The thesis provides a clear and thorough analysis of transformer health monitoring using Dissolved Gas Analysis (DGA) and Oil Quality Analysis (OQA). It effectively explains common transformer failure causes and highlights how diagnostic techniques can detect faults early. The study uses real field data, standard testing methods, and graphical tools such as the Duval Triangle to interpret transformer conditions. Your results show how trends in gas and oil parameters help predict ageing, insulation degradation, and potential failures. Overall, the thesis contributes valuable insights for improving transformer reliability and supporting condition-based maintenance strategies.