A hybrid failure mode and effects analysis with decision-making trial and evaluation laboratory approach for enhanced fault assessment in power plants

Fault analysis and classification play a critical role in ensuring the reliability and safety of complex industrial systems, particularly in high-risk environments such as power generation. Failure mode and effects analysis (FMEA) is one of the tools used to identify, analyze, and classify faults to minimize their frequency, reduce their impact, enhance reliability, save operating costs, and improve competitiveness. However, FMEA is often limited by the subjective nature of expert evaluations, which can lead to inconsistencies when different experts assign varying scores to the same failure mode. To address this issue, a hybrid approach combining FMEA with the decision-making trial and evaluation laboratory (FDEMATEL) model was proposed. By integrating these tools, critical faults can be prioritized more effectively. This study aims to determine the priority of faults in gas units in a combined cycle power plant in Libya by using a hybrid method that was previously mentioned. FMEA initially prioritized critical failures, while FDEMATEL supplemented this analysis by evaluating the cause-effect relationships between failures, enabling a systemic reassessment of their rankings based on interdependencies. Python and Excel were used to perform the mathematical operations for both methods. The study revealed three key causal failure patterns: control system failure, air filtration system clogging, and fuel gas system leakage, which should be the focus of attention. The study recommends applying the FDEMATEL model to fields that require knowledge of the relationships between these elements.