This study aims to highlight the importance of a systematic approach to process capability assessment and the importance of following a sequence of steps. Statistical process control provides several different ways of assessing process capability. This study evaluates the process capability of crown cap manufacturing through capability indices. In addition to calculating the indices, the evaluation involves extensive data analysis. Before calculating the capability indices, the assumptions for their correct selection and use were also verified. Several statistical tests were used to verify each assumption. The research value of the study lies in pointing out that not all tests led to the same conclusions. It highlights the importance of selecting the appropriate test type for the evaluated process quality characteristics.

Underground coal gasification (UCG) is an industrial process that converts coal into product gas (syngas). This technology makes it possible to obtain energy without mining coal and post-processing. The UCG process is considered a safe technology with various advantages over conventional mining techniques. However, a small amount of potentially dangerous syngas may escape from the UCG cavity, and it is necessary to pay attention to the safety of the process in this respect. This article analyses the impact of a syngas leak from UCG on a possible CO poisoning and explosion hazard in the vulnerable zones. Measured data from experiments and proposed mathematical models were used for the analysis of the UCG process and simulation studies. It is mainly a mathematical model mixing of gases, which evaluated the danger of explosion and CO poisoning in sensitive zones. This model predicts the composition of the syngas mixture with air because this mixture can be dangerous at a certain concentration. Simulation studies focused mainly on CO poisoning in vulnerable areas based on the measured data from laboratory experiments. Simulation studies have shown that the critical value of CO poisoning can achieve with a certain composition of syngas and its escape into vulnerable areas. The results of the studies here indicate a possible hazard. However, by monitoring and control of UCG process, this risk can be minimized. Based on the obtained results, the control of the supply of fresh air to the endangered area during the monitoring of the syngas composition was proposed to prevent the occurrence of possible poisoning.

In general, college students have concerns about mastering the Statistics course. Several scientific articles suggest that methodologies in which the student is an active part of the educational process lead to their greater involvement in teaching activities and better results in their overall assessment. A modified form of the Mathematics course inspires this study. The Mathematics course precedes the Statistics course. This study presents students’ results from both affected courses for the last 12 years. The authors obtained the data from the Modular Academic Information System (MAIS). The study describes the Statistics course, which is a combination of the traditional form of teaching and learning with elements of active learning. The product is a redesign of this course. The proposed changes are based on the requirements of some stakeholders. The results are from a survey of course graduates, from the experience of online teaching during the COVID-19 pandemic, and the introduction of active-learning elements. The authors of the article point out the risks and opportunities they found in teaching the Statistics course.

Technical and technological developments in recent decades have stimulated the rapid development of methods and tools in the field of statistical process quality control, which also includes control charts. The principle of control charts defined by Dr. W. Shewhart has been known for more than 100 years. Since then, they have been used in many industries to monitor and control processes. This paper aims to assess the possibilities of use and the selection of the most suitable type of control chart for monitoring the quality of a process depending on its nature. This tool should help operators in monitoring coking time, which is one of the important control variables affecting the quality of coke production. The autoregressive nature of the variable being monitored was considered when selecting a suitable control chart from the group of options considered. In addition to the three traditional types of control charts (Shewhart’s, CUSUM, and EWMA), which were applied to the residuals of individual values of different types of ARIMA models, various statistical tests, and plots, a dynamic EWMA control chart was also used. Its advantage over traditional control charts applied to residuals is that it works with directly measured coking time data. This chart is intended to serve as a method to monitor the process. Its role is only to alert the process operator to the occurrence of problems with the length of the coking time.

The underground coal gasification represents a technology capable of obtaining synthetic coal gas from hard-reached coal deposits and coal beds with tectonic faults. This technology is also less expensive than conventional coal mining. The cavity is formed in the coal seam by converting coal to synthetic gas during the underground coal gasification process. The cavity growth rate and the gasification queue’s moving velocity are affected by controllable variables, i.e., the operation pressure, the gasification agent, and the laboratory coal seam geometry. These variables can be continuously measured by standard measuring devices and techniques as opposed to the underground temperature. This paper researches the possibility of the regression models utilization for temperature data prediction for this reason. Several regression models were proposed that were differed in their structures, i.e., the number and type of selected controllable variables as independent variables. The goal was to find such a regression model structure, where the underground temperature is predicted with the greatest possible accuracy. The regression model structures’ proposal was realized on data obtained from two laboratory measurements realized in the ex situ reactor. The obtained temperature data can be used for visualization of the cavity growth in the gasified coal seam.

Mining and mineral processing are essential for the functioning of many economic sectors and for meeting human needs. Diagnostics and evaluations of faults are necessary to ensure the successful and responsible management of mining and processing processes for mineral raw materials. Fault-free operation contributes to increased efficiency, productivity, safety, and reliability, reduces the cost of the process under consideration, and reduces environmental impacts. This study aims to identify and analyze possible component failures associated with the jaw crusher used in the process of andesite crushing in an open-pit quarry and compare different approaches to their assessment. The benefit of this is using three different failure analysis methods to assess the criticality of individual jaw crusher components. This approach’s novelty lies in the synergy that occurs when assessing the failures’ impacts on safety, quality, and the environment.