Using the Exponential Weighted Geometric Mean (EWGM) Method to Optimise the FMEA as a Risk Assessment Methodology

Abstract

Failure Modes and Effect Analysis (FMEA) is a proactive, highly structured, and systematic approach for failure analysis. It has been also applied as a risk assessment tool, by ranking potential risks based on the estimation of Risk Priority Numbers (RPNs). This paper develops an improved FMEA methodology for strategic risk analysis. The proposed approach combines the Analytic Hierarchy Process (AHP) technique with the Exponential and Weighted Geometric Mean method (EWGM) to support risk analysis. AHP is applied to estimate the weights of three risk factors: Severity (S), Occurrence (O) and Detection (D), which integrate the RPN for each risk. The EWGM method is applied for ranking RPNs. Combining AHP with EWGM allows avoiding repetition of FMEA results. The results of the developed methodology reveal that duplication of RPNs has been decreased, and facilitating an effective risk ranking by offering a unique value for each risk. The proposed methodology focuses not only on high severity values for risk ranking but also it considers other risk factors (O and D), resulting in an enhanced risk assessment process. Furthermore, the weights of the three risk factors are considered. In this way, the developed methodology offers unique value for each risk in a simple way which makes the risk assessment results more accurate. This methodology provides a practical and systematic approach to support decision-makers in assessing and ranking risks that could affect long-term strategy implementation. The methodology was validated through the case study of a power plant in the Middle East, assessing 84 risks within 9 risk categories. The case study revealed that top management should pay more attention to key risks associated with electricity price, gas emissions, lost-time injuries, bad odor, and production.