This paper critically assesses Business Process Management (BPM) education in Poland and provides evidence-based recommendations for improvement. Through a survey of 44 BPM educators, the study evaluates BPM lifecycle coverage, IT tool utilization, and incorporation of the Six Core Elements of BPM. The findings reveal a focus on process modeling and analysis, identifying gaps in the way the entire BPM lifecycle is addressed. Despite the utilization of various IT tools, there is a notable absence of coverage for emerging topics such as process mining, AI, and Robotic Process Automation. Only 12% of courses cover all Six Core Elements of BPM, and there is a critical gap in student education, which is the underrepresentation of the People and Culture elements. The paper concludes with a manifesto for greater alignment between academic education and industry needs through comprehensive BPM curricula, dedicated software tools, and more robust coverage of the strategic and governance aspects of BPM. This will bridge the gap between academic education and real-world BPM applications, so that graduates can be better prepared for the challenges of the modern business landscape, which can enhance the quality and effectiveness of BPM education, thereby aligning it with the evolving demands of the business environment and contributing to the growth and competitiveness of organizations in Poland.

Conformance checking is a process mining technique that compares a process model with an event log of the same process to check whether the current execution stored in the log conforms to the model and vice versa. This paper deals with the conformance checking of a longwall shearer process. The approach uses place-transition Petri nets with inhibitor arcs for modeling purposes. We use event log files collected from a few coal mines located in Poland by Famur S.A., one of the global suppliers of coal mining machines. One of the main advantages of the approach is the possibility for both offline and online analysis of the log data. The paper presents a detailed description of the longwall process, an original formal model we developed, selected elements of the approach’s implementation and the results of experiments.

Method of probabilistic modeling of the production cycle duration time within hard coal longwall faces has been described in the present study. Duration of these activities for various technologies, including probabilistic schemes modeling have been described in the introduction. In order to illustrate the described method, an example of probabilistic modeling for data obtained from specific longwall face has been presented. The final chapters entitled “The possibility of Using the method” and “Results” contain information on the perspective of the method application in mining industry.

Method of the influence of assessment of longwall effective working time onto obtained mining output, has been discussed in the present study. Mean flow rate of the winning stream being also considered as directional factor of linear function describing relation between daily output and effective mining in the longwall face, has been determined. Such relation – presented also graphically in form of the diagram – determines significance and influence of the effective working time onto obtained mining output. This relation should be considered as motivation in particular for supervisory personnel, as it shows advantages resulting from elongation of this time, as well as it shows possible loses of the daily output in a case, when the effective working time in given longwall face was shortened.