results of an original expert-mathematical study to assess the usefulness of specific Lean Management tools and techniques in hard coal mining. The study drew on knowledge obtained from selected, competent experts who demonstrated high levels of agreement in their assessments. Five core production areas were identified, and twelve widely used Lean Management tools and techniques were selected. The obtained assessments of the usefulness of Lean tools could serve as valuable guidance for mining management in the selection of methods for improving mining production in coal mines.

This article describes the benefits offered by the analysis of data from production processes. With the correct processing, such data allows issues to be identified both within the analysed process and in the ways machines are used. The paper presents an initial analysis of data from the fragmentation process in a hard coal mine using longwall shearers. The analysis is described using R programming language functions.

W artykule przybliżono możliwości wykorzystania języka Visual Basic do analizy danych pochodzących z procesu produkcyjnego. Przedstawiono przykładowy program napisany w tym języku oraz omówiono jego funkcjonalność. W programie zawarto rozwiązania, które pozwalają monitorować i analizować część procesu produkcyjnego związaną z urabianiem węgla kamiennego. Artykuł prezentuje szereg koncepcji wykorzystania surowych danych pochodzących z czujników maszyny do uzyskiwania informacji, które mogą być przydatne w analizie jej pracy.