## 5 Conclusions  
As a result of this study, the impact of increasing corrective and preventative maintenance to improve the reliability of underground mine communication systems is made evident. In the case of the communication system without standby in the one-shaft underground mine studied, the current availability rate was 73.95%, and after increasing preventative maintenance by 50%, the availability rate was 81.26% and 9.8% compared to the status. After doubling corrective maintenance, it was 85.27% and 15.6%, compared to the status and after combined corrective and preventative maintenance, it was 89.75% and 21.3% compared to the status. The most significant result was a model of the interdependence of devices included in the communication system without standby in the one-shaft underground mine, built based on their conditional probabilities (Figure 11). The model makes it possible to simulate the availability rate of each device and the availability of the communication system without standby in the one-shaft underground mine using failure and maintenance functions. The new model is also suggested for developing the rate probability of the availability of underground mine communication system with one, two, and three shafts. According to the original objectives of our study, a methodology was developed that allows for simulation development of the communication system without standby in the one-shaft underground mine, which shows the impact of doubling the current and corrective maintenance without standby after increasing preventative maintenance by 50% and increasing corrective and preventative maintenance simultaneously. The results of our study show that using system dynamics modeling instead of traditional methods provides a simple simulation model that can be used to study the reliability and availability of any communication system. In this paper, real-time failure data of a system was used for simulation development. System failure data was not used to develop a model for single and dual standby systems. By being based on a real operating system, the models that were developed are suitable for practical use.  
The artificial intelligence-based neural system dynamic research methodology can be further developed based on our model. Moreover, based on the source in [17] it seems that it is possible to develop a diagnostic model based on Vensim software, not only on MATLAB (LabVIEW). Regarding future work on communication systems with single- and dual standby system:  
* Conduct experiment by replacing variable values (\(\mu,\lambda\)) instead of real system values (system failure values);
* In the dual standby communication system, it is expected that no two devices will be in failure state at the same time, and if one is in failure, then the second will be in failure state, and then all three will be in failure state. Moreover, the maintenance parameters are considered to be exactly the same as the failure parameters.
* Conducting an experiment in the case of if two devices fail simultaneously, the third device does not fail, and vice versa; when the third device fails, the first and second devices do not fail.
* The reason why these conditions were not considered in this paper is because the system of differential equations was very large and complicated to calculate.