The process quality capability indicators C_p and C_pk are widely used to measure process capability. Traditional metric estimation methods require process data to be explicit and normally distributed. Often, the actual data obtained from the production process regarding the measurements of quality features are incomplete and do not have a normal distribution. This means that the use of traditional methods of estimating C_p and C_pk indicators may lead to erroneous results. Moreover, in the case of qualitative characteristics where a two-sided tolerance limit is specified, it should not be very difficult. The problem arises when the data do not meet the postulate of normality distribution and/or a one-sided tolerance limit has been defined for the process. Therefore, the purpose of this article was to present the possibility of using the Six Sigma method in relation to numerical data that do not meet the postulate of normality of distribution. The paper proposes a power transformation method using multiple-criteria decision analysis (MCDA) for the asymmetry coefficient and kurtosis coefficient. The task was to minimize the Jarque–Bera statistic, which we used to test the normality of the distribution. An appropriate methodology was developed for this purpose and presented on an empirical example. In addition, for the variable after transformation, for which the one-sided tolerance limit was determined, selected process quality evaluation indices were calculated.

Logistics processes, their effective planning as well as proper management and effective implementation are of key importance in an enterprise. This article analyzes the process of supplying raw materials necessary for the implementation of production tasks. The specificity of the examined waste processing company requires the knowledge about the size of potential deliveries because the delivered waste must be properly managed and stored due to its toxicity to the natural environment. In the article, hidden Markov models were used to assess the level of supply. They are a statistical modeling tool used to analyze and predict the phenomena of a sequence of events. It is not always possible to provide sufficiently reliable information with the existing classical methods in this regard. Therefore, the article proposes modeling techniques with the help of stochastic processes. In hidden Markov models, the system is represented as a Markov process with states that are invisible to the observer but with a visible output (observation) that is a random state function. In the article, the distribution of outputs from the hidden states is defined by a polynomial distribution.

The study analyzed the impact of the COVID-19 pandemic on the carbon dioxide emissions from electricity generation. Additionally, monthly seasonality was taken into account. It was assumed (research hypothesis) that both the COVID-19 pandemic (expressed in individual waves of infection cases) and the month have a significant impact on CO₂ emissions. Analysis of variance (ANOVA) and non-parametric Kruskal–Wallis tests were used to evaluate the significance of the influence of individual explanatory variables on the CO₂ emission. The identification of the studied series (CO₂ emission) was first made by means of a linear regression model with binary variables and then by the ARMAX model. The analysis shows that in the consecutive months and periods of the COVID-19 pandemic, CO₂ emissions differ significantly. The highest increase in emissions was recorded for the second wave of the pandemic, as well as in January and February. This is due to the overlapping of both the increase in infections (favoring stays at home) and the winter season. It can be concluded that working plants, schools and factories had the same demand for electricity, but sources of increased consumption were people staying at home and in hospitals as a result of deteriorated health, isolation or quarantine.

Unmanned aerial vehicles are used for a wide range of fire protection tasks, includ-ing search and rescue operations. Today, unmanned aerial platforms patrol coastal zones, par-ticipate in road incidents patrolling, and perform many other tasks in various areas of the infra-structure, economy, etc. The Military Fire Protection Inspectorate organizes, supervises, and conducts rescue operations in divisions supervised by Ministry of National Defense. Due to advanced technology, FlyEye unmanned aerial vehicles effectively help to eliminate fire risks in military units and other organizational units.

The growing intensity of fire hazards is increasing the need for incorporating aerial vehicles including unmanned aerial vehicles, which are now becoming a valuable tool in the hands ofvarious state bodies and institutions, including the State Fire Service (SFS) in Poland, in supportingactivities aimed at saving human life, health or property. The article presents the characteristicsand purpose of the SFS and the range of tasks performed by it, as well as key problems in thisarea. Examples of the use of unmanned aerial vehicles (UAVs) in firefighting activities werealso presented. It was pointed out that improving the ability of SFS to carry out tasks should bea priority, especially in an era of cyclical threats arising from human activity or environmentalforces, and the continued growth of technology means that unmanned aerial vehicles can provideincreasing support. The purpose of the article was to present the scale and level of a fire threat andto indicate the potential of UAVs in combating it. The research was conducted on the exampleof a selected region. The article uses the case study method: 3 examples are presented to supportrescue operations using unmanned aerial vehicles. Descriptions of cases are supplemented byoperational conclusions and recommendations. It was assumed (research hypothesis) that thelarge-scale use of unmanned systems for search and rescue operations in the SFS would not onlyaffect the speed and effectiveness of the response, but also enhance the level of safety of the officersinvolved. The authors also emphasise the need of creating a new unit in the structures of theState Fire Service, which would deal exclusively with the implementation of tasks related to theprocessing, management, analysis and placement on the map of the necessary data on the hazards.This would make preventive measures more effective.e

Cel pracy: W Polsce bardzo często dochodzi do zjawisk cyklicznych takich jak pożar czy powódź, co powoduje każdorazowo mobilizację służb i instytucji państwowych. Czynności, które należy zazwyczaj wykonać są bardzo dynamiczne ponieważ wiążą się z niesamowitą presją czasową. Bezzałogowe statki powietrzne przystosowane są zarówno do zapobiegania, monitorowania oraz zwalczania zagrożeń wynikających z infrastruktury krytycznej. Główny problem badawczy sformułowano w postaci pytania: Jakie funkcjonalności systemu BSP są przydatne do realizacji zadań realizowanych przez służby i instytucje odpowiedzialne za zwalczanie zagrożeń związanych z infrastrukturą krytyczną?Materiał i metody: Kwestionariusz wywiadu eksoerckiego, obserwacja, własne doświadczenia.Wyniki: Jak wynika z przeprowadzonych badań oraz własnych spostrzeżeń można stwierdzić, że system lotnictwa bezzałogowego pełni ważną rolę w systemie bezpieczeństwa ekologicznego. Drony poprzez wiele funkcjonalności są w stanie monitorować zagrożenia środowiskowe i skutecznie im przeciwdziałać.Wnioski: Należy w dalszym ciągu prowadzić badania na temat zastosowania BSP w ochronie środowiska. Wskazanym jest ciągłe unowocześnianie, rozwijanie oraz implementowanie BSP w strukturach służb oraz instytucji odpowiedzialnych za ochronę środowiska w Polsce. Niezwykle ważnym aspektem jest również implementacja systemów bezzałogowych przez służby typu Policja, Straż Graniczna czy Państwowa Straż Pożarna. Wspólna wymiana informacji drogą powietrzną pomiędzy poszczególnymi służbami ułatwiałaby koordynację zadań związanych z ochroną środowiska.