This work introduces the application of Cohen’s kappa concordance coefficient as part of a comparative approach between different methods used to improve the FMECA analysis. The proposed approach considers the concordance assessment between different methodologies used in FMECA (Risk Isosurface function, VIKOR, ITWH, FWGM, Type-I and Type-II Fuzzy Inference System) when applied to the same problem and regarding an FMECA ranking selected as the reference one. The analyzed problem is a blood transfusion case study consisting of eleven failure modes widely used for benchmarking. Results show that Type-II fuzzy inference systems achieve the highest agreement regarding the reference FMECA ranking; one possible explanation for this result is that Type-II FIS considers uncertainty as an additional parameter. This approach proves effective to compare statistically different FMECA methods instead of the classical qualitative comparison between rankings.