Evaluating the effectiveness of a boiler plant's predictive maintenance system

A boiler plays a vital role in the process of generating electricity, hence power plants need to invest in effective maintenance strategies that ensure the boiler equipment and components are well maintained and function with minimal failures. As the technology evolves, the design of boiler equipment has also become more complex which has resulted in power plants favoring the predictive and preventive maintenance strategies; however, the power plant needs to ensure that the systems supporting the predictive maintenance strategies are properly implemented. The main function of the boiler predictive maintenance system is to predict the health status of the boiler, through tube wear rate monitoring to prevent unforeseen failure leading to a boiler emergency shutdown. At power plant X, the major cause of the boiler shutdown is boiler tube failure incidents. Such incidents still occur despite the implementation of the predictive maintenance system, thus the need for this study. In this study the effectiveness of the boiler's predictive maintenance systems is evaluated, and it is identified that the data collected during inspections for system prediction is not sufficient to predict the health status of the boiler, as the system is not configured to monitor the entire tube length and does not consider all failure mechanisms, hence production loss time of 9487 hours for 12 years.