At present, a new generation of students is studying at universities with their specific abilities and skills. In addition to hard skills, potential employers also require significantly developed soft skills from their employees. The school, and not just the university, is entering this process in a different position than in the past due to the changing requirements placed on it. Activities in the school environment must adapt to emerging trends. This article explains how present-day requirements on graduates and specifics of the new generation of students challenge the approach to education. In order to increase the efficiency and attractiveness of the educational process, the SCRUM framework has been implemented into course Mathematics 1. The re-designed course was implemented and validated by an experimental group of students in the academic year 2019/2020. Two questionnaire analyses and a comparison of learning outcomes were conducted to find out the answers to research questions. The results of students indicate that agile methodologies are useful for increasing the efficiency of the educational process. The paper offers our proposal for the introduction of agile methodology into the educational process and our first-hand experience with this way of teaching and its impact on the studying results of the experimental group and, last but not least, suggestions for possible improvements.

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.

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.

The present paper deals with using different mathematical tools and approaches for the data fitting. A comparison of two types of mathematical models, which solutions are used to fit experimental data is done, where the error-of-fit and the computation time are taken as the fitting benchmarks. Both types of the defined models consist of differential equations, one uses fractional, the other integer orders of differentiation. The first advantage of the fractional-order models is the fact that fractional-order differential equation (FDE) has one degree of freedom more (the order of differentiation lies in the interval (0,1)), whereas the integer-order differential equation has the order of differentiation constant, equal to 1. The other advantage besides the “freedom in order” is that FDEs provide a powerful instrument for description of memory and hereditary properties of systems in comparison to the integer-order models, where such effects are neglected or difficult to incorporate. The first aspect of this work consist in choosing a suitable optimization method for finding the parameters of the defined models based on minimizing chosen fitting criterion. The Medium-scale optimization, using the tools of sequential quadratic programming, Quasi-Newton and line-search algorithms (performed by the MATLAB function fmincon) is compared with the evolutionary - genetic algorithm (performed by the MATLAB function ga). The second aspect lies in using two different approaches in the formulation of the optimization criterion. For the time domain identification the classical least squares method (LSM) and so the sum of vertical offsets will be used. The state-space identification will use the total least squares method (TLSM or the so-called orthogonal distance fitting criterion - ODF), which uses the sum of orthogonal (perpendicular) distances between the experimental points and the fitting curve. Several examples are presented in the form of figures. The efficiency of computation and the values of the error-of-fit using different approaches are compared in the form of tables.

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.

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.