Enhanced criticality analysis methodology using weighted Euclidean distance in developing condition monitoring framework

To ensure allocation of resources in gas power plants, this study emphasizes the development of a criticality analysis framework as the basis of maintaining uninterrupted power production. The primary focus is on advancing a robust criticality analysis using the Weighted Euclidean Distance method to accurately assess and prioritize equipment failures within the gas power plant. This approach addresses the limitations of traditional Failure Modes and Effects Analysis (FMEA), particularly the issue of subjectivity, by providing a more objective and scalable method for evaluating criticality. The analysis highlights the differences between the criticality ranks derived from the FMECA technique and those obtained from the proposed method, offering a more reliable basis for maintenance decision-making. Building on this criticality analysis, the study also establishes a structured framework for condition monitoring, aimed at refining predictive maintenance strategies and enhancing process management procedures. A comprehensive monitoring system will be designed and implemented, integrating techniques such as vibration monitoring, thermography, lubrication and wear debris analysis, performance monitoring, and human sensory observations. Furthermore, the study evaluates the effectiveness and feasibility of the implemented condition monitoring system, considering scalability for potential application across other areas of the gas power plant. By prioritizing criticality analysis and condition monitoring, this study aims to lay the groundwork for a proactive maintenance approach that not only enhances equipment reliability and operational efficiency but also contributes to the long-term sustainability and resilience of power generation.