# Reliability Analysis of Technical Means of Transport
## 5 Conclusions  
The objective of this article was to define the reliability of technical means of transport, using the example of a selected MU, and to determine the expected fitness time, using the GNU Octave and Notepad++ software. The source literature contains numerous studies on the reliability of a transport system, with much less elaboration related to the issues associated with the reliability of means of transport, which are, undoubtedly, components of the entire system. Ensuring an appropriate level of military equipment readiness and proper operating conditions for vehicles enables the execution of tasks at individual command levels. Every vehicle failure can lead to growing operating costs resulting from the need for diagnostics and repairs. It should be noted that the operating conditions of means of transport significantly influence their technical condition, durability and reliability. This can be reflected in the decreasing operating efficiency of the vehicles and can impose a higher frequency of maintenance work. This study focused on determining the reliability characteristics, both functional and numerical. One of the numerical characteristics is the expected fitness time, the value of which can be calculated using numerical integration methods. The article presents a novel solution in the form of a script, the implementation of which in GNU Octave leads to the determination of the expected fitness time for a studied group of vehicles. It also discusses the theoretical grounds for the structure of the mathematical model and explains the purposefulness of applying the numerical formulas for the integration of functions with single independent variables, so-called quadratures. Each of the applied methods was compared regarding the indicated advantages and disadvantages resulting from their application. The subject of the research included a group of medium-capacity, high-mobility military vehicles, with a permissible gross vehicle mass below 7000 kg. The main purpose of the analyzed means of transport was carrying people and equipment and, depending on the needs, the ability to adapt the chassis for the installation of special devices. Over the course of the 18-month studies, using departure orders and technical servicing sheets, the operational mileage of each vehicle and the dates of the failure were recorded on a daily basis. Based on the collected data, it was concluded that the number of roadworthy (fit) vehicles over the period in question changed on two occasions. The highest alignment factor of 93% was obtained through the approximation of the empirical reliability function using an exponential function. It should be noted that, depending on the adopted integration interval length, the expected fitness time values calculated using the compound trapezoidal rule and compound Simpson's rule were slightly different. The expected fitness time for the studied group of vehicles was approximately 15 months. The results of tests covering medium-capacity, high-mobility military vehicles have their specific characteristics and have not yet been the subject of other publications. Given the above, the authors were not able to compare them with the study results presented in other  
Figure 10: Leading empirical function waveform. publications. The determination of the expected fitness time is significantly simplified by the possibility of applying the \"quad\" feature provided in the GNU Octave software, which consequently led to obtaining a result corresponding to the assumed Simpson's quadrature. The conducted calculations showed that the GNU Octave software is an effective tool when applied for the determination of the expected fitness time, depending on the adopted reliability function. The implementation of the proposed solution reduces the calculation time and enables a user to determine the expected fitness time based on the individually specified criteria.