## 1 Introduction
This methodology was subsequently applied in practice by the authors of [24] to assess the condition of substation equipment. Furthermore, the authors of [6; 9; 12; 14] proposed methodologies for determining the health index (HI) of CBs. These studies suggested that a device's technical condition can be treated as an equivalent indicator of its HI. In particular, the HI assessment approach described in [9] aligns closely with the methodology outlined in [23]. Finally, condition-based maintenance strategies have also been extended to other components, such as power transformers and wind turbines, as explored by the authors of [25; 26]. The main contribution of this study is the enhancement of the existing condition assessment concept for CBs, Ds, and ITs by integrating multiplicative criteria alongside additive ones. This new approach encompasses all condition-monitoring tasks. While prior studies [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21] focused primarily on individual maintenance tasks, this study addresses the operating principles, failure modes, practical monitoring tasks, and comprehensive calculation of the technical condition. The technical condition forms the basis for broader health assessments. The implementation of optimized maintenance strategies lies beyond the scope of this research study. According to the new assessment approach proposed in this study, the calculated condition value follows the maintenance priorities with the condition of the devices directly, emphasizing the detected deficiencies and penalizing the technical condition. Devices in poorer conditions are assigned higher urgency for intervention. Within the examined TSO, IBM Maximo serves as the central information system (IS) supporting condition-based preventive maintenance. This system manages and automates maintenance workflows, enabling the computerized evaluation of the technical condition. Consequently, this study presents a fully automated assessment of the device's conditions based on the calculated technical condition of devices in the HV SB. The primary innovations introduced in this study can be summarized as follows:  
* A novel methodology for classifying deficiencies and internal defects (failure modes) in CBs, Ds, and ITs by severity levels. * An enhanced device data model for calculating the technical condition that integrates multiplicative criteria--linked to failure mode severity and maintenance priorities--with additive criteria reflecting the operational history of the device. * Integration of the new HV SB device data model with databases containing historical and operational data (related maintenance processes, the nature of device operation, and external influences on its operation) sourced from IBM Maximo, facilitating fully automated assessment across a device's operational lifetime. * Capability to track the progression of technical conditions over time dynamically, generating a time-series profile that highlights the effects of maintenance priorities and the current device state. * A comparative analysis between the proposed data model and the existing model [23]. * A validation of the new model through a comparative evaluation of the technical condition results for the assessed devices, using both the newly proposed and existing models [23]. This manuscript consists of six sections. Section 2 describes the physical maintenance activities based on the device condition in the HV switchyards, which serves as input for the technical condition assessment using the new model. General information is also provided about the operation of the devices in the HV SB. Section 3 details the development of a new model for calculating the technical condition of the devices in the HV SB using multiplicative and additive criteria. The procedure for determining failure mode analysis as a result of the performed maintenance processes is presented, along with descriptions of the multiplicative and additive criteria.