## 3 Research Results and Discussion
### Exemplary Calculation Results
Figure 4: Graphs of the function g(x)—profit per time unit as a function of time to preventive replacement x [h], determined when the number of preventive replacements is as in the Example 1 (curve a) and when the number of preventive replacements is increased by 15%, 30% and 45%, respectively (curves b, c and d). Figure 5: Graphs of the function g(x)—availability to carry out transport tasks in function of time to preventive replacement x [h], determined when the number of preventive replacements is as in the Example 1 (curve a) and when the number of preventive replacements is increased by 15%, 30% and 45%, respectively (curves b, c and d). In the publication [21], the simplest semi-Markov model was developed for the stationary mode of system operation. A systematic probabilistic-statistical approach and a graph-analytical apparatus were used. The obtained semi-Markov model of operation was tested on a potato harvest. The obtained results indicate that the developed semi-Markov model can be used to find probability-time indicators of crop harvesting processes in agriculture. However, the article does not develop a model that has similar functions to ours. This article uses a different state graph. PM and MR were not addressed. The article [22] presents a modeling of the process of exploitation of the means of transport in the army. There, it is necessary to maintain transport units at a high level of availability. As quantitative characteristics for assessing and optimizing the availability of military vehicles, three indicators were proposed: functional availability, technical efficiency and airworthiness. In order to determine their value, a stochastic exploitation model was developed, based on the application of the theory of Markov processes. Based on the collected empirical data, nine states of the system have been identified. Operational states related to the implementation of the transport task, refueling, parking in the garage and maintenance and repairs were distinguished. As part of the consideration on continuous time, the verification of the distribution of time characteristics led to the development of the semi-Markov model. The indicators of functional accessibility, efficiency and technical suitability were determined. This article uses a different state graph. PM and MR were not addressed. The article [23] presents an analysis of the real system of operation of means of transport together with a mathematical model that allows for examining the degree of their readiness to perform transport tasks using the semi-Markov model. The calculated characteristics made it possible to diagnose the analyzed system and assess the level of technical readiness. As a result of the analysis of the transport system using the semi-Markov model, the values of the selected indicators were obtained, which were then used to determine the probability of the vehicles staying in the distinguished operating states. Such a model allows for a qualitative and quantitative assessment of credibility and the identification of weak links and areas requiring detailed control, which may result in an increase in the organization's potential.