## 1 Introduction and Literature Review  
Since an underground mine is a very dangerous work environment, the safety of workers can only be ensured with the help of reliable radio communication and information technology systems. It is important to develop and calculate the reliable operation of these systems on a scientific basis [1]. This study is an important part of a doctoral dissertation on the reliability of underground communication systems, which analyzes the exponential distribution of seismic data using statistics on the reliability of underground communication systems to determine the probability of an earthquake in an underground mine. An earthquake is one of the largest natural risk factors for a mine. The probability of an earthquake was determined using seismic data from 1957 to 2017 in Khanbogd soum, Umnugovi aimag, kept by the Institute of Astronomy and Geophysics of the Mongolian Academy of Sciences [2]. Another important part of our doctoral study is improving the reliability of communication systems and the modeling of standby communication systems [1]. We studied the complex structure of underground mines and tunnel distribution [3]. The results show that the isolation of RF repeaters and the distribution of radiation cables within the tunnel have been studied in accordance with the complex structure of an underground mine. In addition, in the event of an accident at an underground mine, radio communication services were relocated from the area where radio communication services were disrupted to a place where radio communication services were normal, and miners were quickly evacuated. We developed an emergency analysis using graph theory and [PERSON]'s algorithm developed in the MATLAB program and developed an algorithm [4]. The communication system for underground mining is one of the most important parts of a mine. The main objective of this study is to evaluate the possibility of improving the reliability of underground communication systems. Relationship between key elements was established using reliability causality diagram based on maintenance by system dynamics method and even there are advantages as we have recommended preventive and corrective maintenance to improve system reliability in the study, but the study was not addressed to standby systems [5]. In addition, the aging and maintenance times of single-source and dual parallel systems are considered in the Weibull distribution law. The system's mathematical model was modeled using the Markov model, but the model was not studied for dual parallel and triple parallel systems, only for Weibull distribution [6]. A current and future reliability analysis of a smart grid consisting of an electric power distribution system and an integrated communications network based on Monte Carlo simulation was developed and tested in this study [7], whereas in another study [8], a reliability model and analysis were carried out using Poisson distribution to improve the reliability of the distributed network by reducing the energy consumption of the data center. However, in studies [9; 10], the researchers reviewed these studies about the reliability of systems due to the challenges of the 4 th industrial revolution and the requirements set. In other words, it is concluded that new solutions using artificial intelligence, machine learning and big data mean the goal of sustainable production to achieve a balance between environmental, social, and economic dimensions. In addition, it is emphasized that machine learning is the most important tool for assessing the reliability of a system, and in doing so, it is emphasized that using a combination of different methods will help to better analyze the reliability. To increase the reliability of underground communication systems, this study identified new models for increasing and testing corrective and preventative maintenance, as well as developing an availability rating for single and dual standby systems.