## 1 Introduction
### Maintenance Grouping Strategies and Literature Review  
In the maintenance planning context, the grouping strategy establishes a time span over which a joint execution of a certain number of maintenance activities is planned (See e.g., [25; 26]). Through the application of the grouping strategy, it is possible to reduce the system setup costs related to the preparation, assembly, or disassembly of components when performing maintenance tasks. In the case of multi-component series systems, the grouping strategy also allows increasing system availability and consequently improving efficiency and productivity levels, while reducing the number of interruptions and downtime service [27]. In this regard, the scientific literature shows a wide application of this type of strategy in several industries, addressing the technical features of the productive environments, as well as the complexity and interaction between its components. In this sense, [PERSON] [28] originally proposed three types of multi-component system dependencies, namely: economic, structural, and stochastic. In this way, it is possible to classify the strategies proposed in the scientific literature, depending on the interactions addressed in each particular case. The economic dependence on a production system establishes that the joint execution of maintenance activities is economically more efficient than their individual executions. In this way, the grouping strategy then implies a reduction in total maintenance costs. The vast majority of research related to the application of these strategies seeks to exploit this phenomenon in economic-dependent systems (see [PERSON] and [PERSON] [29], [PERSON] et al. [30], [PERSON] et al. [31], [PERSON] et al. [32], [PERSON] et al. [26], [PERSON] et al. [33], [PERSON] et al. [34], [PERSON] et al. [35], [PERSON] and [PERSON] [36]). Addressing economic dependency, [PERSON] et al. [34] develops a framework for planning PM activities, considering the use of time-window tolerances for the advance or delay in the execution of activities under a controlled risk zone, facilitating the creation of grouping schemes in a continuous-time planning horizon. Consideringthe close strategic relationship between operational and maintenance functions, recent research extends the grouping problem from a joint optimization approach to operational and maintenance management (See e.g., [PERSON] and [PERSON] [37], [PERSON] et al. [38], [PERSON] et al. [39], [PERSON] and [PERSON] [40], [PERSON] et al. [41]). In several production systems, scientific literature in the field have shown the presence of different types of interactions or dependencies, which cannot be omitted when developing and implementing an efficient grouping strategy. For this reason, recent research in the field addresses several dependency types in complex systems. Structural dependence, on the one hand, includes the requirements for replacement, repair, and assembly of other work units to carry out the maintenance activity on a certain component [28]. In this sense, [PERSON] and [PERSON] [42] address the existence of structural dependence for the evaluation of a selective grouping and maintenance strategy in multi-state multi-component series systems. On the other hand, stochastic dependence establishes the existence of lifetime correlation and deterioration between the different components of the production system. Recently, the research developed in [PERSON] and [PERSON] [43] simultaneously addresses the economic and stochastic dependence in multi-component systems, while research works such as [PERSON] and [PERSON] [44], and [PERSON] et al. [45] address the stochastic dependence phenomenon by modeling the deterioration of the components. In the context of sewage treatment plants, some studies have addressed the impact of maintenance and renewal policies on the performance and efficiency of the plants, revealing a strong relationship between the management and application of said policies, the proportion of O&M costs, and the productivity levels. [PERSON] et al.