Improvement of process management for testing and maintenance operations in high voltage transformers

The reliability of energy transmission and distribution systems is directly dependent on the performance of high-voltage power transformers, which are among the most critical components of modern power infrastructure. Power transformers require substantial investment and, in the event of a failure, can lead to prolonged outages, severe economic losses, and compromised operational safety. Therefore, ensuring the effective, reliable, and well-planned management of transformer testing and maintenance processes is essential for continuous energy supply and infrastructure dependability. However, in many utilities and industrial facilities, maintenance activities are still conducted based on time-based or reactive approaches, which limit fault prevention capability and reduce resource efficiency. The primary aim of this master's thesis is to develop an integrated process management model that addresses the testing and maintenance operations of high-voltage power transformers. Within this framework, international standards such as ISO 17359, IEC 60076, IEEE C57, and CIGRE TB 761 were used as references to reconstruct maintenance workflows. The proposed model is structured on the Plan–Do–Check–Act (PDCA) cycle and aims to digitalize maintenance management by integrating test data—such as Dissolved Gas Analysis (DGA), Partial Discharge (PD), Sweep Frequency Response Analysis (SFRA), thermal, and moisture measurements—into the decision-making process. Through the analysis of multi-source condition monitoring data, the model enhances maintenance continuity, enables pre-fault intervention, and reduces operational costs. Ultimately, this study proposes a process-based maintenance management approach for high-voltage power transformers, providing a conceptual framework that bridges traditional reactive maintenance practices with proactive, data - driven, and reliability-centered asset management systems.