The article concerns the condition of automation and robotization of underground mining in Poland. Attention has been focused on the specific character of the mining industry. This limits the possibility of using robotization, and sometimes even the mechanization of certain processes. In recent years, robotic and automated machines and machine system solutions have been developed and applied in Poland. They are autonomous to a various degree, depending on the branch. The type of automation and artificial intelligence depends on the specific use. Some examples presently being used include the MIKRUS automated longwall system and autonomous device(s) for breaking rocks or mining rescue work. In Poland, fully automated plow systems produced by foreign companies are also used. Companies in Poland and international research centers are also actively engaged in the development of underwater and space mining. where robotization is of key importance. Research is also being undertaken by Robotics in Mining, euRobotics and PERASPERA as well as Space Mining Conference.

Every company must ensure that the production process proceeds without interferences. Within this article, the author uses the term "interferences" in reference to unplanned stoppages caused by breakdowns. Unfortunately, usually due to machine operators' mistakes, machines break, which causes stoppages thus generating additional costs for the company. This article shows a cause and effect analysis of a breakdown in a production process. The FMEA as well as quality management tools: the Ishikawa diagram and Pareto chart were used for the analysis. Correction measures were presented which allowed for a significant reduction in the number of stoppages caused by breakdowns.

This article presents the results of noise tests, measurements and proposals of solutions that have an impact for reducing noise at one of the Jastrzębska Spółka Węglowa S.A. mines. All units and workstations at the mechanical coal processing plant were tested. Coal enrichment, aimed at adjusting its quality parameters to the requirements of various customers, is considered as a stage of mineral resources management. The adaptation of the quality of commercial coal products to the needs of specific customers consists in removing useless components from the excavated material. The processes of coal processing are carried out on various machines, the power of which reaches several dozen kilowatts. The energy of these machines, in addition to the useful power, is converted into heat, friction and noise. From the energy point of view, noise is not important, but it is very harmful to employees. The issue of noise pollution, although very dangerous to employees’ health, is often underestimated. Due to the subjective perception of noise, it is not possible to determine the risk without proper research. The aim of this study was to determine where the noise standards are exceeded. The next step was to propose specific solutions to reduce the impacts of noise on health and work comfort.

The proper selection of cutting longwall winning machines for specific mining and geological conditions requires the development of an appropriate algorithm. The appropriate selection of a machine (shearer) is closely related to acquiring a high concentration of exploitation from the given longwall. That is indispensable, especially taking into consideration the growing cost of mining, as well as the depth of coal seams. In this article, an algorithm showing the selection of longwall winning machines has been presented. The algorithm has been created based on results of research on the processed coal’s mechanical properties. Analysis of the mining process, especially in difficult conditions, shows that in order to define a drum longwall shearer’s range of usage, the coal’s properties which have a significant impact on the mining process must be determined. The above also influences the technique, technology and effectiveness of mining—they impact the effectiveness of the winning machines. In connection to this, the cutting heads should be chosen and designed based on those factors, as well as any performance forecasts. As representative values the following have been chosen: workability index (WU_B), resistance to unidirectional compression (R_c), and energy consumption of the mining process (TE).

Mechanical mining is a widely used method of separating materials from the face to obtain a useful mineral (e.g., coal, metal ores, salts, and diamonds), to make underground workings (e.g., mine galleries, tunnels, and underground garages), level roads, shape slopes, or to dig ditches. Mechanical mining is applied in the mining branch, tunnelling, road, and construction industries. Depending on the mechanical properties of the rocks, most frequently described by uniaxial compression strength, various machines and tools are used. The methods of mining high-strength abrasive rocks that have been used and developed in recent years are particularly applicable to the mining of copper, gold, tungsten, platinum ores, diamond deposits, and tunnelling. In addition to rock strength, the effectiveness of the mining process is affected by abrasiveness, which influences the rate of abrasive tool wear. Therefore, in various research and development centres, but also in production companies, tools are tested on unique stands. Tests are carried out to determine the cutting resistance and assess the wear rate. This article reviews methods and benches for testing mining tools, conical picks, and discs. Various solutions for testing single tools and cutting heads have been presented. The analysis conducted has revealed that despite the large number and great diversity of different test benches, there are no appropriate methods and stands for testing the wear rate of materials intended for mining tools.

Failure frequency in the mining process, with a focus on the mining machine, has been presented and illustrated by the example of two coal-mines. Two mining systems have been subjected to analysis: a cutter-loader and a plough system. In order to reduce costs generated by failures, maintenance teams should regularly make sure that the machines are used and operated in a rational and effective way. Such activities will allow downtimes to be reduced, and, in consequence, will increase the effectiveness of a mining plant. The evaluation of mining machines’ failure frequency contained in this study has been based on one of the traditional quality management tools - the Pareto chart.