## 1 Introduction  
In the ongoing transformation of the energy and communication infrastructure, a marked transition from centralized to decentralized systems can be observed. Concurrently, there is a substantial deployment of smart devices designed for network management, control, and monitoring, further enhancing the interconnection between the energy and communication networks. This enhanced integration is crucial, especially in the context of distribution networks. These networks are essential in ensuring a steady supply of electricity to households, businesses, and industries. It is essential to mention that any disruption in this supply can result in significant financial implications. Not only do Distribution System Operators (DSO) lose profits from such interruptions, but they also face potential penalties imposed by regulators. The efficiency and reliability of distribution networks is therefore of great importance to both consumers and DSOs. The reliability and consistency of electricity distribution are key characteristics, and their effectiveness is measured using specific metrics, namely the System Average Interruption Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI). These indices provide a quantifiable measure of the electricity's delivery quality to the end users. As the energy sector transitions to decentralized systems and incorporates intelligent network management devices, it is evident that communication devices play a substantial role in influencing these metrics. Specifically, devices such as Remote Terminal Unit (RTU) and Advanced Metering Monitor (AMM) are introduced. These components not only serve as essential interfaces between the distribution network and the control center, but also ensure real-time monitoring and control over the entire grid, encompassing power elements like transformers, lines, and circuit breakers. To enhance the reliability of the distribution system, one effective strategy is optimizing its maintenance with regard to repair costs, revisions, and the frequency of these tasks. This optimization task, however, becomes considerably more intricate when two interconnected infrastructures, namely the power and communication networks, are taken into account. This paper introduces a novel methodology to calculate the unavailability of the entire system which is crucial for computing SAIFI and SAIDI parameters. Furthermore, we delve into the possibilities of optimizing maintenance on a test network of these interconnected infrastructures, laying emphasis on potential dependencies and interactions during their operation. On the basis of prior research, a mathematical model employing the Weibull distribution is adopted to evaluate system contingencies within this combined infrastructure. In this research, a key objective is to standardize the terminology associated with reliability parameters relevant to both power grid and communication network systems. It has been observed in various publications that these terms are often misunderstood or inaccurately labeled. When multiple interconnected systems are taken into account instead of a singular system, understanding their interrelationships and dependencies becomes essential. To address this, the paper aims to clarify these relationships using Acyclic Graph (AG), a graphical representation method that has been successfully utilized by the authors in past research, as evidenced by [1]. The rest of the paper is organized as follows. It begins with a discussion of the state of the art in Section 2, where an overview of relevant literature and the results in the field are presented. In Section 3.1, the intricacies of the interconnected infrastructures' test network are explained. This section provides a detailed description of the devices in these infrastructures and painstakingly delineates their mutual dependencies. As it progresses to Section 3.2, the article is focused on the definition of the system's optimal function.